Molecular Engineering of Selective Recognition Elements as Coatings for Sensor

Platforms

by

Justyn Wayne Jaworski

B.S. (Boston University) 2004

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Joint Doctor of Philosophy

with the University of California, San Francisco

in

Bioengineering

in the

GRADUATE DIVISION

of the

UNIVERSITY OF CALIFORNIA, BERKELEY

Committee in charge:

Professor Seung-Wuk Lee, co-Chair

Professor Arun Majumdar, co-Chair

Professor Tejal Desai

Professor Ting Xu

Spring 2009

The dissertation of Justyn Wayne Jaworski is approved:

Prof. Seung-Wuk Lee, co-Chair Date

Prof. Arun Majumdar, co-Chair Date

Prof. Tejal Desai Date

Prof. Ting Xu Date

University of California, Berkeley

Spring 2009

Molecular Engineering of Selective Recognition Elements as Coatings for Sensor

Platforms

Copyright 2009

by

Justyn Wayne Jaworski

1

Abstract

Molecular Engineering of Selective Recognition Elements as Coatings for Sensor

Platforms

by

Justyn Wayne Jaworski

Joint Doctor of Philosophy

with the University of California, San Francisco

in

Bioengineering

in the

GRADUATE DIVISION

of the

UNIVERSITY OF CALIFORNIA, BERKELEY

Professor Seung-Wuk Lee, co-Chair

Professor Arun Majumdar, co-Chair

This dissertation focuses on the aspects of selectivity in chemical sensing systems. While

a number of sensing platforms exist that are capable of highly sensitive detection, the

common factor of poor selectivity continues to limit their widespread use. In this work,

we explore the use of sequence specific biopolymers identified through combinatorial

screening approaches for the creation of molecular recognition elements for chemical

sensor coatings. Particularly, a library of bacteriophage was screened to identify which

2

of the unique peptide sequences present on their protein coat could provide the highest

affinity binding to a target chemical. We specifically targeted small molecules including

trinitrotoluene (TNT) and dinitrotoluene (DNT). From phage display experiments, we

identify consensus peptide motifs, and we analyzed their binding efficacy based on

affinity and specificity. Additionally, we demonstrate that the standalone receptor for

TNT could be incorporated into a polymeric coating while retaining its functionality. In

doing so, a peptide based sensor coating was developed and implemented onto a common

Quartz Crystal Microbalance sensing platform. Liquid phase experiments demonstrated

the sensing ability of this system selectivity respond to TNT while remaining relatively

inert to the analogue DNT molecule. Furthermore, a polymeric based sensing system

was developed with the TNT receptive motif to create a widely deployable sensing

system. Integration was simply a matter of coupling a chromic responsive polymer at the

final step of receptor synthesis. In doing so, a modular sensing system was created which

demonstrated target binding to small molecules, such as TNT, or large cells, such as

fibroblasts, depending on the surface receptor motif. Finally, we show that the

fabrication approach could be optimized to enhance the sensitivity of the system to small

molecule targets.

Our results demonstrate that short amino acid sequences can be identified through phage

screening for small molecule binding and further developed into a sensor coating. The

receptors may be implemented onto a common QCM based sensor or onto a newly

develop chromic responsive system, thus demonstrating the broad sensor integration

capabilities of these receptive motifs. We anticipate this approach may lead to furthering

3

the development of molecular recognition elements by utilizing the biological toolkit of

evolutionary screening for selective receptors. In the future, we hope such approaches

will be used to gain a mechanistic understanding of molecular recognition which would

have a profound impact on the chemical sensing community.

_________________________

Co-Chair, Dissertation Committee

_________________________

Co-Chair, Dissertation Committee

i

Dedicated to Sonja Jaworski and Hilda Todd

ii

Table of Contents

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv

Chapter 1: Introduction

1.1 Challenges and Current Approaches in Chemical Sensing . . . . . . . . . . . . . . . . . . . . . 1

1.2 Molecular Recognition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.3 Approaches to Achieving Molecular Recognition. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.4 Challenges and Future Trends in Chemical Sensor Coatings. . . . . . . . . . . . . . . . . . .19

Chapter 2: Phage Screening of Small Molecule Targets for Selectivity Motifs

2.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

2.2 Phage Display for Selection of TNT and DNT Binding Peptide Motifs . . . . . . . . . .21

2.3 Phage Display for Selection of Methyl Parathion Binding Peptide Motifs. . . . . . . . 27

2.4 Phage Display for Selection of Eugenol Binding Peptide Motifs. . . . . . . . . . . . . . . 30

2.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Chapter 3: Analysis Techniques for Identifying Selective Binding Motifs

3.1 Selective Binding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.2 Synthesis of Standalone Receptors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45

3.3 Mutational Analysis Binding Assay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

3.4 Isothermal Titration Calorimetry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

3.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

iii

Chapter 4: Selective Coatings for Chemical Sensing

4.1 Introduction to Chemical Sensing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

4.2 Overview of a Peptide Based Sensor Coatings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.3 Coating Design for Surface Stress Based Sensors. . . . . . . . . . . . . . . . . . . . . . . . . . . 54

4.4 Coating Design for Quartz Crystal Microbalance Sensing Platform. . . . . . . . . . . . . 62

4.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Chapter 5: Development and Optimization of a Polymeric Sensing Vesicle

5.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85

5.2 Overview of Polydiacetylene as a Sensing Platform. . . . . . . . . . . . . . . . . . . . . . . . . 86

5.3 Experimental Section. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

5.4 Results and Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96

5.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Chapter 6: Summary and Outlook

6.1 Molecular Recognition Elements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

6.2 Sensor Coatings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

6.3 Sensing Platforms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114

Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

iv

List of Figures

Figure-1: a) Typical synthetic polymers consist of a monomer repeated multiple times.

Target analyte molecules generally have one binding site with such polymers. b)

Sequence-specific polymers have different residues strung together in a single chain.

Depending on the sequence, target molecules can form multiple binding sites with the

polymer, which leads to higher free energy of binding and thereby higher selectivity

against background interfering molecules.

Figure-2: Schematic of molecular imprinting approach to creating target selective

recognition motifs.

Figure-3: Overview of phage display screening process against molecular crystal TNT.

Figure-4: Schematic of SELEX screening process for identifying RNA or DNA based

aptamers for target specific binding.

Figure-5: Schematic diagram showing our biomimetic approach to develop selective

coatings for gas-phase explosive molecules. Identified molecular recognition elements

from the directed evolution process of phage display are used for their multivalent

recognition of explosive targets in liquid-phase screening. Through chemical

modification, the peptide receptors are linked with oligo(ethylene glycol) and

immobilized as coatings capable of binding explosive targets in air.

v

Figure-6: Phage display sequence results after the third and fourth rounds of phage

display screening against a TNT substrate.

Figure-7: Phage display sequence results after the third, fourth, and fifth rounds of phage

display screening against a DNT substrate.

Figure-8: Phage display screening results: a) converged amino acid sequences from the

fourth round of phage display screening with a noted percentage abundance obtained

from sequencing results, b) selectivity screening of the DNT receptor and TNT receptor

against DNT substrates and TNT substrates with the level of binding quantified from

phage titration. Nonspecific binding levels are identified by PS binding phages against

TNT and DNT substrates. All data are presented as the mean ± standard deviation.

Figure-9: Chemical structure of the pesticide methyl parathion, a small molecule

compound target used for phage display screening.

Figure-10: Phage display sequence results from experiment 1 after the third, fourth, and

fifth rounds of phage display screening against a methyl parathion substrate.

Figure-11: Phage display sequence results from experiment 2 after the third and fourth

rounds of phage display screening against a methyl parathion substrate.

vi

Figure-12: Overview of the method for immobilizing liquid target (eugenol) onto a solid

support (TentaGel beads) to allow a method for phage display screening of liquid targets.

Figure-13: Overview of the phage display screening process developed against a liquid

target immobilized onto a solid support. An initial screening against the solid support

alone is performed to remove phage that may bind to the support material.

Figure-14: Phage display sequence results from the fourth round of phage display

screening against eugenol, an immobilized liquid target.

Figure-15: Phage display sequence results from the fifth round of phage display

screening against eugenol.

Figure-16: Comparison of non-selective conventional polymer coatings to target specific

biopolymers.

Figure-17: The pIII receptors present on phage that were used for competitive screening

analysis. The number of appearances for a given receptor after competitive screening

(last column) were found from the DNA sequencing results.

Figure-18: a) Receptor sequences from phage primarily from TNT panning used in the

following specificity screening, and b) specificity screening results of phage against TNT

vii

and DNT substrate. Levels of binding represented as the ratio of phage remaining bound

after interaction and washing as compared to the initially exposed number of phage.

Figure-19: a) Receptor sequences from phage primarily from DNT panning used in the

following specificity screening, and b) specificity screening results of phage against TNT

and DNT substrate. Levels of binding represented as the ratio of phage remaining bound

after interaction and washing as compared to the initially exposed number of phage.

Figure-20: Phage display screening results of converged amino acid sequences from the

fourth round of phage display screening.

Figure-21: Selectivity screening of the DNT receptor and TNT receptor against DNT

substrates and TNT substrates with the level of binding quantified from phage titration.

Figure-22: Mutational analysis for identified TNT and DNT binding peptides. (a)

Sequence of receptors synthesized with C-terminal biotinylated lysine to allow

functionalization with the fluorescent probe Atto-425. TNT-BP and DNT-BP represent

the identified TNT and DNT binding receptor sequences, respectively, while H-Sub

(histidine substituted by alanine) and W-Sub (tryptophan substituted by alanine) are

mutations at amino acids 1 and 2 of TNT-BP. Scram-Ctrl is a nonspecific sequence

derived from scrambling the TNT-BP sequence to demonstrate the sequence importance

for encoding target selectivity and hence a negative control. (b) Fluorescence binding

assay against TNT substrate and DNT substrate, revealing the importance of tryptophan

viii

and histidine residues in TNT-BP as well as demonstrating the ability of the lone peptides

TNT-BP and DNT-BP to bind selectively to their targets in liquid when not associated

with the other phage body proteins. Fluorescence levels are normalized to the BSA

fluorescence background signal (P<0.0001, n=4). All data are presented as the mean ±

standard deviation.

Figure-23: Measurement of the dissociation constant of the complex between TNT and

the peptide TNT-BP determined from isothermal titration calorimetry. Data points

(values for the integrated heat change during each injection, normalized per mole of

TNT) are represented by filled squares. A one-site model was used to fit the data. The

solid red line is the calculated curve using the best-fit parameters.

Figure-24: Operation mechanism of micromembrane surface stress sensor.

Figure-25: Gas-phase screening for partition coefficients of various coatings on Si

exposed to DNT gas. The values are normalized to the DNT gas partition coefficient of

blank Si substrates to observe the contribution attributed solely to the coating layer.

Partition coefficients are calculated as the ratio of the concentration of analyte bound to

the coating (identified through thermal desorption GCMS) to the concentration of analyte

in the exposed gas headspace.

ix

Figure-26: Analysis of the level of TNT substrate binding for the designated TNT

binding peptide (TNT-BP) as well as a scramble TNT-BP sequence as control and a

trinitrobenzene binding sequence (TNB-Ctrl).

Figure-27: Selective gas-phase binding assay for DNT-specific coating: (a) schematic

diagram of the DNT binding peptide conjugated to oligo(ethylene glycol) and their

coating onto a gold surface for gas-phase selective binding; (b) partition coefficient of

DNT receptor coatings exposed to TNT gas and DNT gas. The values are normalized to

the target gas partition coefficient of OEG coating on a Au substrate to isolate the

contribution attributed to the DNT receptor element. Partition coefficients are identified

as the ratio of the concentration of analyte bound to the coating to the concentration of

analyte in the exposed gas headspace. The results are obtained through thermal

desorption GC-MS experiments on exposed coating surfaces (P < 0.001, n = 4). All data

are presented as the mean ± standard deviation.

Figure-28: Analysis of a hydrophilic and hydrophobic polymeric coatings using Quartz

Crystal Microbalance to identify the humidity response.

Figure-29: Chemical structure of the poly(ethylene-co-glycidyl methacrylate), called

'PEGM', which was found to have the lowest humidity response of the polymers tested.

Hence, it was chosen as the polymeric support for attachment of selective receptors and

coating onto the QCM.

x

Figure-30: Schematic of attachment mechanism for amine on receptor with epoxy grou

of poly(ethylene-co-glycidyl methacrylate).

Figure-31: XPS spectra of C 1s (first row), N 1s (second row) and S 2p (third row) peaks

of TNT receptor deposited on a bare Au slide before (column A) and after (column B)

washing in water overnight. Experimental spectra are plotted in solid line, fitted spectra

in dashed line, and fits for each peak component in dash-dotted line. The inset in the C

peak, column B, represents the C 1s spectrum recorded on a bare Au substrate.

Figure-32: XPS spectra of C 1s (first row), N 1s (second row) and S 2p (third row) peaks

of PEGM deposited on Au (sample 'PEGM/Au') (column A), and TNT receptor bound to

PEGM on Au (sample 'TNTrec/PEGM/Au') before (column B), and after (column C)

washing in water overnight. Experimental spectra are plotted in solid line, fitted spectra

in dashed line, and fits for each peak component in dash-dotted line.

Figure-33: XPS spectra of N 1s region for samples prepared by deposition of 660 nmol

of TNT on a) PEGM/Au and b) PEGM with TNT receptor. Experimental spectra are

plotted in solid line, fitted spectra in dashed line, and fits for each peak component in

dash-dotted line.

Figure-34: Percentage of TNT remaining on samples containing TNT receptor, DNT

receptor, and just PEGM after overnight washing in water. The values were calculated by

xi

dividing the normalized area underlying the peak at ∼409 eV relative to TNT after

washing the sample in water to the normalized area of the same peak measured before

washing the sample, and multiplying the result by 100, to obtain a percentage. Details

about the normalization of the peak relative to TNT and p values calculated according to

Student’s t test are reported in the text

Figure-35: GC/MS measurements of a) the amount of TNT remaining on samples

containing TNT receptor, DNT receptor, and just PEGM after overnight washing in

water and b) the amount of TNT and DNT remaining on samples containing the receptor

specific for TNT, after overnight washing in water.

Figure-36: Schematics showing the two modes of operation of the QCM setup.

Figure-37: Change in QCM resonance frequency measured on a crystal coated with

PEGM/TNT receptor, after exposure of a solution containing TNT a) and DNT b),

respectively.

Figure-38: Schematic diagram of synthesis, composition, and assembly parameters

which must be optimized to achieve an effective colorimetric PDA vesicle based sensor.

Figure-39: Dynamic light scattering measurements analysis was used to characterize the

diameter of the range of assembled PCDA-Trp-His-Trp particles to be on average 162 nm.

xii

Figure-40: Effect of PDA polymerization times were analyzed by a) varying exposure of

PDA vesicles to identify the conditions for achieving maximal chromic response (trend

line added as guide), and b) identifying the length of UV exposure required for full PDA

vesicle polymerization as indicated by irreversibility of the system.

Figure-41: Effect of PDA functional end-group on initial blue percentage for 100%

surface functionality of PCDA (carboxyl), PCDA-Trp, and PCDA-Trp-His-Trp

Figure-42: Dependence of initial blue percentage on the surface density of vesicles

comprising various concentrations of peptide-conjugate PCDA-Trp-His-Trp. The dashed

line represents the minimum blue percentage (42%) required to have a visually detectable

chromic response of 15% change relative to the blue percentage provided at 100%

surface density.

Figure-43: Visible-absorption spectra of polymerized vesicles containing: a) 4 mol %

Trp-His-Trp surface receptor; b) 2 mol % Trp and 2 mol % Trp-His-Trp surface

receptor; c) 4 mol % Trp and 4 mol % Trp-His-Trp surface receptor; d) 4 mol % Gly-

Arg-Gly-Asp-Ser surface receptor. Solid lines represent the non-exposed spectra while

dashed lines represent spectra attained after target exposure. Exposed spectra are

normalized to the corresponding non-exposed spectra and y-axes scaled to clarify the

change in chromic response.

xiii

Figure-44: Dependence of alkane chain length on PDA-Trp-His-Trp sensitivity to TNT

target. Decreasing PDA lengths facilitate a higher chromic response over a range of TNT

concentrations.

xiv

Acknowledgements

I have been extremely fortunate to have had the opportunity to work with two advisors.

Both Professor Arun Majumdar and Professor Seung-Wuk Lee have been extremely

encouraging and supportive, and I am highly grateful for their eagerness to take on

challenging projects in the exciting field of chemical sensing. I am also deeply indebted

to them for giving me the freedom to work on areas of my interest during my graduate

study. Their scientific advice and insight into future areas of importance have taught me

that science is not merely performed for its own sake, rather science and engineering

should be done on behalf of the public. This has left a lasting impression that I will bring

with me in my upcoming research work.

I also would like to thank the members of Professor Majumdar’s and Professor Lee’s

groups. I gained a lot from Dr. Woo-Jae Chung’s extensive experience in solid-phase

synthesis, and I highly appreciate his advice, technical expertise, and friendship. Dr. Ki-

Young Kwon has also offered terrific advice, not only in terms of research but also

advice on life and careers. I would especially like to thank Eddie Wang for his friendship,

keeping the laboratory a fun place to work, and always having a useful answer to my

many questions. Additionally, I would like to thank Jin Huh, with whom this research

began. I cannot thank him enough for all those long hours spent working on sequencing

and phage screening experiments. I would also like to thank Yang Guo for his time and

efforts in developing different phage display screening strategies for various targets.

Anna Merzlyak has been a great friend, and I really enjoyed her support and unity to

finish our PhD simultaneously. My professional interaction with other fellow lab

xv

members has been intellectually very satisfying and has had a significant influence on my

research work. A partial list of those members I’d like to thank includes: Masae

Kobayashi, Jonathan Phillips, Rohit Karnik, Pramod Reddy, Woochul Kim, Srinath

Satyanarayana, Si-Hyung Lim, Robert Wang, Tony Tong, Yang Zhao, Renkun Chen,

Suzanne Singer, Chuanhua Duan, Kaal Baheti, and Digvijay Raorane. I would especially

like to thank Keisuke Yokoyama and Chris Zueger for their collaboration on the chromic

responsive sensor work. Besides being great friends and members of the Sensing Team,

they have always provided terrific advice, and I appreciated their hard work in helping

create this exciting sensor platform. Additionally, Dr. Marta Cerruti has been a great

friend and motivator, and her expertise in surface chemistry has been very helpful in

making this project a success. My friendships with some of the greatest people in

Berkeley and San Francisco are unforgettable, and I am highly appreciative. Our

solidarity has helped ensure a healthy level of laboratory life. I also gratefully

acknowledge the funding agencies that made this research possible, namely, the Bill and

Melinda Gates Foundation, the National Science Foundation, the Office of Naval

Research, the Center of Integrated Nanomechanical Systems, and the Department of

Energy.

I would also like to thank Dr. Ron Zuckermann for providing me with project advice,

training, and access to equipment in the Molecular Foundry for my experiments.

Additionally, I would like to thank Professor Kevin Healy for his guidance in helping

form my project aims as my qualifying examination chairman. Additionally, I thank

Professor Song Li for his help in structuring my coursework as my curriculum advisor.

xvi

My research experience at Berkeley would have been quite different without the

wonderful research rotations I had with Professor Jay Keasling and Professor Luke Lee.

I highly appreciate their advice and guidance during those rotations and beyond. I also

want to thank Professor Tejal Desai and Professor Ting Xu for serving on my dissertation

committee and for their wisdom in helping me to prepare for this work as well as my

qualifying examination. Also, I highly appreciated their suggestions on project directions

and materials usage. Finally, I would like to thank my family, though words cannot

express the gratitude I have for their motivation and support of my education.

1

Chapter 1: Introduction

1.1 Challenges and Current Approaches in Chemical Sensing

The ability to detect and analyze volatile organic compounds (VOCs) such as

explosives,1 pesticides,

2 disease markers,

3 and food aroma

4 has significant bearing on our

security, health, and general well being. As opposed to mobility-based5 and optical

sensors,6 those based on ligand-receptor binding that emulate the olfactory system enable

miniaturization. While there are several highly sensitive ways to convert ligand-receptor

binding to electrical or optical signals,7-13

the lack of selectivity has remained a key

challenge, making such sensors inadequate in many applications and preventing their

widespread use. At issue are functional coatings, which in the past have relied on arrays

of oxide layers,14

readily available polymers, 15

or even de novo designed receptors.9, 16-18

Although such arrays provide a pattern of binding that can be mathematically processed

to distinguish molecular species, the affinity differences are often insufficient for highly

selective and sensitive chemical analysis in realistic conditions.

1.1.1 Introduction to Current Sensing Platforms

While the focus of this research lies in the selective coating layer, it is important to first

look at the various chemical sensing platforms available. This is necessary in order to

effectively create a sensor coating amenable to the various signal transduction approaches

used by these sensors. The sensitivity of the transducer to ligand-receptor binding events

2

depends heavily on which sensing platform is to be used. The transduction can occur in

many ways: (i) change in electrical resistance of a chemoresistor or a chemo-field effect

transistor (chemFET);19, 20

(ii) frequency shift in mechanical resonance devices such as

quartz crystal microbalances, surface acoustic wave (SAW) devices, cantilever beams;7,

21-23 (iii) frequency shift in optical resonances such as surface plasmon resonance, cavity

resonance,24, 25

(iv) structural deflections such as in cantilever beams and membranes.26, 27

The above chemical sensing systems are effective provided they have an adequate sensor

coating which will provide a physical change attributed to the binding event. For a

ligand-receptor interaction event (as in the case of our sensor coating), binding may result

in three fundamental changes: (i) changes in local dielectric constant; (ii) addition of

mass; (iii) generation of intermolecular forces.28

A device capable of detecting each of

these physical changes simultaneously could be broadly used in detection of the ligand-

receptor binding events. The micromembrane and microcantilever systems may provide

a means of identifying all three of these changes. A change in mass addition or even

surface stress (attributed to intermolecular forces) could produce changes in the resonant

frequency detectable by capacitance measurements via a micromembrane or

microcantilever based sensor. A capacitance change could also directly be a result of

dielectric changes attributed to target binding attributed to analyte replacement of water

in the capacitive sensor.

3

1.1.2 Introduction to Current Sensor Coatings

The creation of a chemical sensing device capable of selective detection of a target

chemical is a deeply sought after technology. The accurate detection of various

chemicals related to explosive threats would significantly enhance homeland security

measures through protection of civilians and military forces. Example target molecules

of interest include volatile and semi-volatile small molecules such as TNT

(trinitrotoluene) which typically have a molecular weight in the 50-500 g/mol range.

Current sensor technologies have the opportunity for highly sensitive detection;7

however, the lack of proper selectivity continues to be the main challenge in creating a

chemical detection system which is successful against a background of various

interfering agents.29

System-level performance of chemical sensing systems is often quantified in terms of

receiver operating characteristic curves in which an optimally sensitive sensor would

want to maximize selectivity (or minimize the occurrence of false positives). The

current gold standard for sensitive and selective systems is based on gas chromatography-

mass spectroscopy (GC/MS). Unfortunately, these machines are very large, expensive,

and require complex data analysis. Aside from this, many successful chemical sensors

for di-atomic and tri-atomic molecules, such as NOx and CO2, have demonstrated

selectivity.30-35

Though these chemicals are important, there remains a void for selective

sensors of volatile organic compounds in the 50g/mol – 500g/mol range due to the lack of

diversity available in sensor coatings.

4

The most promising candidates for portable systems are based on transduction of ligand-

receptor binding to an electrical signal.36

This style of device typically uses an array of

polymers as coatings to generate a binding signature pattern.37, 38

While an interesting

approach, these polymers are unfortunately non-specific in their binding,39

which is

detrimental in two ways: (i) the affinity ratios between target analytes are not enough to

distinguish molecules of sufficiently low concentrations; (ii) the binding of background

chemicals is too high causing creating uncertainty in the acquired data. As a result, such

polymer-based systems have poor selectivity. To address the selectivity challenge we

looked to biology, which relies on selective ligand-receptor interaction for complex

molecular networks and interactions. Particularly, we are interested in biology’s use of

sequence-specific heteropolymers which are rich in structure and chemical functionality

as compared to bulk homopolymer coatings.40

1.1.3 Sensor Coating Formation

Many applications of polymers and biopolymers as sensor coating utilize the formation of

monolayers on a sensing surface. Typically these consist of either drop-cast polymers or

the more stable self-assembled monolayer. Self-assembled monolayers, or SAMs, are

stable, highly ordered, single layers of molecules that organize spontaneously during

adsorption to a solid substrate.41-45

Molecules involved in SAM formation have a distinct

“head” with affinity for the solid substrate and a “tail” usually consisting of alkyl or

ethylene glycol chains.40

Covalent chemical bonding between the head group and the

5

surface often plays a major role to stabilize the monolayer structures.44

Systems forming

SAMs include the adsorption of alkylthiols onto gold, alkylamines onto platinum, and

alkylchlorosilanes onto silica.43, 44

The development of such a coating material that contains a high density of specific

receptors with intact binding efficacy is a critical step for the fabrication of specific and

sensitive sensing devices. Coating receptor immobilization and SAM formation are

typically formed by solution preparation methods, where a solid substrate is introduced

into a solution of solvent and molecules with a head group having affinity for the

substrate.41

Ellipsometry is generally used to determine layer thickness and surface

plasmon resonance is used to study their in situ formation.43, 46

Although more

information can be gained from the technique of x-ray photoelectron spectroscopy which

is employed to determine uniformity of coverage, the orientation and tilt of the

molecules, and extent of their order.43

Chemically and biologically selective coatings

have gained attention in a wide number of fields with application ranging from

microelectronic structures to biocompatible solid surface environments. SAMs in

particular are of general interest in surface science as model systems, as well ordered

monolayers may be engineered with different head-tail combinations to provide insight

into interfacial phenomena and the relationships between structure and function.43, 45

6

1.2 Molecular Recognition

The ability to recognize an individual molecule is a daunting task from a design

perspective, while Nature has proven to be an effective source for such interactions.

Biology is filled with examples of selective molecular recognition. Recognition is in fact

vital for most cellular level processes (protein-protein docking, protein-DNA interactions,

enzyme-substrate catalysis, and receptor-ligand binding to name a few). While the

importance of these binding events is vast, little has been developed in terms of

predictive mechanisms for biomolecular interactions. One case in which we have

achieved a working knowledge of biomolecular interactions lies in the formulaic Watson-

Crick base pairing of DNA. The advent of this discovery undoubtedly changed biology

forever. Unfortunately for protein-protein and protein-small molecule interactions, we

are not given a set of generic patterns such as hydrophobicity, charge pairing, and shape

that we can use directly to predict which atoms will be involved in a binding event. To

achieve such goals, researchers utilize spectroscopy and crystallization approaches to

resolve Angstrom level intramolecular interactions as well as intermolecular host/guest

interactions. By looking at these examples from nature, we one day hope to achieve a

mechanistic understanding of all molecular interactions.

The concept of molecular recognition requires a receptor (host) molecule to participate in

non-covalent bonding with a specific ligand (guest). Several coupling events can occur

between a given receptor-ligand pair including hydrogen bonding, electrostatic

interactions, aromatic interactions, or Van der Waals interactions. In a molecular

7

recognition event, it is typical for several combinations of these interactions to occur

simultaneously. This multi-valence binding is critical for receptors to discriminate

between different potential guest target molecules. This differentiation for a specific

guest is deemed the selectivity of a receptor. Several factors have been found to

contribute to a selective molecular recognition event including: complementary

molecular shape, appropriate structural rigidity, and appropriate available binding sites.

The importance of molecular shape rests in the need to maximize the number of potential

interaction sites for a given binding event. In having a complimentary shape, a proper

distance between functional groups can be achieved for effective hydrogen bonding and

aromatic interactions. In contrast, a steric hindrance may force a receptor-ligand pair to

rely solely on long-range electrostatic interactions. From such steric consideration, it is

has been made evident that selective molecular recognition is enhanced by the intrinsic

inaccessibility of larger, non-target molecules.47

Another critical attribute for a receptor is for it to maintain an appropriate level of

plasticity or structural rigidity. Host receptors are generally not loosely swinging

molecular ropes; rather receptors possess an adequately rigid structure which can

minimize entropic losses that will arise due to reorganization or freezing of rotating bond

which occurs upon binding with the designated target guest molecule. As such, many

supramolecular chemists have utilized cyclic structures as receptor templates including

crown ethers, cryptands, spherands, cavitands, calixarenes, and porphyrins.48-52

As an

exception to this, researchers have found a protein-DNA interaction which was deemed

8

the “fly-casting mechanism”.53

In this instance, long-range weak forces are used to bring

the protein in proximity to the DNA at which point folding occurs in concert with the

binding event. As such, this protein folding event allows distant folding interactions to

contribute to an increased stability of the overall final recognition event. With that said,

typical conformation changes of a peptide backbone are generally less that 1A,54

while

functional side-chain dynamics can be significantly altered and restricted upon binding

supporting the notion that complex formations are generally enthalpic in nature.55

Finally, selective recognition of target molecule requires a receptor to have the

appropriate functional groups available for binding to occur. Binding sites containing

acid functionalities are capable of interacting ionically with amine and amide functions

on a target molecule or through hydrogen bonding with a variety of polar functionalities

including carboxylic acids, carbamates and carboxylic esters.56

Aromatic groups offer

another set of interaction mechanisms including cation- π, anion- π , and π–π interactions,

These interactions are quite ubiquitous through biological molecular recognition. Other

important bonding mechanisms, including van der Waals forces, charge-transfer

interactions, and dipole-dipole interactions, may also be present in the binding site if

beneficial for selective recognition of the corresponding target molecule. The following

sections will present some current approaches being used by researchers to achieve

molecular recognition. In addition, we will take a closer look at some attempts to

incorporate molecular recognition into chemical sensing platforms and the associated

challenges.

9

1.3 Approaches to Achieving Molecular Recognition

1.3.1 Overview

Molecular recognition stems from specific binding attributed to complementary

intermolecular interactions defined by structure and chemical functionality.9, 50, 57, 58

In

biology, three-dimensional shapes and chemistry diversity arises from the massive

combinatorial possibility of nucleic acids and peptide sequences.59, 60

Our goal is to use

this diversity and emulate molecular recognition in the non-living world.

Figure 1: a) Typical synthetic polymers consist of a monomer repeated multiple

times. Target analyte molecules generally have one binding site with such polymers.

b) Sequence-specific polymers have different residues strung together in a single

chain. Depending on the sequence, target molecules can form multiple binding sites

with the polymer, which leads to higher free energy of binding and thereby higher

selectivity against background interfering molecules.

Sequence-specific heteropolymers are rich in structure and chemical functionality as

compared to bulk polymers.40

Natural biopolymers, like nucleic acids and polypeptides,

are classic examples of materials that can adopt complex, defined structures that present a

variety of different functional groups in a particular geometry (Figure-1). These folded

structures are capable of highly-selective molecular recognition and efficient catalysis of

a wide variety of chemical transformations.61, 62

While bulk polymers have many

10

sophisticated and useful properties (structural, mechanical, optical, electronic…), they are

not capable of the degree of molecular recognition and transformation as that of proteins.

The ability of proteins to bind a wide variety of substances with high-affinities (e.g. small

molecules, nucleic acids, peptides, other proteins, etc) has long been exploited to discover

novel receptors for ligands of interest.63-65

Large combinatorial libraries of peptides,

antibodies, RNA or DNA can be readily prepared and screened.66

Peptide libraries have

been a particularly fruitful source of molecular diversity, as they have provided numerous

functional peptides.67

Such libraries can be readily prepared by both chemical and

biological methods. Using a relatively short peptide libraries, where a sequence of <20

residues is randomized, offers a significant advantage, in that that the discovered

receptors can be readily synthesized on a large scale for coupling with other materials or

incorporation into devices. In order to improve the specificity of the sensory molecules,

our approach is to exploit established chemical and biological toolkits to develop specific

recognition elements.

It is widely accepted that molecular recognition is essential to biological signal

transduction, enzymatic processes, gene expression, and a number of other cellular level

processes which are vital for sustaining life. Using structural information of existing

receptor-ligand docking events, researchers have been able to identify steric and

electronic conformations of selective binding events. In addition, replacement of

functional groups through mutational analysis has also allowed key bonding components

of an interaction to be identified along with their contribution to binding affinity. In

11

general, thermodynamic and kinetic studies can provide a measure of substrate affinity

from association constants with which specificity can be determined. In order to better

control the selectivity of biological systems and to exploit these mechanisms for other

purposes (such as chemical sensing), researchers have attempted to devise ways of

creating receptors capable of selective molecular recognition. Herein we will discuss the

approaches to achieving molecular recognition through molecular imprinting,

supramolecular chemistry, protein engineering, and finally screening technologies

including phage display. Phage display will be discussed in depth, as this technology was

utilized in this study for identification of small molecule receptors.

1.3.2 Molecular Imprinting

The concept of molecular imprinting (depicted in Figure-2) utilizes a target molecule of

interest to create a template within a polymeric system which once removed will leave a

cavity (or binding site) available for selectively binding identical target molecules. To

create such binding sites, monomers possessing particular functional groups (usually

methacrylates) are mixed in solutions containing the target “template” molecules of

interest. A cross-linking agent is also added to the mixture in order to “cast” the

functional monomers around the template molecules. The target molecule is then

disrupted or washed from the polymeric film to leave an empty template site available for

future binding to occur.

12

Figure 2: Schematic of molecular imprinting approach to creating target selective

recognition motifs.

One such case of molecular recognition via molecular imprinting utilized L-tryptophan as

a template target molecule to demonstrate enantiomer selectivity against D-tryptophan.68

In this study, L-tryptophan was cast into a polymer film using acrylamide functional

monomers and various concentrations of cross-linking agent (1,1,1-Trimethylolpropane

trimethacrylate). The researchers implement the polymeric film onto a quartz crystal

microbalance based sensor to demonstrate preferential interaction for L-Tryptophan over

D-tryptophan. In fact, the sensor was capable of a detection limit of 80uM. It should be

noted, that D-tryptophan did produce a signal, though it was considerably less than that

for the target L-tryptophan. Interestingly, the researchers found that increasing the cross-

linking density resulted in enhanced selectivity to a certain point, which is believe to be

due to the stabilization of the polymer binding pocket.

While the concept of molecular imprinting is very alluring, one should be aware of its

limitations. Primarily, the incidence of non-specific interactions is still a concern as the

13

site formation is polyclonal. Since the polymer film may have various different template

sites which possess various confirmations and hence affinities, the polymer film cannot

achieve purely selective molecular recognition. In addition, cross-linked polymer

systems can easily undergo swelling or shrinkage depending on the environment. In

some instance, temperature and humidity can drastically deform imprints thereby

rendering them impractical. The extent of cross-linking can easily impact the percentage

of functioning imprints on the polymeric film. Extensive cross-linking makes many

imprint sites inaccessible, while insufficient cross-linking results in unconstrained

templates which can result in altered template morphology. Despite the short-comings of

the approach, it has provided a significant advance toward selectivity in chemical

sensing.

1.3.3 Supramolecular chemistry

Using computational and theoretical means, supramolecular chemistry has been used to

design receptors to be tailor made recognition elements for specific target molecules. By

engineering the correct curvature and functionality to fill the space complementary to the

given target molecule, research have demonstrated high affinity target binding. One such

receptor was designed to have a concave binding site with the right size and shape for

choline.52

It is expected that strong cation-π interaction are occurring, as the researchers

have demonstrated the ability to preferentially bind choline (Kd of 83 uM) over

acetylcholine (Kd of 250 uM).

14

Cavitands, similar to the one mentioned above for choline binding, have the ability to

bind to aliphatic and aromatic guests in both gas and liquid.69, 70

As such, several

research groups have implemented these supramolecular based receptors, including

cavitands, crown-ethers, and metalloporphyrins, onto chemical sensing platforms.16, 18, 52

A particular example of a sensor that utilizes supramolecular chemistry takes the form of

a quartz-crystal microbalance coated with cavitands which are responsive to organic

molecules in both liquid and vapor phase.71

The sensor, which was intended to be

selective, actually showed a response to multiple different targets. While a preference for

aromatic and chlorinated hydrocarbons was demonstrated, this demonstrates the difficulty

in achieving highly specific molecular recognition. The research did successfully

demonstrate that different cavity organizations and shapes elicit different response

behavior. This indicates that it should be possible to specifically control the selectivity

based on the supramolecular design.

1.3.4 Protein engineering

Perhaps, the most successful approaches to achieving molecular recognition have been

through the use of protein engineering. In protein engineering, molecular recognition is

achieved by either borrowing existing molecular recognition domains from nature or

modifying binding/catalytic sites for altered specificity. To facilitate this, researchers

have utilized a combination of a computational approach, in which receptive domains are

analyzed in silico with extensive modeling of interacting domains,17, 72

and a rapid

evolutionary approach, generally DNA shuffling and site directed mutagenesis.73

While

15

many mutagenesis strategies exist, it has become a consensus that the optimal mutation

rate is dependent on the methodology of the mutagenesis as well as the organism and

protein being modified.74

Using random mutagenesis, researchers group have found it possible to engineer proteins

for selective molecular recognition. A particularly interesting example of this involved

the directed evolution of G protein coupled receptors (GPCR) to be activated by a pre-

designated target molecule.75

Initially, a library of chimeric GPCRs were created, which

were made insensitive to acetylcholine by replacement and random mutagenesis of the

target recognition site. The GPCR library was cloned into yeast and designed such that

activation would result in histidine production. This was important for screening as the

yeast were then grown in His deficient media to screen for activation. Screening was

performed in the presence of clozapine-N-oxide which is a pharmacologically inert small

molecule. By identifying the surviving yeast clones, the researchers were able to isolate

GPCR which were activated by clozapine-N-oxide. The sequences were recovered and

underwent additional mutagenesis and screening at lower clozapine-N-oxide

concentration to enrich high affinity target binders. Through this strategy the group was

able to achieve selective molecular recognition via GPCRs with activation at less than

5nM of clozapine-N-oxide while remaining insensitive to acetylcholine. This reflects a

significant advance for molecular recognition and helps solidify protein engineering as a

viable approach to re-engineering receptor protein selectivity.

16

1.3.5 Phage Display and SELEX Screening technologies

Genetic engineering of phage provides a rapid tool to identify specific binding peptide

motifs against various substrates including proteins, cell surfaces, and even inorganic

semiconductor or metallic surfaces. By mimicking the evolution process in nature, the

phage is used as an information mining tool to identify specific peptide sequences

capable of recognizing desired materials at the molecular level. Phage display is a

combinatorial process to identify specific binding peptides which utilizes phage and

bacterial biology through a fast, directed-evolution method.76

M13 bacteriophage, a

bacterial virus, is comprised of a single stranded DNA encapsulated by various major and

minor coat proteins. It has a long-rod filament shape that is approximately 880 nm in

length and 6.6 nm in width. The viral peptide capsid is composed of 2,700 copies of

helically arranged major coat protein, known as pVIII, and 5-7 copies of other proteins

(pIII, pVI, pIX and pVII) located at either end of the phage. All of the above proteins can

be genetically modified to display short (8-12 amino acids) peptide sequences at various

locations on the phage. By inserting randomized DNA sequences into specific locations

of the phage genome, a highly diverse library of peptides (up to 109 random sequences)

can be displayed on the viral particles. To select the best binding peptide sequence for a

given target material, the engineered phage library pool goes through several rounds of

selection processes. This is depicted in the following figure with the case of a TNT

(trinitrotoluene) crystal target.

17

Figure 3: Overview of phage display screening process against a molecular crystal

target of TNT.

Initially, the phages are allowed to bind to the target. The non-bound phages are then

washed away, while the remaining (stronger binding) phages are eluted, captured, and

amplified through infection of an E. coli bacterial host. This evolutionary approach to

select the fittest binding peptide sequence is repeated several times with consecutively

more rigorous binding conditions to enrich the phage with the best affinity peptide for the

target. Finally the dominant binding peptides are identified by DNA analysis of the phage

genome.

Traditionally this technique has been used to identify small antibodies and study protein

interaction.77

Though, recently phage display has been utilized to identify peptide

sequences with affinity for a variety of inorganic substances, such as semiconducting,

18

magnetic, and metallic materials.78, 79

Other screening technologies include SELEX,

Systematic Evolution of Ligands by Exponential Enrichment, which utilizes RNA or

DNA libraries. Commonly, the libraries consist of RNA in a stem-loop structure with the

loop region comprising the variable region.80

Similar to the phage display screening

approach described above, a series of target binding, washing, and enrichments steps are

carried out until a consensus sequence is attained which binds well to the target of

interest. Generally, the binding mechanisms for these recognition elements take one of

the following forms: 1) a previously unstructured aptamer folds to conform to a stable

structure around the target; 2) a large stable secondary RNA structure acts as a docking

site for target binding.

Figure 4: Schematic of SELEX screening process for identifying RNA or DNA

based aptamers for target specific binding.

One such RNA aptamer, screened to bind to the target Vitamin B-12, was found to have a

dissociation constant of approximately 90nM.81

The strong aptamer-target recognition

19

was analyzed by NMR to show that indeed steric complementarities, hydrophobic

packing, and electrostatic interactions were essential for binding. Even though aptamer

screening technology can provide high-affinity binders, the major limitation of such

nucleic acid based recognition elements for chemical sensing platforms remains in their

instability as a coating material. Primarily, RNA and DNA are easily degraded which

unfortunately prevents their use as a practical sensor coating.

1.4 Challenges and Future Trends in Chemical Sensor Coatings

Molecular detection is an important research topic in such areas as environmental

analysis (detection of pollutants),82

food industry (food spoilage and quality tests),83

and

security (detection of explosives).1 While most sensors presented in the literature are

highly sensitive, often their selectivity is insufficient for performance in the field. In

practical applications selectivity is critical for successful detection, where the molecule of

interest exists in a complex environment together with many other species that can create

false positive signals. This is primarily attributed to the lack of diversity available for

sensor coatings specific for these targets,84

as most current coating technologies rely on

weak or non-specific molecular interaction.10, 11, 14, 15, 85-88

20

Chapter 2: Phage Screening of Small Molecule Targets for Selectivity Motifs

2.1 Introduction

Molecular biology is replete with examples where weak interactions based on hydrogen

bonding or van der Waals interactions can lead to highly specific molecular recognition

through multivalent or cooperative binding. The diversity of chemistry and structure

produced by sequence-specific biopolymers such as nucleic acids and peptides allows

specific multivalent receptors to be created for a wide range of target ligands. The

immune system, for example, utilizes this to create specific protein-based receptors

against a large variety of foreign antigens. The use of sequence-specific heteropolymers

and multivalent binding has, however, not been thoroughly explored for the detection of

VOCs. While oligomers of DNA and RNA have been used recently,89

the multivalency

of their binding against VOCs has remained undetermined. Moreover, the diverse

chemistry of amino acids suggests that peptides are better suited as receptors against a

wide range of target molecules. The challenge, however, is to identify the specific N-mer

amino acid sequence that provides the strongest multivalent binding among 20N possible

sequences. We utilized the combinatorial screening power of phage display, an

information mining tool, for the identification of peptides that can specifically recognize

a desired target material at the molecular level (Figure-5). Evolutionary screening

processes have been previously used in liquid environments for diverse material targets

including semiconductors,78, 79

metals,90-92

and proteins.77, 93

21

Figure 5: Schematic diagram showing our biomimetic approach to develop selective

coatings for gas-phase explosive molecules. Identified molecular recognition

elements from the directed evolution process of phage display are used for their

multivalent recognition of explosive targets in liquid-phase screening. Through

chemical modification, the peptide receptors are linked with oligo(ethylene glycol)

and immobilized as coatings capable of binding explosive targets in air.

2.2 Phage Display for Selection of TNT and DNT Binding Peptide Motifs

Utilizing phage display we pursued the selection of peptides which could selectively bind

to the explosive trinitrotoluene (TNT). Additional phage display experiments were

performed to identify selective molecular recognition elements for dinitrotoluene.

Receptor screening utilized a phage library which possessed 3.9x109 different peptides,

composed of both linear 12mer (Ph.D.™-12) and constrained 7mer (Ph.D.™-C7C)

random amino acids, fused to the pIII coat proteins of M13 phages. The input phage

library solution was prepared by adding 10 µL of each library to 1mL of 0.1% TBST

buffer (50 mM Tris-HCl [pH 7.5], 150 mM NaCl, 0.1% [v/v] Tween-20). In order to

eliminate substrate heterogeneity, we screened the library against the molecular crystal

22

form of TNT and DNT using standard phage display for peptide selection.78, 79

Phage

display was performed with the initial binding condition of 0.1% TBST for 30 minutes at

room temperature on a rocking platform with 5 mg of target, TNT or DNT crystals.

Following binding, a series of 10 wash steps were performed using the same binding

buffer to remove non-specific binders. Specific binding phages were eluted with 1mL of

0.2 M Glycine-HCl [pH 2.2], 1 mg/ml BSA. The progressive screening rounds utilized

increasing surfactant concentration to increase stringency of binding to TNT or DNT

targets. Screening results were obtained through sequence analysis of the receptor region

following each screening round.

23

Figure 6: Phage display sequence results after the third and fourth rounds of phage

display screening against a TNT substrate.

24

The sequences seen in Figure-6 represent the phages sequenced after the third and fourth

rounds of phage display screening against a TNT substrate under a binding condition of

pH 7.5. The sequence ID represents “Substrate - Binding Conditions - Round/Experiment

- Phage Sample”. The abundance listed on the right reflects the number of times a given

receptor sequence appeared from the sequencing results. After each round, approximately

20 phage samples were submitted for sequencing.

25

Figure 7: Phage display sequence results after the third, fourth, and fifth rounds of

phage display screening against a DNT substrate.

The sequences seen in Figure-7 represent the phages sequenced after the third, fourth,

and fifth rounds of phage display screening against a DNT substrate under a binding

condition of pH 7.5. The sequence ID represents “Substrate - Binding Conditions -

Round/Experiment - Phage Sample”. The abundance listed on the right reflects the

26

number of times a given receptor sequence appeared from the sequencing results. After

each round, approximately 20 phage samples were submitted for sequencing.

The phage display results from third and fourth round screenings against molecular TNT

crystals are represented in the Figure-6. After four rounds of TNT screening, we

identified TNT binding sequences with the consensus motif of Trp-His-Trp-X (X:

hydroxylated, amine, or positively-charged side chain) at the N terminus of the receptor.

Similarly, the resulting phage display sequences from third, fourth, and fifth round

screenings against the molecular DNT crystal target can be seen in Supplementary

Figure-7. Through these experiments, we arrived at the consensus DNT binding motifs

and TNT binding motifs depicted in Figure 8a.

27

Figure 8: Phage display screening results: a) converged amino acid sequences

from the fourth round of phage display screening with a noted percentage

abundance obtained from sequencing results, b) selectivity screening of the DNT

receptor and TNT receptor against DNT substrates and TNT substrates with the

level of binding quantified from phage titration. Nonspecific binding levels are

identified by PS binding phages against TNT and DNT substrates. All data are

presented as the mean ± standard deviation.

2.3 Phage Display for Selection of Methyl Parathion Binding Peptide Motifs

In addition to explosive molecules, we aimed to utilize this phage display based selection

strategy for other small molecule targets of interest. Particularly, we were interested in

using this system for identifying receptors to organophosphates. Organophosphate

28

detection holds significant interest in terms of environmental safety, as this class of

chemicals constitutes pesticides and chemical warfare agents.94

To identify a receptor for

a particular organophosphate, we pursued the screening of methyl parathion, seen in

Figure-9.

Figure 9: Chemical structure of the pesticide methyl parathion, a small molecule

compound target used for phage display screening.

Methyl parathion is a small molecule compound used extensively as an agricultural

chemical to control the presence of insects. Methyl parathion has show to be extremely

hazardous to human health. Exposure has shown to cause disorders in the reproductive

and cardiovascular system, and its role as an acetylcholinesterase inhibitor leads to

neurological degeneration.95

Unfortunately, this highly toxic chemical often becomes

present in nearby streams and water sources as a result of run-off.96

As such, this

molecule is an attractive candidate for chemical sensing applications. Detection of

methyl parathion presence, may aid in preventing its inadvertent consumption, thereby

preventing the occurrence of a number of associated physiological disorders. Previously,

researchers have attempted to use quartz crystal resonator based sensing devices in

combination with antibodies for methyl parathion.97

A number of other research groups

have utilize the enzyme, Organophosphorus Hydrolase, as the selectivity element on

potentiometric sensing platform,98

optical based biosensors,99

and amperometric

biosensors.100

Here in, we pursued an improved selective coating to the large protein or

29

antibody for methyl parathion by using our evolutionary screening approach. By

identifying a shorter peptide sequence capable of binding to methyl parathion, we hoped

to maintain the selectivity of the antibody or enzyme while incorporating the high

stability of small peptides onto a sensor coating.

Figure 10: Phage display sequence results from experiment 1 after the third, fourth,

and fifth rounds of phage display screening against a methyl parathion substrate.

Using the same screening approach described in the previous section for determining

explosive binding receptors, we performed phage display to identify homologous leads as

potential receptors for methyl parathion.

30

Figure 11: Phage display sequence results from experiment 2 after the third and

fourth rounds of phage display screening against a methyl parathion substrate.

Notice that the Asn-Ile-Ile-Thr-Thr-Gln-Asn-Trp-Trp-Lys-Gln-Thr sequence appeared as

the most abundant in both experiments. Researchers have identified important amino

acid residues involved in the binding of methyl parathion, by identifying the crystal

structure of methyl parathion hydrolase.96

Looking at the binding site for methyl

parathion in this enzymes, the researchers found that the binding pockets are lined by

hydrophobic residues including Leu65, Leu67, Phe119, Trp179, Phe196, Leu273 and

Leu258. After modeling of the methyl parathion substrate into this cavity, the

researchers data suggests that the the Phe119 and Phe196 are ideally placed to anchor the

phenyl group of methyl parathion.96

Interestingly, our results from evolutionary

screening also show an aromatic rich domain of Trp-Trp which may also participate in

non-covalent interaction with phenyl groups.

2.4 Phage Display for Selection of Eugenol Binding Peptide Motifs

The final target we pursued to identify a binding motif for was eugenol, a liquid target

which has a characteristic aromatic scent of cloves. This scent was chosen in particular

to provide a chemical which has high vapor pressure. To utilize phage display for this

31

liquid target, a new screening strategy was developed. Initially TentaGel beads

(TentaGel HL-Br, Sigma Aldrich, St. Louis, MO) were utilized to immobilize the

eugenol to a solid support.

Figure 12: Overview of the method for immobilizing liquid target (eugenol) onto a

solid support (TentaGel beads) to allow a method for phage display screening of

liquid targets.

Considering that the eugenol target is a liquid, immobilization onto a solid support

facilitates a method for separating the bound phage via centrifugation. Immobilization of

eugenol consisted of incubating the TentaGel beads for 2 hours at room temperature at

equimolar concentration of NaOH. Several washing step in TBS were performed to

remove all trace amounts of un-bound eugenol.

32

Figure 13: Overview of the phage display screening process developed against a

liquid target immobilized onto a solid support. An initial screening against the solid

support alone is performed to remove phage that may bind to the support material.

The phage display approach, seen in Figure-13, utilizes an initial round of library

screening against uncoated TentaGel beads. The purpose of this initial screening round is

to remove phage from the M13 library which would bind to the TentaGel bead material

(polystyrene). As such, the beads were discarded, and the supernatant was retained as the

input for eugenol screening. Hence, after 30 minutes of binding to TentaGel beads, the

supernatant was removed and added to 5mg of eugenol coated TentaGel beads to

facilitate eugenol binding. After this, the screening was performed in the same fashion as

that of the TNT, DNT, and methyl parathion.

33

Figure 14: Phage display sequence results from the fourth round of phage display

screening against eugenol, an immobilized liquid target.

From fourth round screening results, two major sequences were found to be dominant.

These sequences were Gly-Ser-Arg-Met-Ser-Gln-Ser-Ser-Lys-Arg-Asn-Leu and Phe-Ser-

Leu-Pro-Ser-Lys-Ala-Leu-Pro-Trp-Gln-Leu as seen in Figure-14. Interestingly, this

latter sequence was also seen to dominate the fifth round screening results. By

examining the sequences in more detail, we found that From this, the we examined the

potential for the sequence Phe-Ser-Leu-Pro-Ser-Lys-Ala-Leu-Pro-Trp-Gln-Leu to be a

good binder for eugenol. We found that the initial screening used to remove TentaGel

binding phage, may not have been sufficient to remove non-specific binders. The theory

behind the screening of the liquid target while logical was not as effective in practice.

Particularly, the presence of the solid support offers too many sites for non-specific

binding to occur in comparison the available eugenol targets. As such, we found that

these results may not be effective representation of eugenol binding peptides.

Figure 15: Phage display sequence results from the fifth round of phage display

screening against eugenol.

34

2.5 Conclusion

Here in we have demonstrated the use of a diverse chemistry of amino acids present on

M13 bacteriophage to identify receptors for small molecule targets. Two distinct

strategies were utilized by performing phage display screening against the chemical

target. In one case, a molecular crystal form of the small molecule was used which works

well in the case of the target having low solubility in aqueous solution. The other

approach utilized prior immobilization of the target onto a polymeric bead. Utilizing the

combinatorial screening approach of phage display, we were able to mine information

from the available library for peptides which have preferential binding to the desired

targets. The first target screened was trinitrotoluene in the molecular crystal form. From

phage display results we identified a consensus motif comprising or aromatics and amino

acids capable of hydrogen bonding. In addition to this explosive molecule, we pursued

the screening of an analogue target dinitrotoluene from which we also found a consensus

binding sequences from phage display which was different from that of the TNT binding

motif. The last small molecule that was screened with a molecular crystal target strategy

was the organophosphate, methyl parathion. Since organophosphate

(pesticide/neurotoxin) detection holds interest to the public in terms of environmental

safety, we pursued the screening of methyl parathion to identify a potential receptor for

its detection. Our results show an aromatic rich domain of Trp-Trp which may

participate in non-covalent interaction with the phenyl group of methyl parathion.

Finally, we screened a liquid target, eugenol, by immobilizing it onto a solid support.

Screening for the eugenol sequence, while theoretically sound, did not yield effective

phage display results. We believe this is a result of the initial screening that was required

35

against the TentaGel bead solid support. To summarize, we have found several

consensus sequences from phage display for our targets of interest. We have found it is

highly necessary to have a molecular crystal target or a target with sufficiently identical

binding sites available throughout in order to have effective phage display results. In the

following chapters, we will discuss the steps used to identify the efficacy of these

sequences in binding to there respective targets with selectivity.

36

Chapter 3: Analysis Techniques for Identifying Selective Binding Motifs

3.1 Selective Binding

Achieving selective binding has been severely limited in sensor development by the use

of “off-the-shelf” polymers. While polymers such as polystyrene and PVC may offer

good structural characteristics, they are not well suited for discriminating between target

molecules due to the use of a repeating functional motif. Conversely, biopolymers such

as the specific binding pockets found in antibodies and GPCR (G-Protein Coupled

Receptors) elicit multivalent binding to offer a mode of achieving selective binding as

depicted in Figure-16.

Figure 16: Comparison of non-selective conventional polymer coatings to target

specific biopolymers.

37

3.1.1 Competitive Affinity Screening

In order to determine the strongest TNT binding receptors from the large subset of phage

display results, the phages bearing TNT binding peptides were collected. These 33

individual phage samples from TNT phage display screening results were picked and

separately amplified and diluted into a single mini-library of TNT binding phage having

106 pfu/µL of each phage. A single round of phage screening was performed against 5

mg of TNT in 0.2% TBST. Here, the TNT binding phages were simultaneously exposed

to the TNT target substrate in solution. After this competitive binding, the weak binding

phages were washed from the target, while the remaining strong binding phages were

captured. These remaining phage were titrated on LB Xgal/IPTG agar plates.79

Phage

titration was used to select phage plaques with receptor inserts.79

Twenty plaques, which

appeared blue, were picked and sequenced to reveal the strongest binding sequence.

Similarly, we identified the strongest DNT binding sequences from DNT target

screening.

38

Figure 17: The pIII receptors present on phage that were used for competitive

screening analysis. The number of appearances for a given receptor after

competitive screening (last column) were found from the DNA sequencing results.

The 33 sequences in Figure-17 represent the pIII receptors expressed on the M13

bacteriophage which were amplified and mixed to equal concentrations of 106 pfu/uL of

each phage for competitive screening. After a single round of phage screening with 0.2%

TBST, the remaining bound phage were eluted, captured, and titrated onto LB Xgal/IPTG

39

agar plates. From the blue plaques which appeared after overnight incubation at 37°C,

twenty of these were picked for sequence analysis. The last column of Figure-17

represents the number of appearances of a given receptor amino acid sequence from the

DNA sequencing results. The most abundant of these receptor sequences indicates the

highest level of binding. Importantly, 19 of the 20 phages sequenced possessed a Trp-

His-Trp motif at the N terminus.

Within the competitive screening experiments, 33 phage samples were screened against

TNT, and their corresponding pIII receptor sequences can be seen in Figure-17. The

remaining bound phages were captured and 20 of the phage were randomly picked for

sequence analysis. The last column of Figure-17 represents the number of appearances of

a given receptor amino acid sequence from the 20 random phages. The most abundant of

these receptor sequences indicates the highest level of TNT binding. Importantly, 95% of

these strongest TNT binding phage exhibited the same N terminal tetra-peptide motif:

Trp-His-Trp-X. Through this rigorous competitive screening, we assigned the most

abundant binding sequence as the strongest TNT binding peptide candidate (Trp-His-Trp-

Gln-Arg-Pro-Leu-Met-Pro-Val-Ser-Ile: TNT-BP). Similarly from the identified DNT

binding sequences, His-Pro-Asn-Phe-Ser-Lys-Tyr-Ile-Leu-His-Gln-Arg, was found to be

the strongest DNT binding sequences and was denoted DNT-BP.

40

3.1.2 Substrate Specificity Screening

To determine the most selective receptors from phage display screening results, TNT

binding phage and DNT binding phage were separately screened against both TNT and

DNT substrates. To evaluate the extent of receptor binding activity to these target

molecules, we measured the ratio of the amount of phage present after one round of

screening with stringent washing steps as compared to the amount of phage initially

introduced (Output/Input). Specifically, the phages were amplified to a concentration of

106 pfu/µL (Input), and each phage sample underwent one round of the screening process

with 0.2% TBST against 5 mg TNT and DNT separately. The amount of phage was

identified via UV spectrometer as well as titration. After titration, blue plaques were

counted to determine the concentration of bound phage (Output). This ratio of

Output/Input was calculated for each phage sample and then related to that of polystyrene

(PS-BP) specific phage which has no particular binding preference to either TNT or

DNT. PS-BP was, therefore, used as a negative ‘non-specific’ control. The receptor

with largest ratio difference between TNT and DNT substrate binding was designated

most specific for its target substrate.

41

Figure 18: a) Receptor sequences from phage primarily from TNT screening results

used in the following specificity screening, and b) specificity screening results of

phage against TNT and DNT substrate. Levels of binding represented as the ratio

of phage remaining bound after interaction and washing as compared to the initially

exposed number of phage.

42

The phages bearing receptors identified in Figure-18a were amplified to a concentration

of 106 pfu/uL. This number of phages was identified as the “Input” and was verified via

UV spectrometer as well as titration. 1mL of the phage samples were then individually

screened against 5mg of TNT, washed, and the remaining bound phage were eluted. This

elution, known as the “Output” number of phages, was quantified using phage titration.

The ratio of Output / Input was calculated and the values can be seen in Figure-18b.

Similarly, phage samples indicated * were also screened against 5mg of DNT and the

corresponding ratio of Output / Input can be seen in Figure-18b. The results reflect the

preferential binding of a given phage for the TNT substrate and hence the selectivity of

the receptor sequence.

43

Figure 19: a) Receptor sequences from phage primarily identified from DNT

screening used in the following specificity screening, and b) specificity screening

results of phage against TNT and DNT substrate. Levels of binding represented as

the ratio of phage remaining bound after interaction and washing as compared to

the initially exposed number of phage.

Similarly, the phages bearing receptors identified in Figure-19a were amplified to a

concentration of 106 pfu/uL. This number of phages was identified as the “Input” and was

verified via a UV spectrometer and also titration of phage. 1mL of the phage samples

were then individually screened against 5mg of DNT, washed, and the remaining bound

44

phage were eluted. This elution, known as the “Output” number of phages, was

quantified using phage titration. The ratio of Output / Input was calculated and the values

can be seen in Figure-19b. Similarly, phage samples indicated * were also screened

against 5mg of TNT and the corresponding ratio of Output / Input can be seen in Figure-

19b. The results reflect the preferential binding of DNT_ph7.5-Va-11 for the DNT

substrate and hence the selectivity of the receptor sequence His-Pro-Asn-Phe-Ser-Lys-

Tyr-Ile-Leu-His-Gln-Arg.

Figure 20: Phage display screening results of converged amino acid sequences from

the fourth round of phage display screening.

From the phage display results, we assessed the best binding phage by greatest target

selectivity. This target selectivity was determined based on the relative level of phage

binding to TNT and DNT target substrates. Among the subset of TNT binding

sequences, several exhibited varying affinity for DNT. We selected the phage with the

largest binding difference between TNT and DNT targets (those with strong binding to

TNT and low affinity for DNT), which was determined to have the TNT binding peptide,

TNT-BP. Similarly from DNT phage display results, we screened various DNT binding

phage against TNT and DNT and identified the most selective phage to contain the

45

sequence from DNT-BP (Figure-18). From our selectivity screening, the peptide TNT-

BP was found to have only non-specific interactions with DNT as demonstrated by

comparison to the negative control phage (Figure-21). Interestingly, DNT-BP binding to

TNT also remained on the order of non-specificity. This important result demonstrates

that M13 linked receptor sequences identified from phage display can selectively bind a

pre-determined target.

Figure 21: Selectivity screening of the DNT receptor and TNT receptor against

DNT substrates and TNT substrates with the level of binding quantified from phage

titration.

3.2 Synthesis of Standalone Receptors

All receptors were synthesized using standard Fmoc chemistry based solid-phase peptide

synthesis101

with amino acids and pre-loaded (cysteine or biotinylated-lysine) Wang

46

resins. OEG conjugated DNT receptors were synthesized by coupling three subunits of

Fmoc-amino-diethoxy-acetic acid to cysteine resin prior to addition of the DNT-BP

sequence. Cleavage reactions were performed for 2 hours with the a cocktail of 82.5%

trifluoroacetic acid, 5% thioanisole, 2.5% water, 5% phenol, 2.5% ethanedithiol, and

2.5% tri-isopropyl silane. Samples were purified by HPLC to >95% purity.

3.3 Mutational Analysis Binding Assay

Utilizing alanine substituted control peptides; we could identify the influence of

individual substitutions on the receptor’s binding capability and substrate specificity, and

thus identify the role of multivalent binding. By using a tetrapeptide biotinylated linker,

the receptors could be functionalized with Atto 425-Streptavidin probes for fluorescence

binding assays. In this assay, 10 µL of 100 µg/mL TNT or DNT in acetonitrile was

placed in 96 well TCPS plates. The TNT or DNT target was coated to the surface by

introduction of 300 µL TBS (50 mM Tris-HCl [pH 7.5], 150 mM NaCl) and set overnight

at room temperature. Solutions were removed and rinsed with TBS to remove non-

adsorbed TNT or DNT target. 1mM of peptides were introduced to the TNT or DNT

coated wells for 30 minutes. After binding, the substrate was washed with 0.1% TBST.

A bovine serum albumin (BSA) blocking buffer was then used for 30 minutes to prevent

non-specific adsorption of the fluorophore. An avidin labeled fluorophore, Atto 425-

Streptavidin, was then introduced while allowing 20 minutes for binding to the attached

biotinylated peptides. The substrate was washed with 0.1% TBST in order to remove any

non-specifically bound fluorophore. Finally, the bound receptor peptides, now

47

conjugated with the fluorophore, were eluted from the TNT substrate with vigorous

washing with 0.5% TBST. An Electromax Gemini EM plate reader was used to obtain

emission intensity at λ = 476 nm with excitation at λ = 436 nm in order to characterize

the amount of eluted peptide and the relative fluorescence signal was compared to the

BSA background.

48

Figure 22: Mutational analysis for identified TNT and DNT binding peptides. (a)

Sequence of receptors synthesized with C-terminal biotinylated lysine to allow

functionalization with the fluorescent probe Atto-425. TNT-BP and DNT-BP

represent the identified TNT and DNT binding receptor sequences, respectively,

while H-Sub (histidine substituted by alanine) and W-Sub (tryptophan substituted

by alanine) are mutations at amino acids 1 and 2 of TNT-BP. Scram-Ctrl is a

nonspecific sequence derived from scrambling the TNT-BP sequence to demonstrate

the sequence importance for encoding target selectivity and hence a negative control.

(b) Fluorescence binding assay against TNT substrate and DNT substrate, revealing

the importance of tryptophan and histidine residues in TNT-BP as well as

demonstrating the ability of the lone peptides TNT-BP and DNT-BP to bind

selectively to their targets in liquid when not associated with the other phage body

proteins. Fluorescence levels are normalized to the BSA fluorescence background

signal (P<0.0001, n=4). All data are presented as the mean ± standard deviation.

While target specific phage binding was a critical first step, the fluorescence binding

studies indicated that the receptors retained high substrate specificity despite no longer

being attached to the M13 phage (Figure-22a,b). The selectivity of the TNT receptor is

demonstrated by the significantly higher fluorescence levels of TNT-BP to the TNT

49

substrate as compared to the low levels of binding against the DNT substrate.

Substitutions in the N terminal region with alanine residues demonstrate the importance

of the conserved tryptophan and histidine residues in the binding event. This supports the

importance of multi-site interactions, as the tryptophan replacement resulted in a 58%

decrease in binding while the histidine replacement decreased binding by 48%. By

comparing the TNT binding sequence, scrambled TNT binding sequence, histidine

substitute, and tryptophan substitute for different substrates, we provide evidence of

substrate selectivity through multivalent binding. Direct comparison of the TNT binding

sequence for TNT and DNT substrates demonstrates the ability of the isolated TNT

receptor to bind selectively (over 3 fold increase) to the TNT substrate while remaining

relatively inert to DNT substrate (on the order of the non-specific scrambled sequence

and background (Figure-22b). Similarly, our isolated DNT receptor preferentially bound

the DNT substrate (over 2 fold increase compared to response against the TNT substrate

(Figure-22b)).

3.4 Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) was used to obtain binding isotherms of the

complex between TNT and the peptide TNT-BP, from which the dissociation constant

was determined. The ITC reservoir cell (kept at 25°C under constant mixing) contained a

10 µM solution of TNT-BP in acetonitrile to which a stock solution of TNT (100 µM in

acetonitrile) was added with an initial 5.0µL equilibration injection volume followed by

15µL injections every 5 minutes. The heat released per ITC injection of TNT was

50

measured, and the integrated heat plotted against the molar ratio of TNT added to TNT-

BP was obtained to give a complete binding isotherm for the interaction. To determine

the dissociation constant, the data was fit to a one-site binding model. The binding

isotherm obtained from the titration of TNT into a solution of TNT-BP is provided in

Figure-23. This isotherm, calculated from the integrated heat change per mole of TNT

injected and fit to a one-site binding model, provided the best-fit parameters values of the

binding constant and the enthalpy of K = 1.4 x 107 ±3 x 10

6 M

-1 and ∆H = -49 ±1

kcal/mol respectively. The inverse of the calculated K value gives us the dissociation

constant of 71 nM for TNT-BP interaction with TNT. These results support our ability

to use evolutionary screening to identify a receptor for a pre-determined target.

Figure 23: Measurement of the dissociation constant of the complex between TNT

and the peptide TNT-BP determined from isothermal titration calorimetry. Data

points (values for the integrated heat change during each injection, normalized per

mole of TNT) are represented by filled squares. A one-site model was used to fit the

data. The solid red line is the calculated curve using the best-fit parameters.

51

3.5 Conclusion

Using directed evolutionary screening processes, we identified specific TNT and DNT

binding peptides. Compared with the resulting TNT binding peptide, (Trp-His-Trp-X:

where X represents Gln, Ser, Asn, or Lys), the active site of nature’s known TNT binding

protein Enterobacter cloacae’s pentaerythritol tetranitrate reductase (Trp102, His181,

Tyr186, Thr26) contains many compositional similarities.102

PETN-reductase and other

TNT binding proteins display a highly conserved tryptophan residue involved in the

binding event.102, 103

Furthermore, these previous studies show that changes in the

tryptophan’s neighboring amino acid, histidine, can drastically modulate the TNT binding

ability of these proteins. Similarly, through mutational analysis of our TNT binding

motif (Figure-22b), we have demonstrated the role of multivalent binding involved with

neighboring tryptophan and histidine residues. Various mechanisms exist by which

tryptophan may attribute its strong role in the binding motif for TNT. The PETN-

reductase utilizes the aromatic stacking between tryptophan and the ring structures of

nitroaromatics.104

Through computational approaches, researchers have identified similar

dual aromatic residues as part of a high affinity TNT binding motif which parallels the

tryptophan arrangement of our own TNT binding sequence.17

Tryptophan’s interaction

with TNT may take on a donor-acceptor character due to the electron deficiency of the

ring in TNT while those of tryptophan are electron rich.105

Histidine can also contribute

to π-π interactions.106

In addition, imidazole side-chains can coordinate with the nitro

group in the TNT molecules through partial charge-charge interactions or hydrogen

bonding.102, 107

52

In summary, we have shown the successful evolutionary screening of highly selective

peptide receptors for explosive targets, such as TNT and DNT. We discovered a peptide

motif which coincides with the TNT binding site in PETN-reductase that has evolved in

nature. Using mutational analysis, we demonstrated that multivalent binding is the key to

selectivity of the TNT binding motif

53

Chapter 4: Selective Coatings for Chemical Sensing

4.1 Introduction to Chemical Sensing

Susceptibility of chemical sensors to false positive signals remains a common drawback

due to insufficient sensor coating selectivity. By mimicking biology, we have

demonstrated the use of sequence-specific biopolymers to generate highly selective

receptors for trinitrotoluene (TNT) and 2, 4-dinitrotoluene (DNT). Using mutational

analysis, we show that the identified binding peptides recognize the target substrate

through multivalent binding with key side-chain amino acids elements. Additionally, our

peptide-based receptors embedded in a hydrogel show selective binding to target

molecules in the gas phase. These experiments demonstrate the technique of receptor

screening in liquid to be translated to selective gas phase target binding, potentially

impacting the design of a new class of sensor coatings.

4.2 Overview of a Peptide Based Sensor Coatings

Utilizing the evolutionary screening approach discussed in detail in previous chapters, we

discovered molecular recognition motifs capable of selectively binding explosive

molecules TNT and DNT. Furthermore, to make these relevant for VOC detection, we

have translated liquid-phase screening into gas-phase selective binding through the

formation of receptor-laden hydrogels that attempts to emulate the olfactory system. As

demonstrated in the previous chapters, phage display can be used to obtain highly

54

selective receptors for small volatile molecules. In particular, by exploiting the

combinatorial screening power of this technique, it is shown that oligopeptides are

capable of selectively binding the explosive TNT while remaining inactive towards DNT

and vice versa.

4.3 Coating Design for Surface Stress Based Sensors

Chemo-mechanical transducers such as a cantilever beams and micro-membranes can

detect surface stresses created by ligand-receptor binding at very low concentration with

sufficiently high signal-to-noise ratio.8, 108

Such high sensitivity opens many applications

such as detection of explosives and chemical warfare agents. Figure-24 demonstrates the

operation principle of micromembrane surface stress sensors.

Figure 24: Operation mechanism of micromembrane surface stress sensor.

The molecular interaction between probe molecules and target molecules generate a

surface stress on the thin gold layer. This surface stress causes the structural deflection of

the membrane, which generates the capacitance change in electrical sensing. In order to

55

design a coating for such a surface stress based sensor, we implemented our DNT

receptor onto a gold sensor surface as a mock sensor layer.

4.3.1 Gas Phase Binding Assay Methods

A (100) silicon wafer was cleaned with heated Piranha solution. A 5 nm chrome layer

was thermally evaporated onto the wafer as an adhesion layer between the gold and

silicon. A 25 nm thick layer of gold was then thermally evaporated onto the wafer. The

wafer was then protected using 2 µm of G-line photoresist prior to dicing into 3mm by

3mm chips. The photoresist was then stripped using heated PRS-3000 solution, and

chips were cleaned and dried.

As a novel extension to standard liquid phase receptor identification and to make it

relevant for gas-phase chemical sensing, we embedded the selective DNT receptors in a

hygroscopic oligo (ethylene glycol), OEG, coating to test gas phase binding. Given

DNT’s higher vapor pressure compared to TNT, we found it more applicable to focus our

gas phase experiments solely on the identified DNT binding peptide.109, 110

Multiple

coating conditions were analyzed including: (i) DNT Receptor-OEG-Cys on gold chips

(ii) OEG-Cys on gold chips (iii) Blank gold surface (iv) DNT Receptor-OEG-Cys on

blank silicon surface (v) OEG-Cys on blank silicon surface (vi) Blank silicon surface.

Immobilization of coating layers was carried out by immersing the different chips in 1

mM solution of either DNT-OEG-Cys or OEG-Cys solutions for 24 hours utilizing the

available gold-thiol bond chemistry. The coatings were then exposed to target gas in

56

ambient air by placing the chips inside a scintillation tube containing crystalline DNT or

TNT which was heated uniformly to 600C for 2 hours using a custom designed aluminum

heat block with an NIST certified temperature controller (VWR Inc.) to generate DNT or

TNT gas. All experiments were performed with chips exposed to 18ppm of DNT gas.

The chips were immediately analyzed for the amount of bound DNT and TNT by

placement in the thermal desorption tube of a Unity Thermal Desorption System, which

heated the chips to 3000C and passed the desorbed particles directly to an Agilent GC-MS

system (Santa Clara, CA). Partition coefficients are identified as the ratio of

concentration of analyte bound to the coating compared to the concentration of analyte in

exposed gas headspace and normalized to the appropriate control condition (ie. blank Si

and OEG-Cys coatings).

4.3.2 Gas Phase Binding Assays Results

The results of Figure-25 represent the various control experiments performed to identify

the extent to which DNT would interact with the various components of the Au-DNT BP

coating. Silicon chips were exposed to DNT gas and used as the background signal for

DNT partition coefficient measurements for the various coatings of the Si chips. Six

chips conditions were utilized for DNT gas experiments: (i) DNT Receptor-OEG-Cys on

gold chips (ii) OEG-Cys on gold chips (iii) blank gold surface (iv) DNT Receptor-OEG-

Cys on blank silicon surface (v) OEG-Cys on blank silicon surface (vi) blank silicon

surface (control). Importantly, the amount of DNT bound to conditions (iv) and (v) were

relatively the same as that for the blank Au control (iii). This indicates the OEG-Cys or

57

DNT Receptor-OEG-Cys coating attachment is inhibited on Si substrate as compared to

there attachment to Au coated substrates under the same conditions. Furthermore,

Figure-25 identifies the highest DNT partition coefficient for condition (i) in which DNT

Receptor-OEG-Cys was used as the coating for the Au chip. By displaying this

comparatively large DNT partition coefficient using the DNT receptor, we demonstrate

the ability to translate from liquid phase screened receptors into gas phase target binding.

Figure 25: Gas-phase screening for partition coefficients of various coatings on Si

exposed to DNT gas. The values are normalized to the DNT gas partition coefficient

of blank Si substrates to observe the contribution attributed solely to the coating

layer. Partition coefficients are calculated as the ratio of the concentration of

analyte bound to the coating (identified through thermal desorption GCMS) to the

concentration of analyte in the exposed gas headspace.

The sequence identified as the best TNT binder was designated TNT-BP and possessed

the sequence Trp-His-Trp-Gln-Arg-Pro-Leu-Met-Pro-Val-Ser-Ile. Scram-Ctrl represents

58

the same amino acids as TNT-BP but in a different configuration. TNB-Ctrl represents

the positive control as it is known to bind TNT in liquid. These sequences were

synthesized with C terminal biotinylated lysine followed by a tri-Glycine linker to allow

functionalization with a fluorescent probe Atto-425 for the comparative analysis of the

loan peptide receptors (no longer attached to the phage body). Here, the sequences were

exposed to TNT coated polystyrene wells, fluorescently labeled, washed, captured, and

measured of their fluorescence relative to the BSA background signal. Figure-26

represents the level of binding exhibited by the given sequence for the TNT substrate.

The sequence TNT-BP exhibited much greater binding to the sequence Scram-Ctrl which

possessed the same amino acids in a different configuration. This result demonstrates the

importance of the configuration of the amino acids in the binding event, thereby

identifying that it is not solely the apparent charge or the functional groups present on the

receptor but instead their particular arrangement. TNT-BP exhibit higher level of TNT

binding as compared to the positive control, TNB-BP. (P < 0.0001, n = 4). All data

presented as mean ± standard deviation.

59

Figure 26: Analysis of the level of TNT substrate binding for the designated TNT

binding peptide (TNT-BP) as well as a scramble TNT-BP sequence as control and a

trinitrobenzene binding sequence (TNB-Ctrl).

The gas phase binding results for the DNT binding peptide (Figure-27b) show a 4 fold

increase in the partition coefficient for DNT over TNT as a result of the DNT receptor.

The preferred coating condition for selective binding of DNT gas was that of the

identified DNT-BP. Additionally, we found the DNT-BP partition coefficient for TNT

gas is on the same range as that of the OEG coated chip without a receptor indicating that

the selectivity of the DNT receptor remains when implemented in gas phase.

60

Figure 27: Selective gas-phase binding assay for DNT-specific coating: (a)

schematic diagram of the DNT binding peptide conjugated to oligo(ethylene glycol)

and their coating onto a gold surface for gas-phase selective binding; (b) partition

coefficient of DNT receptor coatings exposed to TNT gas and DNT gas. The values

are normalized to the target gas partition coefficient of OEG coating on a Au

substrate to isolate the contribution attributed to the DNT receptor element.

Partition coefficients are identified as the ratio of the concentration of analyte

bound to the coating to the concentration of analyte in the exposed gas headspace.

The results are obtained through thermal desorption GC-MS experiments on

exposed coating surfaces (P < 0.001, n = 4). All data are presented as the mean ±

standard deviation.

While successful biosensors have previously been developed for DNT detection in

aqueous solution, this demonstration of a selective coating for DNT in gas phase is of

particular importance as these short OEG embedded receptors are capable of retaining

efficacy outside of the liquid environment. The success of gas phase binding may be

attributed to the properties of OEG indicated by various research groups including: i) the

ability of OEG to retain the conformation of biomolecules111

and ii) the selectivity of

peptides remaining unaffected by OEG conjugation.101

Additionally, PEG is often used

for its non-fouling properties which may be beneficial in terms of minimizing false

positives in sensing applications.112

61

Unfortunately, the high hygroscopic nature of PEG was actually a drawback in terms of

implementation onto a real world sensor. This is because the PEG accumulates multi-

layers of water with increasing humidity inst of saturating at low humidity levels as

previous hoped. Looking to several potentials polymer for coating onto a sensing

platform, the humidity response was analyzed for the polymeric coatings using Quartz

Crystal Microbalance. Some consideration taken into account included a low humidity

response and the ability to immobilize the receptor.

Figure 28: Analysis of a hydrophilic and hydrophobic polymeric coatings using

Quartz Crystal Microbalance to identify the humidity response.

After analyzing both hygroscopic polymers (ie. poly (acrylic acid) and PEG) as well as

hydrophobic polymers (ie. PCGEF and PEGM), it was determined that the PEGM, poly

(ethylene-co-glycidyl methacrylate), had the lowest response to humidity. Additionally,

62

the epoxy group offered a point of receptor attachment via amino groups as is discussed

in the next section.

4.4 Coating Design for Quartz Crystal Microbalance Sensing Platform

For many sensing applications a high density of receptor is required to yield a measurable

signal when the target concentration is low. This is the case for TNT, which has a vapor

pressure of ~2x10-4

Torr at 25° C,113

and water solubility of 100 mg/L.114

Because of

this, we have examined suitable polymers to use as matrices to embed the receptors in,

with the goal of increasing the number of bound receptors available for interactions with

the target molecules. The polymeric matrices were selected to contain reactive groups

readily available for coupling with the functional groups present on the receptors. In this

paper we report on a particular co-polymer meeting such requirements: poly(ethylene-co-

glycidyl methacrylate), called 'PEGM'.

Figure 29: Chemical structure of the poly(ethylene-co-glycidyl methacrylate), called

'PEGM', which was found to have the lowest humidity response of the polymers

tested. Hence, it was chosen as the polymeric support for attachment of selective

receptors and coating onto the QCM.

63

This co-polymer, seen in Figure-29, contains an epoxy group in the glycidyl methacrylate

monomer, which reacts with amino groups present in the receptor structure to form stable

covalent linkages. Such bonds are not hydrolized in water, thus making this coating

particularly suited not only for gas sensing but also for detection in aqueous

environments. This is of relevance for DNT and TNT detection, because these explosives

are commonly stored in ammunition depots or weapon testing sites, and can seep into the

surrounding ground waters.115

As they are known to be harmful to health,116

their

detection in liquid is especially important to monitor and regulate the contamination in

ground water. In what follows, we show the successful attachment of an oligopeptide

TNT receptor (developed through phage display) to PEGM as verified using X-ray

photoelectron spectroscopy (XPS). The ability of the oligopeptide-PEGM matrix to retain

its functional activity as a receptive coating for TNT is demonstrated both in liquid phase

and in vapor phase using GC/MS. Using this strategy, the use of PEGM-receptor

conjugates as a sensor coating material to facilitate specific interactions with target

molecules is shown. Finally, we demonstrate the real-time selective detection of TNT in

the liquid phase using a QCM sensing platform.

4.4.1 Theory of QCM Operations

The quartz crystal is driven by an internal phase lock voltage controlled oscillator. For

measurements, the crystal current is monitored where the magnitude of the current is

proportional to the crystal conductance. From the voltage, a frequency and amplitude is

obtained. The frequency part of the signal is sent to a buffer, amplified, sent to a counter

64

and then to the acquisition software. Here the crystal current and voltage are monitored.

If there is no different in phase between the crystal current and voltage, then the system is

at the crystal resonant frequency. Addition of mass to the sensor will result in a change

in the measured frequency which is recorded as the signal. Using this, significant binding

events can be identified by a change in the mass and hence a decrease in the resonant

frequency.

4.4.2 Synthesis of PEGM / Receptor

TNT and DNT receptors found through phage display were created using solid-phase

peptide synthesis to provide pure forms of the receptor for analysis and for attachment to

the polymer matrix. Using standard Fmoc chemistry,101

pre-loaded cysteine-Wang resin

was used for 0.1mmol scale synthesis of the TNT and DNT binding peptides. Resins

were pre-swelled for 30 minutes in NMP prior to deprotection. Deprotection steps using

3mL of 3% DBU in NMP were carried out for 20 minutes on a rocking platform.

Washing steps involved rinses with 4mL NMP, 4mL methanol followed 4mL

dichloromethane, and with 4mL NMP. Coupling steps of 3mL 0.2M amino acid, Hobt,

and DIC were carried out on a rocking platform for 2 hours. Kaiser tests were performed

to identify presence of primary amines in order to monitor extent of reaction.117

Cleavage reactions were performed for 2 h with a cocktail of 82.5% trifluoroacetic acid,

5% thioanisole, 2.5% water, 5% phenol, 2.5% ethanedithiol, and 2.5% triisopropylsilane.

Samples were purified by HPLC to >95% purity.

65

To prepare the receptor coating, gold substrates were used to deposit the polymeric and

receptor coatings. Gold substrates were created by sputtering a 5 nm layer of Cr on a

(100) Si wafer, followed by 25 nm of Au. They were diced to the desired dimensions (5 x

5 mm2 for XPS analysis, 3 x 3 mm

2 for GC/MS analysis), sonicated in acetone for 15

min, and further cleaned using UV-Ozeonolysis (UVO-Cleaner, model 42, Jelight

Company, Inc. (Irvine, CA)) for 5 min. A droplet of PEGM solution was immediately

placed onto the Au substrate and allowed to dry, leaving a fairly uniform coating on the

substrate. A volume of 10 uL was used for XPS experiments and 5 uL for GC/MS

experiments. The TNT or DNT receptor attachment was carried out by exposing the

polymer coated chips to solutions containing 2.5 mg/ml of receptor, in 90% acetonitrile

(ACN, Fischer) and 10% ultra-pure 18 MOhm water. Volumes of 15 uL for XPS

experiments, and 5 uL for GC/MS were exposed to the polymer, followed by 15 and 5 uL

of tri-ethyl amine (TEA, 0.8 mg/ml in Acetonitrile) for XPS experiments and GC/MS

substrates, respectively. TEA was used as a catalyst to favor the reaction between the

polymer and the receptor sketched in Figure-30.

Figure 30: Schematic of attachment mechanism for amine on receptor with epoxy

grou of poly(ethylene-co-glycidyl methacrylate).

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4.4.3 Qualitative Analysis of Coating with XPS

Sample preparation used in XPS analysis of receptor attachment and activity

Samples used for XPS analysis were prepared by drying 30 uL of a 22 mM solution of

TNT onto gold chips coated with PEGM and receptive peptides. The samples were then

evacuated in the loading-lock chamber for thirty minutes, and then transferred to the

measurement chamber, with a base pressure of 10-9

Torr, at which point the spectra were

acquired to quantify the amount of TNT on the samples. To identify the extent of receptor

activity, samples were then washed overnight in water to remove non-specifically bound

TNT, followed by nitrogen drying. XPS measurements were carried out after this wash to

identify the extent of TNT that remained bound to the surface. All XPS measurements

were performed with an Omicron EA125 electron energy analyzer and an Omicron

DAR400 source with Al Kα X-rays at an energy of 1486.6 eV. The detector angle was 0°

to the surface normal. Spectral deconvolution was performed after background

subtraction with the Shirley method. The spectra were analyzed using Origin 6.0

software, and peaks were fit to Gaussians or Lorentzians to determine peak positions. For

energy calibration purposes, the Au 4f7/2 peak was used from the substrate as a reference

at 84 eV.118

If the Au from the substrate was too low in intensity to read, the

hydrocarbon contamination peak was used as a reference at 285 eV, as explained by

Clark and Thomas.119

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XPS analysis of TNT receptor attachment to PEGM

XPS spectra of TNT receptor deposited on a bare Au slide before and after rinsing in

water overnight are shown in Figure 31.

Figure 31: XPS spectra of C 1s (first row), N 1s (second row) and S 2p (third row)

peaks of TNT receptor deposited on a bare Au slide before (column A) and after

(column B) washing in water overnight. Experimental spectra are plotted in solid

line, fitted spectra in dashed line, and fits for each peak component in dash-dotted

line. The inset in the C peak, column B, represents the C 1s spectrum recorded on a

bare Au substrate.

68

The C 1s spectrum of the TNT receptor deposited on Au shows different components,

representing the many types of carbon environments found in an oligopeptide. A first

broad peak is centered at 284.5 eV, and is related to aliphatic C atoms. A second peak

located at 286.5 eV corresponds to carbon bonded to an amino group (C-NH2).120

A

second, intense and broad peak is centered at 288.1 eV, and may be assigned to carbon in

amide groups.121

This peak is typically indicative of the presence of a peptide on the

surface.122

The last peak located at 290.4 eV may be assigned to a ππ* shake-up band

due to the presence of aromatic groups within the peptide.123

The N 1s spectrum shows

two main peaks. The lowest peak in intensity is centered at ~400 eV and is related to non-

protonated amines and amides. The peak at higher energy is indicative of the presence of

a large amount of protonated N atoms,124, 125

thus indicating that most amines or imines

in the lateral chains of the amino acids composing the peptide are in fact charged. The S

2p spectrum shows a peak at ~168 eV, indicative of the presence of oxidized S in the

terminal cysteine present in the receptor.126

After washing in water overnight, most of the peptide is washed away from the Au

surface. The C 1s spectrum no longer displays peaks at ~288 and ~291 eV; rather it

becomes similar to that measured on a bare gold substrate (shown in the inset, where only

peaks relative to surface contamination are observed ). The peaks that most compellingly

indicate the removal of the peptide from the surface are the N and S peaks: the latter is

completely disappeared, and in the N spectrum, the most intense peak is now at ~400 eV

with only a shoulder observed at ~403 eV. This could be indicative of the presence of a

thin layer of peptide on the surface, as a similar effect was observed in the past for

69

histidine films on Au.127

This is confirmed by the drastic decrease in total N measured on

the sample soaked in water. The ratio of the total area underlying the N peaks to that

underlying the Au peaks was 23.5 before soaking in water and 0.07 afterwards, which

indicates that virtually all the peptide is washed away by overnight soaking in water, and

the Au surface is left mostly bare.

A very different result is obtained if the Au surface is covered with PEGM, and the

receptor is bound to it, as shown in Figure-32.

Figure 32: XPS spectra of C 1s (first row), N 1s (second row) and S 2p (third row)

peaks of PEGM deposited on Au (sample 'PEGM/Au') (column A), and TNT

receptor bound to PEGM on Au (sample 'TNTrec/PEGM/Au') before (column B),

70

and after (column C) washing in water overnight. Experimental spectra are plotted

in solid line, fitted spectra in dashed line, and fits for each peak component in dash-

dotted line.

The C 1s spectrum of just PEGM on Au displays two main peaks, related to the presence

of aliphatic carbon (peak at 285.2 eV) and carboxyl groups (peak at 289.4 eV), as

expected from the molecular structure of the polymer. No N and S were detected on the

polymer film. The spectra recorded on the sample containing the TNT receptor bound to

PEGM are shown in inset B. Two new peaks appear in the C 1s spectrum, located at

287.8 eV and 290.6 eV. These peaks are in similar positions to those related to amide and

carboxylic groups present in the TNT receptor. In particular, the peak at ~288 eV is

usually considered to be a very specific indication of the presence of peptides. Also the N

and S spectra resemble those analyzed for the receptor on Au. The spectra of the sample

TNTrec/PEGM/Au soaked in water overnight are shown in Figure-32. In the C 1s region,

the peak at ~288 eV is still present, which is an indication that the receptor is still present

on the substrate. An increase in the peak at 285 eV may be related to the adsorption of

impurities on the sample surface, as well as the appearance of some of the underlying

PEGM substrate, which has a carbon component at a similar position. The N 1s spectrum

splits in two peaks, which is indicative of a modification in the charge of some of the

amines and imines in the peptide (the lower energy component increasing in intensity is

related to the presence of a larger amount of neutral species). This split may also reflect

the removal of multilayers of peptide which had physisorbed onto the surface. The S 2p

peak remains visible on the sample, and maintains the same position it had before

soaking in water. All these observations indicate that most of the TNT receptor remains

bound to the surface of the PEGM/Au sample. This is a different observation from the

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sample of TNT receptor drop-casted directly onto gold. The ratio of the total area

underlying the N peaks to that underlying the Au peaks remains virtually unchanged after

soaking in water, going from 2.4 measured before soaking in water to 2.8 measured after

soaking, which is within sample-to-sample variability.

Qualitative analysis of PEGM-TNT receptor activity using XPS

The experiments discussed above show that the TNT receptor can be stably bound to

PEGM. It is now crucial to determine if the attachment of the peptide based receptor to

the polymer compromises its activity. Previous work showed that the amino acid

sequence triplet, tryptophan-histidine-tryptophan, present at the N terminus of the TNT

receptor is critical to the target specificity (Trp-His-Trp). The chemistry used to attach the

receptor to PEGM involves the reaction of primary amino groups from the peptide with

epoxy groups from the polymer. To analyze the receptor activity, a series of XPS and

GC/MS experiments were performed to assess and quantify the presence of TNT bound

to the receptor after overnight washing in water. This amount was then compared with

the results obtained for non-specific adsorption of TNT on PEGM and for adsorption on a

DNT-receptor with no specific affinity to TNT, also bound to PEGM.

72

Figure 33: XPS spectra of N 1s region for samples prepared by deposition of 660

nmol of TNT on a) PEGM/Au and b) PEGM with TNT receptor. Experimental

spectra are plotted in solid line, fitted spectra in dashed line, and fits for each peak

component in dash-dotted line.

XPS was used to determine whether the TNT receptor linked to PEGM was still active

towards TNT binding. The N spectrum of a droplet containing 660 nmol of TNT

deposited on PEGM/Au is shown in Figure-33. As PEGM does not contain nitrogen in its

structure, the appearance of a peak at 408.7 eV after TNT deposition is readily assigned

to the NO2 groups of TNT. This is in agreement with the position observed for nitric

groups in other inorganic and organic structures. The position of NO2 at such high

binding energies allows for an effective identification of the presence of TNT also when

other N-containing species are present on the sample. As an example, the spectrum of a

similar TNT droplet deposited on a sample of TNTrec/PEGM/Au is shown in Figure-32

above The position of this peak is distant from other peaks relative to the peptide, thus

implying that the amount of TNT can be determined without the need of laborious and

somewhat uncertain spectral deconvolution.

73

In order to test the activity of the TNT receptor bound to PEGM, the area of the N peak at

~409 eV right after the deposition of the TNT droplet is compared with the area of the

same peak after soaking the TNT-containing sample in water overnight. Washing in

water overnight removes only the physisorbed TNT, whereas the TNT bound to the

receptor remains on the sample. As previously mentioned, the effect of TNT removal by

washing overnight in water is analyzed for samples containing the TNT receptor bound to

PEGM (TNTrec/PEGM/Au), samples of just PEGM/Au and samples containing the

peptide that is a receptor for DNT instead of TNT (samples DNTrec/PEGM/Au). This

allows one to confirm if the specific binding of TNT to the TNT receptor is retained after

washing. In order to be able to compare the area of the N peak at ~409 eV before and

after washing, one needs to decide which components of the spectrum to be used for

normalization. The Au peaks arising from the substrate are a good choice for the sample

PEGM/Au. However, the intensity of these peaks is too low for the DNTrec/PEGM/Au

and TNTrec/PEGM/Au samples, due to the extreme surface sensitivity of XPS, and

cannot be used for the normalization of the NO2 peak. Hence, the normalization for these

samples is performed using the area underlying all the components of the N 1s spectrum,

which includes the peak relative to TNT and the peaks relative to the amines, imines and

amides from the peptide. As previously shown, the peptide bound to PEGM is stable to

soaking in water overnight, and hence the only difference in the components of the N

spectrum before and after overnight soaking in water is due to the removal of TNT. The

results obtained from the percentage ratio of the normalized area underlying the N 1s

peak relative to TNT before and after soaking in water overnight, multiplied by 100 in

order to obtain a percentage, are shown in the Figure-34 for all the samples analyzed.

74

Figure 34: Percentage of TNT remaining on samples containing TNT receptor,

DNT receptor, and just PEGM after overnight washing in water. The values were

calculated by dividing the normalized area underlying the peak at ∼∼∼∼409 eV relative

to TNT after washing the sample in water to the normalized area of the same peak

measured before washing the sample, and multiplying the result by 100, to obtain a

percentage. Details about the normalization of the peak relative to TNT and p

values calculated according to Student’s t test are reported in the text.

Almost no TNT is removed after overnight washing of the sample containing the TNT

receptor bound to PEGM. On the contrary, when a non-specific receptor, such as the

DNT receptor, is used, about 50% of the TNT is washed away by overnight soaking in

water. This is only slightly higher than the non-specific adsorption of TNT on the

polymer PEGM. These results are not quantitative due to the assumption that none of the

peptide was removed during overnight soaking, required for the normalization of the area

underlying the TNT peak for samples containing receptors. In fact, the possible removal

of some of the peptide during overnight washing may be the reason for the value of

greater than 100% for the TNT on the sample containing the TNT receptor. Also, the

measurements are performed in vacuum, which implies that some of the TNT might have

75

desorbed. Still, these results clearly show a high level of selective binding of TNT

molecules to the TNT receptor, compared to the binding to DNT receptor or non-specific

adsorption on the polymeric matrix.

4.4.4 Quantitative Analysis of PEGM Receptor Conjugate Coating using GC/MS

Quantitative Validation of PEGM-TNT receptor activity in solution using GC/MS

Samples used for GC/MS were prepared by drying 5 uL of a 1 mM ethanolic solution of

TNT on gold chips coated with PEGM and receptors. The samples were then placed

inside the desorption tube of a thermal desorber (Markes Intl. Inc.) and heated at 300°C

using a Unity Thermal Desorption System. The desorbed material was passed directly

into an Agilent Gas Chromatograph-Mass Spectrometer calibrated for TNT

quantification. Control experiments were performed to ensure that a consistent amount of

TNT was initially exposed to each substrate. Analogous GC/MS measurements were

carried out on samples exposed to TNT after soaking in water overnight. More than one

chip was loaded in the thermal desorber to provide a sufficiently readable signal for

samples washed overnight. This was necessary because the TNT bound to only one

sample of PEGM or DNT receptor functionalized surfaces was too low to be detected.

Thus, at least three chips of samples containing the DNT receptor and at least 15 chips of

samples coated with just PEGM were loaded in the thermal desorber, and the amount of

TNT measured was then divided by the number of samples used in order to get the

average amount of TNT left on each sample. A final set of experiments was carried out

76

with GC/MS, by drying 5 uL of a 1 mM ethanolic solution of DNT. GC/MS

measurements were carried out on these samples before and after overnight washing in

water. More than one chip was placed in the thermal desorber to obtain a detectable

signal, as explained above. The amount of TNT and DNT remaining on the samples

washed overnight was evaluated by comparing the GC/MS response obtained for such

samples with that obtained for the samples prepared containing 5 nmol of TNT or DNT,

prior to washing.

A quantitative analysis of the amount of TNT remaining on samples after washing in

water overnight can be performed using GC/MS. The same set of experiments described

in the XPS section above was conducted, using a lower amount of TNT because of the

very high sensitivity of GC/MS. In particular, a droplet of a solution containing 5 nmol of

TNT was exposed to each sample. The samples were then washed in water overnight, and

the amount of TNT left on each sample was evaluated with GC/MS

Figure 35: GC/MS measurements of a) the amount of TNT remaining on samples

containing TNT receptor, DNT receptor, and just PEGM after overnight washing

in water and b) the amount of TNT and DNT remaining on samples containing the

receptor specific for TNT, after overnight washing in water.

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The results shown in Figure-35 confirm those obtained with XPS, namely the amount of

TNT retained on samples containing the receptor specific to TNT was much higher than

that measured on samples containing a non-specific DNT receptor. The non-specific

adsorption of TNT on PEGM was very low. Quantitatively, the ratio of TNT remaining

on samples TNTrec/PEGM/Au to that left on samples DNTrec/PEGM/Au to that

measured on PEGM/Au samples was 1:0.33:0.06 for GC/MS, and 1:0.46:0.29 for XPS.

This shows that the trend measured with the two techniques was the same, although a

higher non-specific adsorption was measured with XPS. Also, it must be noted that the

absolute amounts of TNT remaining on the samples after overnight soaking measured by

XPS was much higher than that measured by GC/MS. Virtually the same amount of TNT

was measured by XPS before and after soaking in water overnight, on the sample

containing the receptor specific for TNT. Instead, less than 1% of it was found with

GC/MS, for the same type of samples. This observation is attributed to the following

factors. XPS was performed in ultra-high vacuum, thus only the amount of TNT that

resisted evacuation was detected; as such, most of the physisorbed TNT molecules were

most likely removed before the spectra were collected. Hence, soaking in water overnight

removed a further portion of TNT only on the samples that did not contain the receptor

specific for TNT, whereas almost no changes were observed in the amount of TNT

measured on samples containing the receptor specific for TNT. Instead, no evacuation

was performed before GC/MS measurements, which implies that the physisorbed TNT

was removed only during the overnight soaking. Hence, the absolute amount of TNT

resisting the overnight soaking was much lower than that initially evaporated on the

samples. This explains why the percentages of TNT left on the samples after overnight

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washing measured by GC/MS are much lower than those measured by XPS. Moreover,

only a thin, superficial layer of the solid TNT dried on the samples was in direct contact

with the receptors bound to the PEGM/Au surface. This would lead to only a small

amount of TNT remaining on the samples after overnight washing, as measured by

GC/MS, since only a small fraction of the initial TNT could interact with the receptors,

while most of the TNT was dissolved in solution. Lastly, the reason for the proportionally

higher non-specific adsorption on PEGM measured by XPS compared to GC/MS is that a

much higher absolute amount of TNT was dried on the samples used for XPS compared

to those used for GC/MS (660 nmol vs. 5 nmol), due to the very different surface

sensitivity of the two techniques, which may imply that the overnight washing may not

have been sufficient to completely remove all the physisorbed TNT on the samples used

for XPS.

These sets of experiments demonstrate the selectivity of TNT binding on the receptor

specific for TNT compared to the binding to a non-specific DNT receptor or the lone

PEGM polymeric matrix. Another set of experiments was performed with GC/MS in

order to analyze the selectivity for TNT when the receptors were embedded in the PEGM

matrix. To identify this selectivity, the same concentration of DNT solution was exposed

to samples containing TNT receptors bound to PEGM, followed by washing in water

overnight. GC/MS spectra were collected before and after the wash to measure the DNT

signal and compare it to that obtained with TNT in the experiments described above.

After soaking in water overnight, virtually no DNT could be detected on the samples, as

shown in Figure-35, where this result is compared to that obtained when samples with

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TNT receptors were exposed to TNT. This analysis shows that only TNT was strictly

bound to the TNT receptors and resisted overnight soaking, whereas DNT was not, and

the amount of DNT remaining on the samples was below the detection limit of GC/MS.

4.4.5 Integration with a Quartz Crystal Microbalance Sensing Platform

These experiments were performed using a Research Quartz Crystal Microbalance

(Maxtek, Inc. (Cypress, CA)). The quartz crystal was placed in a teflon crystal holder

which also acted as a reaction chamber. The crystal holder equipped for liquid flow was

connected by teflon tubings to two syringe pumps, containing DI water and a solution of

either DNT or TNT, respectively. A schematic of the system used for this set of

experiments is shown in Figure-36.

Figure 36: Schematics showing the two modes of operation of the QCM setup.

A 1” diameter, gold-coated quartz crystal was coated with 5 uL of PEGM solution

prepared as described above. TNT receptor was then bound to PEGM following the same

procedure. As shown in the figure above, the flow of solutions coming out of the syringes

is controlled using a set of three-way valves, adjusted in such a way that only one

solution flows through the sensor chamber (quartz crystal holder) at any given time.

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Therefore, the setup can be used in either “solution mode” or “purge mode”, thus

allowing the chamber to be flushed with a solution containing the molecule of interest

(TNT or DNT), or DI water, respectively. Prior to every experiment, the frequency of

quartz crystal was measured and a stable baseline was obtained in the “purge mode”.

Then, the system was switched to “solution mode”, and the crystal coated with TNT

receptor/PEGM was exposed to either TNT or DNT solutions. The change in resonance

frequency of the quartz crystal was measured in real time. The system was maintained in

this mode till the equilibrium was reached. Finally, the system was switched back to

“purge mode”, and the crystal was rinsed with DI water, until a stable baseline was

obtained again.

Here we show the application of the receptor/polymeric coating on a well-known realistic

sensing platform, using QCM in liquid phase. In typical QCM experiments, the resonance

frequency of a quartz crystal is measured, which decreases if the mass adsorbed on the

crystal increases.128

PEGM was deposited on the gold-coated QCM crystal, and TNT

receptor was bound to PEGM as described previously. After reaching a stable baseline by

flowing DI water, the crystal was exposed to either TNT or DNT solution.

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Figure 37: Change in QCM resonance frequency measured on a crystal coated with

PEGM/TNT receptor, after exposure of a solution containing TNT a) and DNT b),

respectively.

As seen in Figure-37, the resonance frequency measured with QCM decreased noticeably

when the crystal was exposed to TNT solution. Equilibrium was achieved in less than 30

minutes. After switching back to flowing DI water, the resonance frequency returned to

its previous value before the exposure. The decrease in frequency of ~6 Hz observed after

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exposure to TNT solution is related to an increase in mass adsorbed on the crystal, due to

the interaction between TNT and TNT receptor. The same coating exposed to a solution

of DNT shows no appreciable changes in the resonance frequency of the crystal, thus

indicating that DNT molecules did not bind appreciably to the TNT receptor. These

results illustrate that the PEGM/TNT receptor coating maintained its high selectivity for

TNT towards DNT also in liquid phase, and that it can be used on a real-time sensing

platform.

4.5 Conclusion

Using the phage display identified receptors for gas phase chemical sensing, we created a

biomimetic coating for highly selective detection of DNT in ambient conditions. We

believe that this approach of evolutionary peptide screening followed by the creation of

biomimetic coatings, when generalized for other target molecules, reflects a significant

advance to enable highly selective and sensitive miniaturized chemical sensors.

In summary, a strategy for the preparation of a selective coating for TNT sensing is

demonstrated. An oligopeptide was identified as a specific receptor for TNT using phage

display, and was stably bound to a co-polymer, PEGM. The attachment was easily

performed by reacting the epoxy groups present in one of the monomers of PEGM to

primary amino groups present in the receptor. The attachment was stable to overnight

washing with water, as shown by XPS. The oligopeptide bound to PEGM maintained its

activity as a receptor for TNT, as shown by experiments performed by exposure to

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solutions of TNT on samples containing TNT receptors bound to PEGM, and washing

such samples in water overnight to remove the unbound TNT. Both XPS and GC/MS

showed that the amount of TNT left on samples containing the specific TNT receptor was

much higher than that remaining on samples containing a non-specific receptor or the

lone PEGM matrix. In particular, the quantitative GC/MS results proved that the specific

adsorption of TNT in solution on TNT receptor was approximately 3 times larger than

that of a non-specific receptor and about 10 times larger than the physisorbed amount on

PEGM. GC/MS experiments also showed the selectivity of TNT over DNT binding in

solution for the TNT receptors was retained when the receptors were conjugated to the

PEGM matrix. A real-time highly selective explosive detection in the liquid phase was

also demonstrated, using QCM as a sensing platform, and coating the QCM crystal with

PEGM/TNT receptor. A decrease in resonance frequency of the QCM was observed only

in the presence of TNT solution, whereas no change in resonance frequency was noted

when the crystal was exposed to DNT solution. The potential of using this sensitive and

selective liquid detection of TNT could be particularly appealing for analysis of

contamination of ground waters near ammunition depots, for example.

In conclusion, these results show that it is possible to make a very selective sensing

coating by embedding specific receptors in a polymer, and that this can be used in a

standard sensor platform such as QCM. Ease of incorporation of these receptors in a

GC/MS sensor highlights versatility of the coating technique. This is of great importance,

because with a similar strategy large concentrations of receptors can be bound to the

sensor surface, if a porous and high surface area polymeric matrix is used. Additionally,

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its possible to control the surface properties of the sensor by changing the polymeric

matrix used. For example, the hydrophobicity of the polymer used in the present work

makes this coating an optimal candidate for most real-life gas sensing applications, where

it is highly desirable to avoid interactions of the sensor with the humidity present in the

air.

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Chapter 5: Development and Optimization of a Polymeric Sensing Vesicle

5.1 Introduction

In this chapter, we discuss the development of a polymeric sensing vesicle. Due

to their unique optical and stimuli-response properties, many sensor groups are utilizing

polydiacetylene vesicles as an alternative to complex mechanical and electrical sensing

systems. Utilizing a modular synthesis strategy to couple peptide based recognition

elements to chromic responsive polydiacetylene (PDA), we fabricated vesicles and

explored the essential design parameters necessary for an effective sensor from the

aspects of synthesis, composition, and assembly. Investigating the potential for these

systems, we explored the detection of small molecules with the specific example of the

explosive molecule trinitrotoluene (TNT). Furthermore, we investigated large targets by

incorporating cell binding domains for fibroblast detection. By observing shifts in the

absorption spectra of these sensor vesicle systems, we were able to identify the important

role of side-chain composition and surface density on transduction of chromic transition

from surface interactions. Additionally, we identified a tradeoff in surface density

considerations between proper monomer alignment and sufficiently high receptor density

to elicit a visually detectable chromic response. Finally, we identified a dependence of

polydiacetylene alkane chain length on the sensitivity of the system to chromic response

by the small molecule target, TNT. Overall, these systems offer the advantages of easy

and low cost manufacturing, simple analysis, and modular incorporation of target

recognition elements. These benefits make the PDA sensor a viable candidate for widely

86

deployable chemical sensing given the proper design parameters examined here are taken

into consideration.

5.2 Overview of Polydiacetylene as a Sensing Platform

Our environment contains a vast assortment of chemical and biological information,

some of which we can perceive through our senses. For instance, our olfaction and

gustation systems provide us with a means of molecular identification through smells and

tastes. Unfortunately, many surrounding harmful biological and chemical species, which

may threaten our health, remain undetectable. As such, we rely on the ability of sensor

technologies to identify the hidden information of our environment. As an alternative to

complex electromechanical sensing platforms, researchers have explored the use of

molecular target interactions and subsequent transduction into a detectable color change

as a means of gaining environmental information. One such colorimetric based sensor

framework utilizes the ability of inorganic nanoparticles to possess different absorption

spectra depending on their inter-particle spacing (or aggregation). Several research

groups have indeed demonstrated this with noble metal nanoparticles129-135

and other

inorganic nanostructures including quantum dots.136-138

When incorporated with

molecular recognition elements, these nanoparticles are effective sensing systems capable

of a visible color change. Other colorimetric based sensing approaches have minimized

the need for signal transduction hardware by using receptors designed for specific

molecular recognition which may elicit large spectral shifts upon ligand binding. Such

systems make use of engineering the curvature and functionality of the receptor to

87

provide the shape, size, and binding complementary for a given target molecule. These

include cavitands, crown-ether, and metalloporphyrin dyes which can provide a visually

detectable color change depending on the particular target-receptor pair.16, 18, 52

Researchers have also utilized chromic responsive polymers functionalized with

recognition sites for sensing purposes.139-145

In this work, we examine the creation of

these chemical sensors which utilize peptide based recognition elements functionalized to

such chromic responsive vesicles comprising conjugated polymer systems.

Several groups have exploited π-conjugated polymers, particularly polydiacetylenes

(PDAs), for chemical sensing applications due to the ability of their absorption spectra to

change in response to target binding.142-144, 146-150

PDA is an amphiphilic polymer

comprised of a carboxylic acid head-group and alkyl tail which facilitates its formation

into supramolecular assemblies such as vesicles.151, 152

When these assemblies are

exposed to UV irradiation, a conjugated PDA (ene-yne) carbon backbone is formed

which exhibits strong absorbance peaks at 640 nm or 540 nm resulting in a blue or red

color, respectively.153

The existence of a blue or red state is highly dependent on extent

of planarity or π orbital overlap of the conjugated PDA backbone.153-155

PDA has been

used extensively due to this susceptibility of the absorption spectrum to be altered by the

shortening of the effective conjugation length resulting from external stimuli.156-160

External stimuli, including interfacial perturbations or binding, can induce strain and

distortions within side-chains of PDA resulting in conformational transitions in the

backbone.161

This transition breaks the conjugated backbone network planarity resulting

in increased absorption at lower wavelengths and hence a red chromatic transition.162, 163

88

Molecular interactions resulting in disturbance of interfacial hydrogen bonds have been

proven to create a stress on the polymer backbone sufficient to effect the polymers

conjugations length.164-167

This change in the effective conjugation length of the π

conjugated backbone can be observed directly through the PDA absorption spectra

thereby making it ideal for sensing purposes.160, 168

Only a few degrees of (ene-yne) C-C

bond rotation can cause the irreversible chromic shift to the red state.153

The side-chain

arrangement is therefore critical to the chromic response of the system as we investigate

below. In this work, we study the design parameters which affect the functionality of

these conjugated polymer systems in colorimetric sensing applications for detection of

targets, such as the explosive TNT.

Figure 38: Schematic diagram of synthesis, composition, and assembly parameters

which must be optimized to achieve an effective colorimetric PDA vesicle based

sensor.

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Using a modular synthesis strategy, we created sensors comprising TNT recognition

elements, identified previously through phage display,169

coupled to chromic responsive

PDA elements. With this system, we investigated the role of side-chain composition and

the role of surface density on the transduction of surface interactions to the conjugated

PDA backbone. Additionally, we identified the effect of these parameters on the self-

assembly by observing their absorption spectra. By investigating these assembly

parameters, we have demonstrated the importance of polymerization timescales in

achieving maximal effective conjugation. The irreversible nature of the chromatic

transition, from a meta-stable blue phase into a more thermodynamically stable red phase,

was also explored through polymerization and heating experiments.163

Finally, we

investigated the potential of these systems for small molecule target (e.g., TNT) as well

as whole cell target (e.g., fibroblast) detection. We believe these parameters are critically

useful to researchers considering fabrication of an effective PDA based sensing system.

5.3 Experimental Section

5.3.1 PDA-Peptide Conjugate Synthesis

To produce PDA-peptide conjugates, standard solid-phase peptide synthesis was carried

out using Fmoc chemistry.101

Fmoc protected amino acids and rink amide resins were

obtained from EMD Biosciences (San Diego, CA), while 10, 12-pentacosadiynoic acid

(PCDA) was obtained from Sigma Aldrich (St. Louis, MO). Resins were pre-swelled for

30 minutes in NMP prior to deprotection. Deprotection steps using 3 mL of 3% DBU in

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NMP were carried out for 20 minutes on a rocking platform. The washing steps

proceeded as follows: 3 washes with 4 mL NMP, 6 washes with the series of 4mL

Methanol followed by 4 mL Dichloromethane, and 3 washes with 4 mL NMP. Coupling

steps of 3 mL and 0.2 M amino acid, Hobt, and DIC were carried out on a rocking

platform for 2 hours. A final coupling step with 3 mL of 0.2 M 10, 12 pentacosadiynoic

acid (PCDA), Hobt, and DIC was performed with the same incubation period of 2 hours

to create the PCDA-peptide conjugate. Kaiser tests were performed at each step to

identify the presence of primary amines in order to monitor the extent of reaction.117

Resins were washed with methylene chloride, dried, and underwent cleavage. Cleavage

reactions were performed for 2 hours while shaking with a cocktail of 82.5%

trifluoroacetic acid, 5% water, 5% phenol, 5% ethanedithiol, and 2.5% triisopropylsilane.

Rotary evaporation followed by precipitation in diethyl ether provided the removal of

cleavage solvents and protecting groups. Samples were then suspended and mixed in

water followed by centrifugation for 10 minutes at 10,000 rpm to pellet the product at

which point the supernatant was discarded to remove any trace contaminants. The

suspension and centrifugation steps were repeated until all cleavage contaminants were

removed. Lyophilization was then performed and samples were stored at 4°C. The

PDA-peptide conjugates which were synthesized are as follows: PCDA-Trp (promoter),

PCDA-Trp-His-Trp (TNT binding motif), and PCDA-Gly-Arg-Gly-Asp-Ser (cell binding

motif). There structures can be found in Figure-38.

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5.3.2 Controlling Surface Composition and Density in Supramolecular Assemblies

PCDA and PCDA-peptide conjugates were suspended to 10 mM in water. Solutions

were sonicated for 20 minutes and heated at 85°C for 20 minutes to melt any existing

super-molecular structure. Additional sonication for 20 minutes was performed prior to

mixing of PCDA with PCDA-peptide conjugates. Volumetric mixing was utilized to

provide the exact molar amount of PCDA and peptide conjugate. For example, 4%

PCDA-Trp-His-Trp and 96% PCDA utilized a 4:96 volumetric ratio of PCDA-Trp-His-

Trp to PCDA. After mixing, the sample was heated for another 5 minutes at 85°C and

sonicated to ensure ample distribution of PCDA-peptide conjugates and PCDA. To allow

self-assembly into vesicle structures, the solution was allowed to cool to room

temperature then incubated at 4°C for 24 hours. The solution is then brought to room

temperature and the self-assembled vesicles are polymerized using a 4 W UV lamp at 254

nm wavelength. Polymerization is carried out for 25 minutes of exposure. After filtering

through a 0.8 µm cellulose acetate filter, vesicle size was measured using a dynamic light

scattering (DLS) particle sizer (Malvern Instruments, Southborough, MA).

5.3.3 UV Exposure, Extent of Polymerization, and Irreversibility Measurements

Extent of PCDA polymerization was characterized from the visible absorption spectra

(400 nm-800 nm wavelength scan with Beckman Coulter UV-Visible

Spectrophotometer). Particularly, the blue percentage, [Abs640 / (Abs640 + Abs540)] *

100%, and the chromic response, [(initial blue percentage – exposed blue percentage) /

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initial blue percentage] * 100%, were used to characterize the parameter of

polymerization of the conjugated π backbone. To identify the irreversibility of the

system as well as the timescale at which UV polymerization is complete, a 10 mM

solution of PCDA, prepared as described above, was initially polymerized by exposure to

5 minutes of UV light (4W lamp at 254 nm). The resulting spectrum was obtained and

the blue percentage determined. The solution was then exposed to 70°C for 5 minutes to

thermally induce a chromatic transition to the red phase at which point the blue

percentage color was again obtained through spectral analysis. This process was repeated

until the blue percentage remained constant indicating complete polymerization and

irreversibility of the system.

To confirm the polymerization time necessary to achieve the greatest potential chromic

response, freshly prepared PCDA samples were exposed to UV light for periods of 5 s,

10 s, 30 s, 1 min, 2.5 min, 5 min, 7.5 min, 10 min, 15 min, 20 min, or 25 min. The blue

percentage was calculated from obtained spectra, and the solutions were then exposed to

thermal stimulus of 70°C overnight to induce complete chromatic transition. From the

resulting spectra, the exposed blue percentage was obtained to calculate chromic response.

The necessary polymerization conditions for maximal chromic response could then be

determined.

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5.3.4 Examination of Surface Density

PCDA vesicle mixtures containing 0, 4, 8, 14, 25, 30, 50, and 100% PCDA-Trp-His-Trp

surface density were prepared as described above. Importantly, all samples were

prepared from the same initial stock solutions in order to minimize variation in spectral

response. The samples were UV polymerized for 25 minutes and the resulting blue

percentage was measured to identify the effect of surface density on assembly into planar

conjugated system and hence the propensity for steric induced red phase transitions.

5.3.5 TNT Target Exposure

Vesicle mixtures containing compositions of PCDA-Trp-His-Trp:PCDA-Trp:PCDA of

4:0:96, 2:2:96, and 4:4:92 were prepared and polymerized by 25 minutes of UV exposure.

Individual samples were separated into No TNT Exposure and TNT Exposure aliquots of

200 µL. TNT Exposure aliquots were given 4 µL of 572 µM TNT in water for a final

concentration of 11 µM TNT. No TNT Exposure aliquots were given 4 µL of water.

Samples were allowed to incubate at room temperature for 1 hour prior to visible

spectrum analysis. The resulting chromic response to TNT exposure was calculated from

the blue percentage of TNT Exposure aliquots in relation to No TNT Exposure aliquots.

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5.3.6 Changing the Alkane Chain Length

In addition to the PCDA-Trp-His-Trp, several other TNT binding motif bearing PDA

constructs with varying alkane chain lengths were produced. This was carried out by

using the same synthesis protocol as listed above but replacing the PCDA component

with one of the following purchased from GFS Chemicals, Inc. (Powell, OH): 10, 12

tricosadiynoic acid (TCDA) and 10, 12 heptacosadiynoic acid (HCDA). The resulting

structures can be seen in Figure-38. To identify the effect of chain length TCDA-peptide

and HCDA-peptide and PCDA-peptide vesicles were created using the same protocol as

listed above but with compositions containing a 10% surface density of peptide. That is

to say, vesicle mixtures were prepared with 10% molar ratio of PDA-Trp-His-Trp in PDA.

Samples were prepared in 200 uL aliquots within a 96 well clear bottom plate for analysis

of the absorbance spectra using a Safire2 plate reader (TECAN, Männedorf, Switzerland).

The plate was shaken for 2 seconds prior to sample measurement, and each sample was

subjected to 10 readings at which point the absorbance was averaged. Samples were then

subjected to TNT at concentrations of 5.2, 9.5, 20.3, 33.6 µM. Again the absorbance

spectra were obtained after TNT exposure using the Safire2 plate reader. The resulting

chromic response to TNT exposure was calculated from the blue percentage of TNT

Exposure aliquots in relation to No TNT Exposure aliquots as described above.

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5.3.7 Fibroblast Culture

IMR-90 human lung fibroblasts (obtained from UC Berkeley Cell Culture Facility) were

grown in Dulbecco's Minimum Essential Media (ATCC, Manassas, VA) containing fetal

bovine serum (10%) and penicillin/streptomycin (1%). Cells were incubated at 37°C in

the presence of 5% CO2 in a humidified incubator. Media was changed every 48 hours,

and cells were split as they approached 80% confluence. Before the experiment, cells

were placed in 1 mL of PBS and a cell scraper was used for detachment from the tissue

culture polystyrene (TCPS) plates. The suspended cells were place in a microcentrifuge

tube, briefly pelleted, and re-suspended at a concentration of 106 cells per 100 µL of

water.

5.3.8 Fibroblast Target Response

Vesicle containing 4% PCDA-Gly-Arg-Gly-Asp-Ser were polymerized by 25 minutes of

UV exposure. Individual samples were separated into “No Cell Exposure” and “Cell

Exposure” aliquots of 200 µL. “Cell Exposure” aliquots were given 2 µL cell stock (104

fibroblast/µL) to give a final concentration of 100 cells/µL of human fibroblasts in water.

“No Cell Exposure” aliquots were given 2 µL of water. Samples were allowed to

incubate at room temperature for 10min prior to visible spectrum analysis. The resulting

chromic response to fibroblast cell exposure was calculated from the blue percentage of

“Cell Exposure” aliquots in relation to “No Cell Exposure” aliquots.

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5.4 Results and Discussion

5.4.1 Vesicle Characterization

Confirming the formation of PCDA-Trp-His-Trp vesicles, we characterized the formation

of PCDA based sensors using dynamic light scatter. Analysis of PCDA-Trp-His-Trp

particle hydrodynamic diameter was identified to be 162 nm on average from dynamic

light scattering measurements. The size distribution of vesicles was identified to be

mono-modal indicating that a single size of vesicle is preferred (Figure-39). These values

of vesicle diameter coincide well with previously reported PCDA vesicles diameters.170

Figure 39: Dynamic light scattering measurements analysis was used to

characterize the diameter of the range of assembled PCDA-Trp-His-Trp particles to

be on average 162 nm.

5.4.2 Maximal Chromic Response Dependence on the Extent of Polymerization

To identify the polymerization time necessary to achieve an optimal initial blue

percentage for sensing purposes, we investigated the relation between chromic response

and UV polymerization of PDA vesicles. Achieving complete polymerization of

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assembled PDA vesicles is vital in the fabrication of consistent and effective PDA based

sensors. It is this parameter which controls the maximal chromic response that can be

achieved for a given vesicle composition. Additionally, we show that insufficient UV

polymerization can give a false impression of a chromic reversible system. Researchers

have extensively explored the irreversibility of polydiacetylene polymers and the energy

barriers associated with these thermal induced bond rotations have shown strong

dependence on the bulkiness and interactions between side-chain groups.171-173

Modification of these polydiacetylene side groups has shown it possible to create chromic

reversible supramolecular assemblies and to control the polymers thermal response

properties.172, 174, 175

Figure 40: Effect of PDA polymerization times were analyzed by a) varying

exposure of PDA vesicles to identify the conditions for achieving maximal chromic

response (trend line added as guide), and b) identifying the length of UV exposure

required for full PDA vesicle polymerization as indicated by irreversibility of the

system.

We demonstrate the irreversibility of our system as well as identification of the UV

exposure necessary for full PDA vesicle polymerization. By monitoring the visible

absorption spectra at various time intervals after heating and UV exposure, we were able

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to qualitatively observe changes in the effective conjugation length. The blue percentage

was used to characterize the extent of π conjugated backbone planarity, where a smaller

blue percentage indicates that a larger red phase had been triggered (decreased

conjugation). The results seen in Figure-40 demonstrate the pseudo-reversibility of the

system after heat exposure if the system is insufficiently polymerized. We see that

additional UV exposure will create π conjugated PDA backbones from any previously

un-polymerized PDA. The result is a mixture of absorption spectra between previously

thermally triggered and newly polymerized PDA. The irreversible nature of the

chromatic transition allows a meta-stable blue phase to enter a more thermodynamically

stable red phase upon heating.163

After several heat and UV cycles as seen in Figure-40b,

no change in the π conjugated backbone can be identified, as the blue percentage remains

constant after 20 minutes of total UV exposure. UV polymerization for longer periods of

time does not indicate any return to the blue phase. This demonstrates that all available

polymerization sites have been reacted. We qualify the polymerization as having reached

completion after this 20 minute exposure, since after this time scale the system exhibits

its true irreversible nature in terms of chromic response.

To confirm the conditions of complete polymerization and to identify the conditions for

maximal chromic response, we analyzed the thermally triggered chromic response of

PDA samples after various levels of UV exposure. From Figure-40a, we observe that the

maximal chromic response of 60.2 ± 1.5% is achieved after 20min (~150 J/cm2) of 254

nm UV exposure. From this data, we have identified the minimum polymerization

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conditions necessary to elicit an optimal chromic response for the given vesicle

composition.

5.4.3 Effects of side-chain composition

In order to have an effective sensor, it is necessary to incorporate recognition

motifs capable of transducing a detectable signal. We demonstrate the ability to

incorporate recognition motifs onto a PDA vesicle while identifying the important

consideration of receptor length. The ability to tune side-chain composition is essential

for controlling the surface interactions experienced by the sensor vesicle as well as the

extent of monomer alignment in self-assembled vesicles.176

We functionalized the side-

chains with different peptide moieties referred to as receptor and promoter elements.

Receptor side-chains, such as PCDA-Trp-His-Trp, are generally bulky components used

to interact with particular target molecules of interest in the surrounding environment,

which is TNT in this case. Transduction of receptor-target binding to a break in

backbone planarity is dependent on side-chain rearrangement.177, 178

Because receptor

elements can be large relative to small molecule targets, it has proven advantageous to

incorporate promoter elements, such as PCDA-Trp, to assist in cascading a side-chain

conformation change from the bound receptor-target complexes.179

This parameter, as

demonstrated in subsequent sections, improves target recognition; therefore, it is an

essential part of designing an effective PDA based sensor. Additionally, we show that

side-chain composition dictates whether self-assembled sensor vesicles will have

sufficient alignment upon polymerization to elicit a significant chromic response.

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Figure 41: Effect of PDA functional end-group on initial blue percentage for 100%

surface functionality of PCDA (carboxyl), PCDA-Trp, and PCDA-Trp-His-Trp

Using 100% surface density of PCDA, PCDA-Trp, and PCDA-Trp-His-Trp, we

identified the steric effect of side chain size on the ability of the vesicles to retain a planar

conjugated backbone. Here we demonstrate the importance of packing ability on

controlling the extent of blue percentage. From Figure-41, we see that increasing the

steric hindrance through bulkier PDA-peptide conjugates affects the ability for effective

packing of the PDA side-chains causing a noticeable decrease in blue percentage. The

observed color of PDA is a direct result of the effective conjugation length of the

delocalized π-conjugated polymer backbones.160

Properly aligned monomer side-chain

units which undergo UV irradiation will polymerize by means of the reactive diacetylene

groups to form blue PDA arrangements which retain their original mesostructure.180

Aside from stimulus driven red shifts, misalignment within the PDA vesicle can results in

a chromatic transition due to increased HOMO-LUMO spacing of the delocalized π

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electrons along the PDA backbone. This is directly attributed to the decrease in the

effective conjugate length from reduction in π-π stacking between adjacent chains.181, 182

With 100% Trp-His-Trp receptor surface density, we see that even prior to the

introduction of an external stimulus the vesicle based sensor has already reached its red

phase indicating that the conjugation length is insufficient to render any further chromic

response. From this, we conclude that high concentrations of bulky receptor side-chains

sterically restrict the proper alignment of monomers, thereby making such vesicles

unusable for sensing purposes. Depending on the target sensing application, it may be

essential to use bulky receptors. Therefore, it is important to consider the use of

promoter elements and the appropriate surface density to achieve an effective

composition of the desired receptor as we explore in the following sections.

5.4.4 Effects of surface density

For the sensor to be practical, the surface must be incorporated with receptive motifs at

the appropriate density to ensure a sufficiently high initial blue percentage as well as

sufficient density to elicit a change in the absorption spectra. To investigate this in

relation to steric effects, we analyzed the effect of receptor surface density on the

chromic response of the sensor. Because of steric hindrance effects, 100% surface

receptor density will prevent proper initial monomer alignment during assembly. This

results in insufficient conjugation lengths to elicit a detectable chromic response. A

visually detectable chromic response is on the order of a 15% change.183

To design an

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effective sensor vesicle, it is important to consider the parameter of PDA-peptide

conjugate surface density which is able to allow such a chromic response. Therefore, the

surface density must be sufficiently high to provide enough transduction sites to disrupt

the planar backbone such that the chromic response is greater than 15%. Conversely, the

surface density must be low enough to ensure that the pre-exposed vesicles do not exist in

the triggered red phase due to steric hindrance, as discussed above. To analyze this

parameter, we observed the blue percentage from vesicle spectra as a function of Trp-

His-Trp receptor surface density.

Figure 42: Dependence of initial blue percentage on the surface density of vesicles

comprising various concentrations of peptide-conjugate PCDA-Trp-His-Trp. The

dashed line represents the minimum blue percentage (42%) required to have a

visually detectable chromic response of 15% change relative to the blue percentage

provided at 100% surface density.

From Figure-42, we can easily identify the extent to which steric hindrance plays a role in

breaking planarity of the conjugated π-backbone of PDA. We are particularly interested

in identifying this failure point in optical quality in which sterics prevent extended

backbone planarity after polymerization. The blue percentage decreases rapidly with

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increasing surface density such that only vesicles with Trp-His-Trp surface receptor

densities less than 14% may be considered practical from a sensor perspective. This is

because an initial blue percentage of at least 42% is required to possibly attain the 15%

chromic response necessary for visual differentiation. Investigation of this parameter is

dependent on the sterics associated with the side-chain functionality. To design an

effective sensor vesicle, researchers must consider the surface density effect on blue

percentage for their particular surface receptor. Ideally, this parameter would be the

largest possible surface density that also allows a chromic response of 15% to be realized.

5.4.5 Evaluating the Effect of Target Size

Target size can have a significant effect on the extent of backbone rearrangement that

occurs, thereby affecting the observed color change. We evaluate the effects of target

size on the chromic response of PDA as well as the effect of utilizing promoter elements

to enhance the chromic response. Using our modular approach, we incorporated different

recognition elements onto the vesicle surface to facilitate binding of a given target. The

versatile nature of this design allowed us to detect a variety of different targets ranging

from small molecules to large cells. First, we explored the use of the peptide conjugate

PCDA-Trp-His-Trp for the purpose of TNT detection. Exposure to 11 µM of TNT

resulted in a red shift in wavelength absorption as identified from spectra analyses,

Figure-43a. Specifically, a change in blue percentage was calculated with a resulting

chromic response of 2.7%. While this demonstrated that the system can detect small

molecules, the level of chromic response is below that discernable by the naked eye. In

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an attempt to enhance the chromic response, a promoter element (PCDA-Trp), was

incorporated at equimolar surface density with the PCDA-Trp-His-Trp receptor elements.

The use of analogous promoter elements have been reported to facilitate chromic

transition by relaying the receptor-target binding to transduction of side-chain

conformation changes resulting in breaking of backbone planarity.179

Figure-43b

demonstrates the use of the receptor/promoter system with 2% PCDA-Trp-His-Trp and

2% PCDA-Trp in the presence of 11 µM of TNT. Analysis of the spectra reveals a

chromic response of 3.5% which is only a small increase that remains below that chromic

response necessary for visual detection. The last sensor vesicle system tested in 11 µM

of TNT was comprised of 4% PCDA-Trp-His-Trp and 4% PCDA-Trp. Again the

chromic response was not visually detectable, but the positive effect of the promoter was

easily revealed in the spectrophotometer measurements showing a slight increase of

chromic response to 4.1%, see Figure-43c. Control experiments with vesicles comprised

of only 4% PCDA-Trp promoter show a chromic response of 1.1% indicating the

promoter is not actively binding.

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Figure 43: Visible-absorption spectra of polymerized vesicles containing: a) 4

mol % Trp-His-Trp surface receptor; b) 2 mol % Trp and 2 mol % Trp-His-Trp

surface receptor; c) 4 mol % Trp and 4 mol % Trp-His-Trp surface receptor; d) 4

mol % Gly-Arg-Gly-Asp-Ser surface receptor. Solid lines represent the non-

exposed spectra while dashed lines represent spectra attained after target exposure.

Exposed spectra are normalized to the corresponding non-exposed spectra and y-

axes scaled to clarify the change in chromic response.

To test the system for larger targets, we pursued the detection of human fibroblasts.

Using our modular sensor approach we could easily incorporate the known sequence

derived from fibronectin protein for binding to cell surface receptors known as integrins.

The sequence was synthesized as the peptide conjugate, PCDA-Gly-Arg-Gly-Asp-Ser.

The spectrum shown in Figure-43d shows the effect of exposing the sensor vesicles to

100 cells/µL of fibroblasts. The average chromic response was calculated to be 36.7%,

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which is significantly larger than that achieved in small molecule target detection. In fact,

the chromic response was easily visually detectable, as it was well above 15%. Negative

controls of 100% PCDA vesicles were subjected to 100 cells/µL of fibroblasts resulting

in a chromic response of 4.5%. This indicates the integrin binding sequence was critical

to initiating a larger spectral response. This more noticeable spectral shift seen for cell

targets compared to small molecule targets may potentially arise due to the large area

available for cell–vesicle interaction which could allow long-range structural changes in

the planar backbone to occur. With the proper consideration of composition and

assembly parameters outlined above, we have successfully demonstrated the versatility,

efficacy, and potential for this platform as a widely deployable sensor. Additionally, the

modular nature of the platform may allow the detection of a variety of targets ranging

from small molecules to large cells.

5.4.6 Effect of Alkane Chain Length on Sensitivity

By increasing the chromic response of the system over a range of concentrations, we may

effectively amplify the color change for enhanced signal detection. We showed that

alkane chain length can influence the sensitivity of the PDA based sensor thereby

providing a means of increasing chromic response. Using the same modular approach,

Trp-His-Trp was incorporated with PDA elements having shorter or longer alkane

elements as compared to PCDA. By monitoring the TNT response of HCDA, PCDA,

and TCDA conjugates of Trp-His-Trp, we were able to identify an effect of alkane chain

length on the sensitivity of the vesicle system to target binding. HCDA, PCDA, and

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TCDA have alkanes of decreasing chain length as shown in Figure-38. As the alkane

chain length decreased, we identified an increase in sensitivity of the systems to the

presence of TNT over a range of concentrations, Figure-44. Additionally, our data

demonstrates a chromic response increase with increasing TNT concentration. This

effect recapitulates the concentration dependence of chromic response seen in other PDA

based sensors.142-144

From these experiments, the largest chromic response to TNT,

which was 5.1%, occurred at the TNT concentration of 33.5 µM using 10% TCDA-Trp-

His-Trp. Through this, we demonstrated that the alkane chain length is indeed a critical

parameter to be taken into consideration when designing a PDA based sensing system.

Figure 44: Dependence of alkane chain length on PDA-Trp-His-Trp sensitivity to

TNT target. Decreasing PDA lengths facilitate a higher chromic response over a

range of TNT concentrations.

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5.5 Conclusion

Utilizing a modular synthesis strategy to couple recognition elements to chromic

responsive polydiacetylene elements, we created a vesicle based sensor to explore the

essential parameters that must be considered in the sensor design process. We

demonstrated that, using this modular approach, sensing systems can be created for a

variety of targets ranging from small molecules (TNT) to large biological systems

(human fibroblasts). In depth discussion of the system parameters is presented from the

aspects of synthesis (receptor and promoter characteristics), composition (surface density

control), and assembly (polymerization considerations). Specific examples of sensor

design for target response have been demonstrated. Choosing a PDA with an

appropriately short alkane chain length proved to be highly important for amplifying the

sensitivity of chromic response to the presence of the small molecule target TNT. With

the PCDA sensor vesicle systems, we were also able to identify the important role of

side-chain composition and surface density on the transduction of chromic transition

from surface interactions by observing shifts in the absorption spectra. Additionally, we

identified a tradeoff in surface density considerations between proper monomer

alignment and sufficiently high receptor density to elicit a visually detectable chromic

response. While we see that low surface receptor densities can present a potential

limitation to these systems, the advantages of easy and low cost manufacturing, simple

analysis, and modular incorporation of target recognition elements make it a viable

candidate for a widely deployable chemical sensing system.

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Chapter 6: Summary and Outlook

6.1 Molecular Recognition Elements

By utilizing phage display, molecular recognition elements have been developed for TNT

and DNT. The TNT recognition element was found to be a peptide with a conserved

amino acid sequence with high similarity to the binding site of pentaerythritol tetranitrate

reductase, one of nature’s own TNT binding proteins. Such TNT binding proteins

generally exhibit a highly conserved tryptophan residue which is involved in the binding

event. Similarly, the studies outline in this work also demonstrated the importance of

tryptophan in binding to TNT. Through mutational analysis of our TNT binding motif as

well as through NMR spectroscopic methods, we have demonstrated the role of

multivalent binding involving neighboring tryptophan residues. There are several

mechanisms by which tryptophan can contribute to TNT binding. Similar to what is seen

for the PETN-reductase, we have found that our TNT binding motif utilizes the aromatic

stacking between tryptophan and the ring structures of nitroaromatics. Furthermore, this

work demonstrates the successful evolutionary screening against not only TNT but also

DNT. In doing so, phage display was identified as successful for developing selective

peptide based receptors for various small molecules. Additionally, the multivalent

binding was identified to be critical to achieving the necessary selectivity.

While biology is extremely effective at creating specific molecular interaction,

researchers still struggle to achieve molecular recognition. Generally, the occurrence of

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such recognition has arisen out of necessity, as most cellular processes rely on highly

important binding events. To identify the mechanisms of such molecular recognition

events, we need to achieve a working knowledge of biomolecular interactions. While

this exists to DNA-DNA interaction, protein-protein and protein-small molecule

interactions do not have a formulaic answer. As such, research will continue to achieve

incremental gains in the knowledge base of biomolecular interactions via spectroscopy

and crystallization techniques. From this, the full understanding of model systems may

allow a more comprehensive level of intermolecular host/guest interaction mechanisms to

be achieved.

The concept of molecular recognition requires a receptor (host) molecule to participate in

non-covalent bonding with a specific ligand (guest). Several coupling events can occur

between a given receptor-ligand pair including hydrogen bonding, electrostatic

interactions, aromatic interactions, or Van der Waals interactions. In a molecular

recognition event, it is typical for several combinations of these interactions to occur

simultaneously. This multi-valence binding is critical for receptors to discriminate

between different potential guest target molecules. This differentiation for a specific

guest is deemed the selectivity of a receptor. Several factors have been found to

contribute to a selective molecular recognition event including: complementary

molecular shape, appropriate structural rigidity, and appropriate available binding sites.

By optimizing the number of potential interaction as well as the shape of the binding site

in relation to the target molecule, a proper distance between functional groups can be

achieved for effective hydrogen bonding and aromatic interactions. However, if size

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exclusion becomes evident, a receptor-ligand binding affinity will be greatly reduced as it

may only have binding contributions from long-rand electrostatic interactions. By

looking at the effects of steric hindrance, one can see that size exclusion helps to

contribute to selectivity in a molecular recognition event.

Aside from the role of steric, an effective molecular recognition element must have an

optimized level of structural rigidity. Particularly, an adequate level of ridigity in the

binding site can minimize entropic loss that would occur upon rearrangement of a main

chain (ie. peptide backbone) in a recognition event. The locking of such rotating bonds

would add to this loss in binding energy. Typical conformation changes of a peptide

backbone are less that 0.1nm, though functional side-chain dynamics can be significantly

altered and restricted upon binding. Supramolecular chemists have taken this into account

and have utilized cyclic structure as receptor templates for a variety of target molecules.

In addition to the above consideration of shape and structural plasticity, the use of

appropriate functional groups continues to be a key component for the design of selective

receptors. The selective recognition of a target may necessitate a binding site which

contains acid functionalities for interacting with amine and amide functions on a target

molecule. Hydrogen bonding is generally a main contributor to recognition events given

as these interactions occur for a variety of polar functionalities including carboxylic

acids, carbamates and carboxylic esters. Aromatic functionalities offer another set of

binding mechanisms including cation-π, anion-π , and π–π interactions. Charge transfer

interaction, dipole-dipole interactions, and van der Waals interactions also may contribute

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to a selective recognition event. By tuning the location of such functional groups to be

complimentary to those of the target molecule, researchers may design effective

recognition elements for a target of interest. It is the hope of the molecular recognition

research community to implement principles gained from research such as this to develop

a generalized set of mechanisms to predict selective target binding.

6.2 Sensor Coatings

Development of a chemical sensor coating, which holds the ability to selectively

discriminate between target and non-target chemicals, is a highly desirable technology.

Such technology would facilitate the detection of the surrounding chemical vapor

landscape. This is of importance to identify information about potential environmental

contaminants and health threats, including industrial carcinogen, explosive, or pesticides.

Such target molecules of interest include volatile small molecules which typically have a

molecular weight in the range of 50-500 g/mol. Current chemical sensors, while very

sensitive, have a lack of proper selectivity. As such, the main challenge in chemical

sensing continues to be creating a chemical detection system which is successful in the

midst of various potential interfering agents that may elicit a false positive.

Utilizing the peptides recognized through phage display, we implemented a strategy for

creating selective coatings for sensor platform technologies. Specifically, we

incorporated a receptor which binds to TNT onto a PEGM polymer via an easy coupling

mechanism. Using an epoxy group present on one of the monomers of PEGM, primary

113

amino groups present on the receptor were capable of covalently attaching, and this

attachment was found to be highly stable. Using both XPS and GC/MS, we identified the

receptor as stably attached and capable of retaining its target selectivity. To further

explore the use of the coating, the PEGM/TNT receptor conjugate was implemented on a

real-time sensing platform (QCM). We identified the selective detection of the explosive

TNT in water by a decrease in resonance frequency of the QCM, while there was no

change in resonance frequency when the coated QCM crystal was exposed to DNT

solution. The potential application of this sensitive and selective liquid detection of TNT

is particularly appealing for analysis of contamination of ground waters near ammunition

depots. We foresee the use of such coatings for various sensing applications which can

be tailored by changing the selectivity motif.

Several other interesting coating technologies have recently been implemented including

polymeric binding pockets from molecular imprinting, de novo designed receptors using

supramolecular chemistry, and engineering of existing recognition elements from

biological receptors. While molecular imprinting has offered impressive selectivity by

demonstrating the ability to discriminate between enantiomers, there are inherent

limitations in using a cross-linked polymer for a QCM sensor. Particularly, swelling of

the polymer in different environments can easily cause a false-positive signal.

Additionally, the non-uniformity of cavity formation results in “poly-clonal” binding

sited which provides mechanisms for non-specific interactions in a complex targeting

environment. The coating technologies developed using supramolecular chemistry do

not fall victim to this, as the de novo designed receptors are uniform. Using

114

computational and theoretical means, supramolecular chemists have been able to design

receptors specific to a target by implementing a complimentary curvature, size, and

functionality. This approach offers high affinity, though intensive design and trial-and-

error are required, as such only a small number of specialized receptors have been

accomplished via this coating approach. A more generalized approach, which has shown

similar efficacy, utilizes engineering of existing protein binding site. By modifying the

molecular recognition motif of natural occurring receptor proteins, researchers have

found ways of altering specificity toward a particular target of interest. Using

mutagenesis and computational modeling, highly selective receptive motifs have been

identified though there use on chemical sensors is not without drawback. Particularly,

there implementation onto sensing platforms has seen limited success due to stability

issue of large protein domains over long time scales and un-natural environments.

Perhaps, these technologies will soon provide improved approaches to chemical sensor

coatings, though progress in overcoming fundamental sensor coating problems must be

taken into account, such as overcoming humidity response issues, eliminating non-

specific interaction, and maintaining stability in a variety of sensing environments.

6.3 Sensing Platforms

The current standard for chemic sensing systems are those based on chromatography-

mass spectroscopy, as these systems are capable of both high sensitivity and high

selectivity. GC/MS sensing systems are currently employed at points of security

screening, although there large size, expensive price, and complex data analysis has

115

hindered there widespread use. To overcome this problem, researchers have explored the

creation of inexpensive and portable chemical sensing systems. Some of the most

promising candidates for widely deployable chemical sensing systems utilize a

technology based on the transduction of ligand-receptor binding into an electrical signal.

Many target binding based sensing platforms utilize an array of polymer coatings from

which a signature pattern may be generated for a give target molecule. This interesting

approach works very well for pure target exposure, though as these polymers are non-

specific they may not be effective in a real world sensing environment in which there are

a variety of background chemical signals. In particular, this non-specificity means the

affinity ratio among different analytes is not discernable and the binding of background

chemicals would create too much uncertainty in the signal. While we have focused

mainly on the creation of selective coating layers, it is important to note there are several

highly sensitive chemical sensing platforms available. It was necessary to look closely at

the sensing mechanisms of theses sensors in order to effectively create a coating that

works well in relation to the signal transduction mechanism used by these sensors. The

sensitivity of the transducer to ligand-receptor binding events depends heavily on which

sensing platform is to be used. Transduction can occur via changes in electrical

resistance of a chemoresistor, a frequency shift in mechanical resonance devices such as

the quartz crystal microbalance used in this work, frequency shift in the optical

resonances of platforms such a SPR (surface plasmon resonance), or even surface stress

based transduction for creating structural deflections such as in cantilever based sensors.

116

Each of the above chemical sensing systems are effective at providing highly sensitive

detection of chemicals. By incorporating such devices with a sensor coating, we can

provide a mechanism for selectivity of the binding event. Future work may utilize these

sensor coatings with work being develop to exploit several simultaneous transduction

mechanisms. For a ligand-receptor interaction event, binding may result in changing a

local dielectric constant, causing an addition of mass, and generation of intermolecular

forces. By creating a device capable of detecting each of these physical changes

simultaneously, one could gains a variety of binding information to overcome the

challenges associated with selective molecular recognition. The micromembrane and

microcantilever systems being developed in our laboratory may provide a means of

identifying several of these changes simultaneously. For instance, a change in mass

addition or surface stress may produce changes in the resonant frequency detectable by

capacitance measurements via a micromembrane sensor. Capacitance changes due to

dielectric changes from target analyte replace of water may also be used simultaneously

in such a sensor. Incorporation of multiple modes of target selective signal

discrimination will remain critical to achieving a robust sensing platform.

With this in mind, the knowledge gained from our research has provided a way to

overcome the poor selectivity of conventional polymer-based coating. By utilizing

sequence-specific heteropolymers akin to biological mechanisms of achieving selectivity,

we have utilized peptides rich in structure and chemical functionality to find a receptor

for the explosive TNT. Utilizing a variety of polymers, we identified an effective coating

which minimizes the humidity response while allowing the receptor to remain specific for

117

TNT. We believe this coating could be used on a variety of existing sensing platforms in

addition to QCM which has already been demonstrated. Additionally, we utilized a

modular synthesis strategy to create a colorimetric sensor via chromic responsive

polydiacetylene elements liked to a receptor of interest. We demonstrated that, using this

modular approach, sensing systems can be created for a variety of targets ranging from

small molecules (TNT) to large biological systems (human fibroblasts). By optimizing

various parameters of the sensor development, we were able to increase the sensitivity of

the sensor to TNT. We believe the advantages of easy and low cost manufacturing,

simple analysis, and modular incorporation of target recognition elements make this

strategy a viable approach for the development of widely deployable chemical sensing

systems.

118

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