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Biophysical Investigations of Allostery in
E.coli Adenylate Kinase Using Entropy
Enhancing Mutations
by
Harry Gustavo Saavedra Espinoza
A dissertation submitted to Johns Hopkins University
in conformity with the requirements for the degree of
Doctor of Philosophy
Baltimore, Maryland
May, 2015
2015 Harry G. Saavedra Espinoza
All Rights Reserved
Abstract
Allostery is the regulatory effect that a perturbation in one region has on an-
other distal site of the same macromolecule. Although allostery has been studied
extensively, understanding of how a perturbation in one region can affect other
region(s) is still incomplete. For a long time, allostery has been regarded as a
structural-based phenomenon. However, it is currently known that allostery can
also be manifested without perturbation in the crystal structure. Also, it has
been demonstrated from studies of thermal adapted enzymes, that enzyme func-
tion regulation can be promoted by increasing the conformational flexibility in
regions other than the active site. To understand these different facets of allostery,
we used Escherichia coli adenylate kinase as a model system. This enzyme is
composed of three distinct domains: The LID, CORE and AMPbd domains. To
answer the question of how conformational perturbations regulate enzyme func-
tion, entropy-enhancing Gly substitutions were used on distal uncharged solvent
exposed residues located far from the active site. Mutations on the three do-
mains were chosen in order to avoid or minimize structural distortions. Subse-
quently, the impact of increased conformational flexibility on the ensemble, bind-
ing affinity and catalytic activity were investigated with DSC, ITC and catalytic
activity assays. In addition, ensemble modulation was characterized by combin-
ing HX-NMR and ITC techniques. Together, the results show that enzymes can
use local unfolding in regions distal to the active site to regulate macromolec-
ular function. This regulation arises predominantly from the redistribution of
ii
the probabilities of states promoted by local destabilization of the enzyme. Also,
this work indicates that allostery can also be understood from a thermodynamic
point of view. Finally, it is shown that the LID interacts with the other domains.
Advisor: Prof. Vincent Hilser
Reader: Prof. Doug Barrick
iii
To my beloved mother, Zoraida, wife, Alicia, and son Rodrigo.
iv
Preface
Life as well as scientific research are not traveled alone. During my years in gradu-
ate school, I was very fortunate to be surrounded by great and supporting people.
Above all, I would like to thank my advisor, Dr. Vincent Hilser for giving me the
opportunity to carry out research in his laboratory. The knowledge I have acquired
from him is invaluable. Not only at the scientific level but also at the personal
level. I really appreciate his efforts in transmitting the value of clear writing and
effective presentations.
I am also indebted to my thesis committee members: Dr. Richard Cone, Dr.
Bertrand Garcia-Moreno, Dr. Doug Barrick and Dr. Greg Bowman. The guidance
and suggestions they gave in every thesis review were really helpful to overcome
different obstacles I faced out during my research journey. Their mentorship com-
plemented Dr. Hilser’s guidance that provided me a wide scientific perspective.
The other person to whom I am eternally grateful is Dr. James Wrabl. He was
always ready to share with me not only insightful ideas but also research expe-
rience. In addition, I would like to thank present and previous students in the
lab, especially Dr. Travis Schrank, who trained me on protein expression and pu-
rification, Dr. William Elam, who showed my how to use the ITC calorimeter,
Dr. Jing Li, who shared with me her expertise on mutagenesis, Jeremy Anderson,
who shared with me 15N-labeled V142G; and, Andrew Martens, Hesam Motlagh,
Jordan White, Alex Chin and James Rives for their useful feedback on my research.
v
I also like to thank our great collaborators -and great people- who played impor-
tant roles in my research. Dr. Arne Schon for sharing his extensive knowledge of
the experimental nuances associated with DSC experiments. Dr. Ananya Majun-
dar for training me on the operation of the NMR spectrometer, and, Dr. Katherine
Tripp for her logistic support on the ITC and DSC calorimeters.
Last, but certainly not least, I would like to acknowledge my mother, Zoraida,
my wife, Alicia, and my son Rodrigo for their love, patience and support during
my years in graduate school.
vi
Table of Contents
Table of Contents vi
List of Tables x
List of Figures xii
List of Abbreviations xix
1 Introduction 1
1.1 Allostery, structural and ensemble views . . . . . . . . . . . . . . . 1
1.2 Thermal adaptations of enzymes . . . . . . . . . . . . . . . . . . . . 3
1.3 E. coli adenylate kinase as a model system . . . . . . . . . . . . . . 4
1.4 Mutational strategy employed to investigate allostery . . . . . . . . 5
1.5 Previous results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.5.1 Glycine mutation promotes local unfolding . . . . . . . . . . 5
1.5.2 One mutation in the LID does not distort the crystallo-
graphic structure . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.3 Allostery can occur in the absence of structural distortion . 6
1.6 Thesis overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 Materials and methods of AK preparation 14
2.1 Selection of entropy enhancing glycine mutations . . . . . . . . . . 14
2.2 Site directed mutagenesis . . . . . . . . . . . . . . . . . . . . . . . . 15
vii
2.3 LIDLESS plasmid construction . . . . . . . . . . . . . . . . . . . . 16
2.4 Protein expression,purification, and storage . . . . . . . . . . . . . . 17
3 Calorimetric determination of interdomain interactions and sta-
bility of AK constructs 21
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.3 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.3.1 Protein preparation . . . . . . . . . . . . . . . . . . . . . . . 22
3.3.2 DSC experimental design . . . . . . . . . . . . . . . . . . . . 23
3.3.3 Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.4.1 The CORE-AMPbd unfolds as a single domain and it is cou-
pled to the LID . . . . . . . . . . . . . . . . . . . . . . . . 29
3.4.2 Single and double mutants promote local unfolding . . . . . 30
3.4.3 Coupling interactions are still present even though the LID
is unfolded . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.4.4 Local unfolding mechanism for stability change . . . . . . . 31
3.4.5 Local unfolding modulates the conformational ensemble . . . 32
3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4 Calorimetric determination of inhibitor binding affinity of AK
constructs 49
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.3 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.3.1 Protein preparation . . . . . . . . . . . . . . . . . . . . . . . 51
4.3.2 ITC experimental design . . . . . . . . . . . . . . . . . . . . 51
viii
4.3.3 Linkage analysis between local unfolding and ensemble mod-
ulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.3.4 Prediction of ∆Ha and ∆Ga . . . . . . . . . . . . . . . . . . 54
4.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.4.1 Local unfolding promoted by mutations modulates binding
affinity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.4.2 The CORE-AMPbd can also bind Ap5A in the absence of
the LID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.4.3 Trends of free energy and enthalpy of binding as functions
of temperature can be predicted using EAM . . . . . . . . . 56
4.4.4 Double mutations in the LID completely depopulate the
folded state at 40 . . . . . . . . . . . . . . . . . . . . . . . 57
4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5 Measurement of catalytic rate of AK constructs 69
5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
5.3 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.3.1 Measurements of catalytic activity in the reverse reaction . . 71
5.3.2 Transition state characterization . . . . . . . . . . . . . . . . 72
5.3.3 Exploration of kcat modulation through a random Bi Bi mech-
anism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.4.1 Mutational effects are temperature dependent . . . . . . . . 73
5.4.2 Local unfolding modulates kcat . . . . . . . . . . . . . . . . . 74
5.4.3 LIDLESS exhibits marginal catalytic activity . . . . . . . . 75
5.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
ix
6 Characterization of the ensemble modulation using HX-NMR and
ITC 83
6.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.3 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . 85
6.3.1 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . 85
6.4 Data acquisition and processing . . . . . . . . . . . . . . . . . . . . 86
6.5 Domain stabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.6 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . 89
6.6.1 The CORE is the most stable domain. . . . . . . . . . . . . 89
6.6.2 V142G modulates the conformational ensemble. . . . . . . . 89
6.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
7 Concluding remarks 100
7.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
7.2 Future directions and experiments . . . . . . . . . . . . . . . . . . . 101
x
List of Tables
3.1 Summary of the thermodynamic parameters obtained from DSC. . . 43
3.2 Stability perturbation of AK domains promoted by Gly mutations. 44
4.1 Intrinsic enthalpy of binding (∆CP,o) of AK constructs. . . . . . . . 68
5.1 Representative values of kcat at 25 . . . . . . . . . . . . . . . . . . 79
5.2 Characterization of the transition state using the linear Eyring-
Polanyi equation, see Eq. 5.3. . . . . . . . . . . . . . . . . . . . . . 80
6.1 ∆GHX of L83 and V106 in WT. . . . . . . . . . . . . . . . . . . . . 91
6.2 ∆GHX of residues L83 and V106 in V142G. . . . . . . . . . . . . . 94
6.3 ∆Ga and ∆GHX values for WT and V142G at 37 . . . . . . . . . . 97
6.4 Domain stabilities in WT and V142G at 37 . . . . . . . . . . . . . 97
xi
List of Figures
1.1 E. coli AK: domains and catalytic scheme. . . . . . . . . . . . . . . 10
1.2 Local unfolding promoted by V142G affects neighboring residues. . 11
1.3 V142G can destabilize the entire LID domain . . . . . . . . . . . . 12
1.4 Mutational effects introduced by one mutation do not affect the
crystallographic structure. . . . . . . . . . . . . . . . . . . . . . . . 13
1.5 Modulation of binding affinity at different temperatures. . . . . . . 13
2.1 Selected Gly mutations on uncharged solvent exposed residues. . . . 19
2.2 LIDLESS plasmid construction. . . . . . . . . . . . . . . . . . . . . 20
3.1 Mutation positions in AK used for DSC experiments shown in red. . 34
3.2 Thermal unfolding simulation of the CORE-AMPbd and the LID
based on Eq. 3.17. . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.3 Corrected 〈∆CP,tr〉 of LIDLESS upon removing the stability effects
of the flexible linker, see Eq. 3.12 . . . . . . . . . . . . . . . . . . . 36
3.4 Comparison of 〈∆CP,tr〉 profiles of WT and LIDLESS. Decreased
Tm of LIDLESS is clearly evident. . . . . . . . . . . . . . . . . . . . 37
3.5 〈∆CP,tr〉 profiles of WT, A55G and A73G. Single mutants exhibit a
small decrease in Tm as compared to WT. . . . . . . . . . . . . . . 38
3.6 〈∆CP,tr〉 profiles of WT, V135G, V142G and V135G/V142G. . . . . 39
3.7 〈∆CP,tr〉 profiles of WT, A73G, V142G and A73G/V142G. . . . . . 40
3.8 ∆CP associated with the unfolding of the CORE-AMPbd . . . . . . 41
xii
3.9 ∆CP associated with the unfolding of the LID . . . . . . . . . . . . 42
3.10 Thermal stabilities calculated according to thermodynamic param-
eters from Table 3.1. . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.11 Coupling interaction (φ)between the LID and CORE-AMPbd in
WT at 37 , based on Fig. 3.10 (b) . . . . . . . . . . . . . . . . . 46
3.12 Theoretical state probabilities vs temperature plots determined us-
ing values from Table 3.1 and Eq. 3.1 . . . . . . . . . . . . . . . . . 47
3.13 Probabilities of the folded state of different constructs calculated at
37 using values from Table 3.1. . . . . . . . . . . . . . . . . . . . 48
4.1 Simulations of ∆Ha as a function of temperature of AK mutants
using Eq. 4.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.2 Simulation of ∆Ga at different temperatures of AK mutants using
Eq. 4.5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3 Apparent enthalpies of binding of AK constructs vs temperature
(∆Ha vs T). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.4 Apparent free energies of binding of AK constructs vs temperature
(∆Ga vs T). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.5 Representative ITC titration curves at 37 with respective fitting
parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.6 Representative binding signatures at 37 . . . . . . . . . . . . . . 64
4.7 Simulated ∆Ha of V135G/V142G as a function of temperature using
Eq. 4.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.8 Simulated ∆Ga of V135G/V142G as a function of temperature using
Eq. 4.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.9 Simulated probabilities of states of simulated V135G/V142G in the
absence of Ap5A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
xiii
5.1 Kinetic model for AK. . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.2 Expected ln(kcat/T ) vs 1000/T using Eq. 5.4. . . . . . . . . . . . . 77
5.3 Experimental data fitted to the linear form of the Eyring-Polanyi
equation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5.4 Simulation of mutational effects of A55G and A73G on kcat. . . . . 81
5.5 Simulation of mutational effects of V135G and V142G on kcat. . . . 82
6.1 Location of residues in the EX2 in WT. . . . . . . . . . . . . . . . . 91
6.2 The apparent rate constant (kex) of residues L83 and V106 in WT. 92
6.3 Residues in the EX2 regime in WT. . . . . . . . . . . . . . . . . . . 93
6.4 Location of residues in the EX2 regime in V142G. . . . . . . . . . . 94
6.5 The apparent rate constant (kex) of residues L83 and V106 in V142G. 95
6.6 Residues in the EX2 regime in V142G. . . . . . . . . . . . . . . . . 96
6.7 Graphical representation of ∆GLID and ∆gmut. . . . . . . . . . . . 98
6.8 Probabilities of the folded state of WT and V142G at 37 using
values from Table 6.4. . . . . . . . . . . . . . . . . . . . . . . . . . 99
7.1 Comparisson between the area under the data points (∆Hcal) and
the van’t Hoff enthalpy (∆HvH) . . . . . . . . . . . . . . . . . . . . 119
xiv
List of Abbreviations
ADP Adenosine diphosphate
AMP Adenosine monophosphate
ATP Adenosine triphosphate
Ala Alanine
AK Escherichia coli adenylate kinase
AMP Adenosine monophosphate
Ap5A P1, P5-Di-(adenosine- 5’)-pentaphosphate
ATP Adenosine triphosphate
CA CORE-AMPbd domain
ddH2O Double-distilled water
DSC Differential scanning calorimetry
DMSO Dimethyl sulfoxide
EAM Ensemble Allosteric Model
F Folded state
Gly Glycine
HX-NMR Hydrogen/deuterium exchange NMR
HSQC Heteronuclear single quantum coherence spectroscopy
xv
ITC Isothermal titration calorimetry
IPTG Isopropyl-D-thiogalactopyranoside
K Equilibrium constant
kcat Catalytic rate
KNF Koshland-Nemethy-Filmer
LU Locally unfolded state
MWC Monod-Wyman-Changeux
NADP Nicotinamide adenine dinucleotide phosphate
NADPH Nicotinamide adenine dinucleotide phosphate reduced
NMR Nuclear magnetic resonance
PCR Polymerase chain reaction
Q Conformational partition function
R Gas constant, (1.986 cal/mol*K)
SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis
T Temperature
Tm Melting temperature
U Unfolded state
Val Valine
WT Wild type
∆CP Change in heat capacity at constant pressure
∆H Change in standard-state enthalpy
xvi
∆G Change in standard-state free energy
∆S Change in standard-state entropy
∆∆G Difference in change in standard-state free energy
xvii
Chapter 1
Introduction
1.1 Allostery, structural and ensemble views
Allostery is the regulation of protein function by remote perturbations such as, but
not restricted to, ligand binding, mutations, change in temperature, and change
in pH. The understanding of this action-at-a-distance regulation is fundamental
to elucidating thermal adaptation, cell signaling and diseases. Overall, functional
regulation in one protein can affect the entire homeostasis of the cell [1]. Allostery
was first described by Monod and Jacob [2] in 1961 and mathematically formulated
by Monod, Wyman, and Changeux in 1965 [3] and by Koshland, Nemethy and
Filmer in 1966 [4]. Theories of allostery can be viewed as belonging to one of two
broad classes: structure-based allostery or ensemble-based (dynamic) allostery.
Structural views of allostery often fall into one of two subcategories. In the
concerted MWC (Monod-Wyman-Changeux) model, proteins can only visit two
states, one having only high affinity subunits and the other having only low con-
formational affinity subunits. Also, binding affinity depends only on the state of
the subunit. The underlying assumption of this model is that there is coupling
between subunits; that is, the conformational change in one subunit promotes
conformational changes in another one. On the other hand, the KNF (Koshland-
Nemethy-Filmer) model states that proteins visit sequential states from the un-
bound to the fully bound state as sites fill with ligand. This model assumes that
1
ligand binding induces conformational changes in the whole protein that increases
the binding affinity of the unbound subunits. In both models, allostery is the re-
sult of mass action between low- and high-affinity states, taking proteins as static
structural macromolecules.
Since the realization that proteins are dynamic macromolecules, the concept of
dynamic allostery has been emerging. Cooper and Dryden [5] introduced the idea
of allostery in the absence of structural change. In other words, allostery can be
an entropic effect that results from conformational fluctuations around the mean.
The importance of fluctuations in regulation of enzyme functions is also stated in
the work of Somero et al. [6, 7]. They observed that ortholog lactate dehydroge-
nases (LDHs) from cold adapted fish have higher activity and lower affinity than
those from warm adapted fish. Interestingly, they also observed that cold adapted
LDHs present more Gly residues outside the active site. Based on their findings,
they hypothesized that proteins adapted their functions by modulating the confor-
mational flexibility (i.e. modulating the conformational entropy) in regions other
than the active site.
Recently, several observations cannot be explained by models based on confor-
mational changes. For example, it has been shown that allostery can exclusively
arise due to changes in conformational motions [8] and in the absence of commu-
nicating structural pathway [9]. Furthermore, allostery can manifest in disordered
domains [10] and intrinsically disordered proteins [11]. In order to reconcile these
results, our lab has developed the Ensemble Allosteric Model (EAM) [13] in which
allostery emerges as the conformational ensemble is modulated by, but not lim-
ited to, ligand binding or mutations. According to the EAM, allostery can be
described simply in terms of domain stabilities and energetic interactions between
them. Thus, crystallographic structure is not necessary a priori although a struc-
tural model of allostery can be considered a special case of EAM. The models and
2
analysis presented in this thesis are based on the ensemble redistribution stand-
point.
1.2 Thermal adaptations of enzymes
Cold adapted organisms do not produce more enzyme to survive at lower tem-
peratures. Instead, they adapt enzyme function because no extra metabolic cost
is involved. Enzymes have evolved to function at different temperatures without
extreme changes in their amino acid sequence [6]. Therefore, more flexible en-
zymes would visit binding competent states more easily and counterbalance lower
thermal energy and higher viscosity.
Studies led by Somero and colleagues [6, 7] on enzyme function of ortholog LDH
molecules from cold and warm adapted fish have shed some light on the thermal
adaptation of enzymes. Analysis of amino acid sequences of cold adapted LDHs
revealed more Gly residues in regions outside the active site [6]. Interestingly,
these enzymes presented lower affinity (higher Km) and higher catalytic activity
(kcat) than those of warm adapted LDHs. Based on their findings, Somero and col-
leagues hypothesized that enzymes thermally adapt their function by modulating
their conformational flexibility through sequence changes in region other than the
active site. Since it is known that enzymes exist as a ensemble of states [14, 21, 22],
Somero and colleagues explained their results in the context of ensemble modu-
lation. Higher flexibility increases the population of binding incompetent states,
thus decreasing the observed binding affinity, and increases the speed of catalytic
steps, increasing the catalytic activity. Because less energy is needed to promote
rate-limiting conformational changes and more ordered enzyme-substrate complex
are involved, lower ∆H‡ and more negative ∆S‡ are expected to be observed. As
a result, the activation energy barrier decreases (involving higher kcat) but not at
the same extent as ∆H‡ due to compensating effects.
3
To investigate the relationship between conformational fluctuations and en-
zyme function, i.e. dynamic allostery, we took the ideas presented by Somero
and colleagues as a starting point. The flexibility was increased through entropic
enhancing mutations that avoid or minimize structural distortions in our model
system (E. coli adenylate kinase). Mutations were introduced according to a strat-
egy developed in our lab. Then, stabilities were characterized and enzyme function
of wild type (WT) and mutants at different temperatures. The model system and
the mutational strategy are explained in detail in the next two sections.
1.3 E. coli adenylate kinase as a model system
Escherichia coli adenylate kinase (AK) is a 214 residue enzyme that catalyzes
the interconversion of ATP and AMP into two molecules of ADP. Its function is
essential to maintaining the homeostais of the cell. AK is composed of three specific
domains, the LID, the CORE and AMPbd domains, see Fig. 1.1. During catalysis,
the LID and AMPbd undergo large conformational changes, forming the active site.
Interestingly, these two regions are highly dynamic before binding, allowing the
enzyme to visit conformations similar to the ligand-bound state [15]. This results
suggest that ligands select the binding competent states (conformational selection)
without inducing any significant conformational change. It has been proposed that
residues exist that function as hinges of the LID and AMPbd domains, based on
a close inspection of the crystallographic structures of the apo and holo states
of the Aquifex AK [16]. However, previous studies [9], as well as data analysis
in this thesis, show that regulation of enzyme function is instead promoted by
conformational fluctuations. Therefore, the idea of residues working as molecular
hinges can be discarded.
4
1.4 Mutational strategy employed to investigate
allostery
Glycine promotes local unfolding and hence increases conformational flexibility,
due to the elimination of steric constraints. This residue confers increased flexibility
because it only has a hydrogen as a side chain, presenting a broader φ, ψ space in
the Ramachandran plot. This characteristic allows Gly to be in turns, loops and
in crowded regions forbidden for other larger residues.
Based on the Somero hypothesis, our lab developed a strategy to promote
conformational fluctuations avoiding or minimizing structural perturbations [9].
That is, the conformational entropy is increased while the crystallographic struc-
ture is not perturbed. For that purpose, selected residue positions are mutated
to entropy-enhancing Gly residues. Residues to be mutated should be uncharged,
solvent exposed residues that are not involved in any intramolecular interaction.
In addition, side chains of the chosen residues should be far from the active site
and they should avoid any contact with ligand(s).
To investigate allostery, amino acid substitutions are made in different domains
of AK and their effects on stability and enzyme function, which involves binding
and catalysis, are measured through calorimetric techniques, NMR hydrogen ex-
change and catalytic activity assays. Mutational impact on the conformational
ensemble is determined by comparing the probability of states of the WT with
those of mutants.
1.5 Previous results
1.5.1 Glycine mutation promotes local unfolding
Val to Gly mutations in the LID domain have higher impact on the conforma-
tional entropy. For that reason, 1H-15N HSQC NMR spectra from WT and V142G
5
were collected at 21 and at 33 [9]. At 21 , peaks corresponding to residues
surrounding V142G mutation become undetectable. In addition, no new peaks
appear, indicating extreme broadening of peaks due to a fast chemical exchange
process induced by local unfolding. The almost perfect overlap of spectra, indicates
very similar folded states at this temperature, see Fig. 1.2. When temperature
is increased to 33 , residues from position 109 to 165 become undetectable. It
is clearly observed that temperature affects the extent of local unfolding. Also,
mutational effects of V142G are located not only on the entire LID domain but
also on some residues of the CORE, see Fig. 1.3.
1.5.2 One mutation in the LID does not distort the crys-
tallographic structure
Comparison of the crystal structure of the complex WT-Ap5A with that of V148G-
Ap5A shows that one solvent exposed Val to Gly mutation does not perturb the
protein structure in the bound state. In other words, this result points out that a
single mutation only perturbs the dynamics of the unbound state, increasing the
population of partially unfolded and unfolded states. However, this perturbation
is negligible at low temperature according to the overlap of 1H-15N HSQC NMR
spectra of WT and V142G at 21 .
1.5.3 Allostery can occur in the absence of structural dis-
tortion
V148G does not perturb the crystallographic structure. However, V148G, along
with V135G and V142G, modulate binding affinity [9]. These three single mutants
have the same effect on binding affinity of Ap5A, see inset Fig. 1.5. In addition,
allostery in the absence of conformational changes has been observed in other en-
zymes. Popovych and colleagues found that cAMP binds the two subunits of the
catabolite activator protein (CAP) following a negative cooperativity process. The
6
binding of the first cAMP is associated with higher protein motions. Neverthe-
less, the binding of the second cAMP has a dampening effect on protein motions.
Interestingly, the binding of one cAMP does not induce conformational change in
the other subunit [8].
1.6 Thesis overview
Allostery can be the result of higher flexibility in regions other than the active site
in the absence of any structural alteration. To answer the question of how allostery
arises, we proposed the hypothesis that proteins modulate enzyme function by pro-
moting local unfolding without any structural distortion in distal regions from the
catalytic site. To test, this hypothesis, we used Gly substitutions in the LID, CORE
and AMPbd according to the mutational strategy previously introduced. Then we
investigated the effect of mutations in binding affinity and catalytic activity.
In Chapter 2, Gly mutations were selected according to the strategy developed
in our lab. Substitutions were done in solvent exposed residues that are distal
from the active site. For that purpose, we inspected the crystallographic structure
of WT AK in the apo and holo forms. Details of plasmid preparations, protein
expression, and purification of Gly and LIDLESS mutants are also described.
In Chapter 3, the effect of Gly mutations on stability and ensemble modulation
was investigated through differential scanning calorimetry in the absence of any
ligand. Also, the energetic coupling between the LID and CORE-AMPbd domains
were investigated by replacing the whole LID with a short Gly-rich linker (LID-
LESS construct). It was found that mutations affected stability, especially those
located in the LID domain. The effect of local unfolding was directly observed
as shifts in unfolding transitions. The ensemble probability of states was then
calculated according to a sequential three-state model. It was determined that
the population of the folded state in WT represents 95% of all the states visited
7
by AK at 37 . The other 5% corresponds to an intermediate state whereby the
LID is unfolded. As expected, the population of the folded state was reduced by
mutations. For instance, the probability of the folded state dropped to 54% in
V135G at the same temperature. Furthermore, it was also found that the stability
of the CORE-AMPbd increases in the absence of the LID (LIDLESS) and that
the CORE and AMPbd unfold as a single domain, suggesting positive coupling
between them. This result shows that coupling interactions are present in WT.
In Chapter 4, the impact of local unfolding on binding affinity was studied using
isothermal titration calorimetry (ITC). Binding experiments were carried out in the
presence of saturating conditions of the non-hydrolyzable inhibitor Ap5A. It was
found that local unfolding promoted by Gly mutations decreases binding affinity to
different extents. This effect can be explained by the modulation of the ensemble
of states, whereby the population of low-affinity state is increased. Moreover, even
though the LID was removed, AK could marginally bind Ap5A.
In Chapter 5, the catalytic activity of the different AK constructions were
characterized in the direction of the formation of ATP and AMP (reverse reaction)
under saturating concentrations of substrates. It was found that local unfolding
can regulate the catalytic rate (kcat). Single mutations in the LID (V135G and
V142G) do not change kcat between 15 and 40 . However, two simultaneous
mutations in the LID (V134G/V142G) decrease kcat. On the other hand, mutations
in the CORE (A73G) and AMPbd (A55G) domains increase kcat. Interestingly, the
kcat of A73G is increased to the value observed in A55G, when V142G is present.
In general, these results can be explained by the redistribution of the ensemble
induced by local unfolding, changes in the release rate of Mg2+.ATP, and binding
affinity of Mg2+.ADP associated with the LID.
In Chapter 6, the redistribution of the ensemble induced by local unfolding was
investigated by comparing the probabilities of the folded state in WT and V142G
8
in the absence of ligand at 37 by combining HX-NMR and ITC techniques.
This method was previously developed in our lab to determine the stability of
domains not detected by HX-NMR, as is the case for the LID and AMPbd that
have the amide hydrogens completely exchanged to deuterium during the sample
preparation. The results show that the LID and AMPbd are very flexible and
the CORE is the most stable domain. According to this method, the folded state
in WT represents 90% of the ensemble. On the other hand, V142G decreases
the population of the folded state to 43%. Although the determined probability
values in this Chapter differ from those values determined by DSC (specially those
associated with V142G), the conclusions are the same: Gly mutations induced
local unfolding that, in turn, caused the redistribution of the ensemble.
Finally, in Chapter 7, the principal findings were discussed, future directions
were outlined and experiments were proposed. A final remark: unless indicated,
plots and simulations in this dissertation were generated with the R programming
language [73].
9
Mg2+ · ATP + AMPforward−−−−−−−−reverse
Mg2+ · ADP + ADP
Figure 1.1: E. coli AK: domains and catalytic scheme. This figure was made usingthe 4AKE.pdb file [17] and PyMOL Molecular Graphics System Version 1.4.1.Schrodinger, LLC
10
Figure 1.2: Local unfolding promoted by V142G affects neighboring residues. 1H-15N HSQC NMR spectra of WT (black) and V142G (red) at 21 C [9]
11
(a) 1H-15N HSQC NMR spectra of WT (black) andV142G (red) at 33 [9]
(b) Propagation of mutational effects at 33 [9]
Figure 1.3: V142G can destabilize the entire LID domain. (a) Local unfoldingincreases with temperature. (b) Affected residues are in yellow.
12
Figure 1.4: Mutational effects introduced by one mutation do not affect the crys-tallographic structure. Alignment of WT and V148G from position A (red) andposition B (black) within the asymmetric unit (ASU). The RMSD values betweenWT and V148G from the same position are less than the RMSD between twocopies of the same construct inside the ASU [9].
Figure 1.5: Modulation of binding affinity at different temperatures [9].
13
Chapter 2
Materials and methods of AK
preparation
2.1 Selection of entropy enhancing glycine mu-
tations
Mutations in the three domains of AK that satisfy our mutational strategy were
selected: V135G, V142G in the LID, A55G in the AMPbd and A73G in the
CORE domain, see Fig. 2.1. In addition to these single mutants, we also se-
lected double mutations such as V135G/V142G, V135G/V148G, V142G/V148G
and A73G/V142G. In addition to the above mutants, the entire LID domain was
removed and replaced with a flexible linker (LIDLESS) in order to investigate the
coupling between the LID and the CORE-AMPbd domains. The reasons for selec-
tion of double mutants were to determine whether AK can function having the LID
severely unfolded, and whether these effects on function are position dependent.
The purposes of LIDLESS characterization were to dissect the coupling between
the LID and CORE-AMPbd and to determine whether the CORE and AMPbd
domains unfold as a single domain.
Target residues to be mutated were selected after close inspection of the apo,
4AKE.pdb [17], and holo, 1AKE.pdb [18], crystallographic structures. Val to Gly
14
mutations were expected to produce the largest conformational entropy change be-
cause a β-branched side chain is effectively reduced to one hydrogen. On the other
hand, Ala to Gly mutation should promote a smaller change in conformational en-
tropy since a methyl group is replaced. Consistent with this expectation, D’aquino
and colleagues computationally determined the unfolding conformational entropy
changes for 19 residues [20]. According to their results, Val to Gly mutation in-
creases the conformational entropy by 2.9 cal/mol*K and Ala to Gly substitution
by 2.4 cal/mol*K.
2.2 Site directed mutagenesis
AK WT plasmid (DNA 2.0, Menlo Park, CA) was optimized for E. coli expression
and then synthesized and inserted into the pJ414 bacterial expression vector. This
vector was designed with a IPTG-inducible T7 promoter and no affinity tag codons.
WT plasmid was used as template to obtain single and double mutations through
site directed mutagenesis employing polymerase chain reactions (PCR) with Phu-
sion High-Fidelity DNA Polymerase (NEB, Ipswich, MA) and specifically designed
primers. Complimentary primers, synthesized by IDT (Coralville,IA) had between
15 and 20 nucleotides on each side of the targeted mutation. This sequence length
ensures selectivity and an a effective Tm of the primers. Tm should be within
the range of 70 to 80 for best results. Reaction setup that includes 3% DMSO
and thermocycling conditions were performed according to the PCR Phusion DNA
Polymerase protocol from NEB. When the thermocycling steps were done, diges-
tion of parental plasmid was achieved by the addition of 2 !l of DpnI for every 10
!l of PCR product and posterior incubation of the product for at least 4 hours at
37 . The digested product was then transformed into homemade DH5 competent
cells. Transformed cells were spread on LB agar plates with 100 !g/ml ampi-
cillin. Plates were incubated for 18-24 hours at 37 . Then, single colonies were
15
gathered for plasmid extraction. Plasmid concentration was increased by using
a GeneJET Plasmid Miniprep Kit (Thermo Fisher Scientific, Rockville, MD) for
subsequent plasmid sequence verification and protein expression. Plasmids were
stored in aliquots at -20 .
2.3 LIDLESS plasmid construction
Amino acids 121-160 corresponding to the LID domain were replaced by the flexible
linker GTGGSGGS, which is composed of eight residues. Threonine and serine
were in the linker to make it soluble without adding bulkier side chains. LIDLESS
plasmid was made from WT plasmid. Complimentary primers were used on the
WT plasmid to remove the LID codons and to add one KpnI and one BamHI
restriction site. A duplex DNA oligomer, which carried the codon sequence for the
flexible linker, replaced the sequence of the LID.
Phosphates were added to the 5’-ends of the duplex before ligation. The primers
and duplex were synthesized by IDT. Deletion of the LID was done using PCR
with Phusion High-Fidelity DNA Polymerase following the corresponding proto-
col. The reaction product was inoculated with 2!l of DpnI for every 10uL to digest
the parental plasmid. The solution was then incubated for 4 hours at 37 . Af-
ter incubation, the plasmid was purified with the GeneJet PCR purification kit.
Afterwards, 47 !l of purified PCR solution was mixed with 2 !l of KpNI, 2 !l
BamHI and 5 !l of 10xCutSmart buffer. This step was necessary to make sticky
ends for ligation. The restriction enzymes and related buffers were from NEB. The
solution was incubated at 37 for at least 1 hour to achieve complete digestion.
Agarose electrophoresis gel was carried out to check the plasmid length. The gel
was made with 40 ml 1xTAE buffer and 0.3 gr of UltraPure"Agarose 16500 Invit-
rogen (Thermo Fisher Scientific). After microwaving the agarose solution for two
minutes, 1 !l of ethidium bromide was added. The ladder solution was made by
16
mixing 1.5 l of 2-Log-DNA marker (NEB) with 5 l of nucleic acid sample buffer
5x (Bio-Rad, Hercules, CA). The plasmid solution was made by mixing 14 l of
nucleic acid sample buffer 5x with 56 l of purified solution for ligation. The gel
was then inspected using UV light in a dark room, wearing proper UV glasses. The
target plasmid was removed from the gel using a clean sterile razor. The plasmid
was extracted from the gel using the GeneJET gel extraction kit.
Addition of 5’-phosphates to the duplex DNA oligomer for subsequent ligation
was achieved by mixing 3 l of duplex solution (50uM), 1 l of T4 Polynuclotide
Kinase (NEB), 10x T4 ligase buffer, 8 l of PEG 8000 (30%) and 33 l of ddH20.
The solution was incubated for 12 hours at 37 !. Ligation between the duplex
DNA oligomer and the cut plasmid was carried out by T4 DNA ligase (NEB).
The concentration of the duplex was three times the extracted concentration of
PCR product. The ligation solution was left at room temperature for 1 hour.
The ligated plasmid was transformed into homemade DH5 competent cells [19].
Transformed cells were spread on LB agar plates with 100 g/ml ampicillin. Plates
were incubated for 18-24 hours at 37!. Afterwards, single colonies were collected
for plasmid extraction. Plasmid concentration was increased by using a GeneJET
Plasmid Miniprep Kit for subsequent plasmid sequence verification and protein
expression. Plasmids were stored in aliquots at -20!.
2.4 Protein expression,purification, and storage
Rosetta"2(DE3)pLysS Singles"competent cells Novagen (EMD millipore, Biller-
ica, MA) were transformed with AK plasmids and plated on LB plates with
100ug/mL ampicillin and incubated for 18-24 hours at 37!. A single colony was
gathered and inoculated into 50 mL 2xYT medium with 60 g/mL ampicillin and
grown for 8 hours at 37! in an incubator shaker at 250 rpm. 5 ml of grown cells
were inoculated for every liter of 2xYT medium containing 60 g/ml. Cells grew
17
at 37 in an incubator shaker at 250 rpm until they reached an OD between 0.6
and 0.8. Then, the culture was induced by 1mM IPTG and continued growing in
the incubator shaker for 5 hours. The pellets were collected and washed with soni-
cation buffer (50 mM Tris, 0.1 NaCl, 2mM EDTA, 2mM DTT, pH 8.0) and stored
at -80 . Sonication was carried out using sonication buffer and protease inhibitor
cocktail (Sigma-Aldrich, St.Louis, MO) in a 4 room. Cell lysate was centrifuged
at 30,000g at 4 for 1 hour. The supernatant containing AK was collected and
filtered several times with 0.2 !m sterile filters (Nalgene). The next purification
steps were taken from [9] and performed using FPLC. The supernatant was diluted
3x with diluting buffer (10mM Tris, 1 mM DTT, pH 8.0) and then loaded into a
column containing Cibacron Blue F3GA dye (Bio-Rad) suspended in buffer A-blue
(50 mM Tris, 0.1 mM EDTA, 1 mM DTT, pH 7.5). AK was gathered through a
linear gradient elution employing buffer A-blue and B-blue (50 mM Tris, 0.1 mM
EDTA, 1 mM DTT, 2M NaCl, pH 7.5). Fraction collections with the highest AK
concentration were selected. Concentrations were determined by measuring the
absorbance at 277 nm. The extinction coefficient (ε) used for WT, single and dou-
ble mutants was 13750 M-1cm-1 and for LIDLESS was 11653 M-1cm-1. Collections
purity was examined on SDS-PAGE. The protein solution was dialyzed against
buffer A (20 mM Tris, 0.1 mM EDTA, 1mM DTT, pH 8.0) for 24 hours at 4 .
Dialyzed AK was then loaded into a Resource Q resin suspended in buffer A. AK
was collected using a linear gradient elution by mixing buffer A and buffer B (20
mM Tris, 0.1 mM EDTA, 1mM DTT, 0.3 M NaCl, pH 8.0). Fraction collections
were monitored at 277 nm and the ones with the highest concentration were gath-
ered and purity was examined on 12% SDS SDS-PAGE. Finally, AK was dialyzed
against calorimetric buffer (60 mM PIPES, 1 mM EDTA, pH 7.85) for 24 hours.
This step was repeated three times. PIPES buffer was acquired from AmericanBio
Inc., Natick, MA. and EDTA from Sigma-Aldrich.
18
(a) Apo state, view 1 (b) Apo state, view 2
(c) Holo state, view 1 (d) Holo state, view 2
Figure 2.1: Selected Gly mutations on uncharged solvent exposed residues. Theseresidues are far from the active site and have no contact with the ligand. Therefore,our mutational strategy is satisfied both in the apo,(a) and (b), and in the holostate, (c) and (d). This figure was made using the 4AKE.pdb [17] and 1AKE.pdb[18] files and PyMOL Molecular Graphics System Version 1.4.1, Schrodinger, LLC.Mutations are shown in red. The active site is approximated by the location ofAp5A (brown).
19
Figure 2.2: LIDLESS plasmid construction.
20
Chapter 3
Calorimetric determination of
interdomain interactions and
stability of AK constructs
3.1 Abstract
NMR hydrogen exchange experiments demonstrated that proteins are flexible en-
tities and exist as an ensemble of conformational states [21]. This technique was
also used to determine the local and global stability of AK at 19 [12]. The results
show that the CORE is the most stable domain of the enzyme. In addition, it has
been suggested that the three domains folds uncooperatively [12]. In other words,
that there is no interdomain (coupling) interactions between domains. However,
our differential scanning calorimetry (DSC) data show that the LID and CORE-
AMPbd are negatively coupled and the coupling is temperature dependent. The
coupling is zero at about 30 and positive at lower temperature. Most impor-
tantly, DSC also allowed us to observed the effects of local unfolding regulation,
promoted by mutations, on the subdomain stabilities, and consequently, to deter-
mine the redistribution of the conformational ensemble.
21
3.2 Introduction
Probabilities of conformational states have been previously determined using differ-
ent techniques such as HX-NMR [21, 22], CD combined with ITC [9] and residual
dipolar coupling (RDC) [23]. In this chapter, we investigated the modulation of
the conformational ensemble promoted by local unfolding regulation. For that
purpose, DSC experiments were performed on WT, A55G, A73G ,V135G,V142,
A73G/V142G, V135G/V142G and on LIDLESS. DSC is a thermodynamic tech-
nique that measures the apparent molar heat capacity (CP ) of proteins as temper-
ature is changed. Thermodynamic parameters such as Tm and ∆HvH of transitions
can be obtained running only one experiment. In addition, ∆CP can be obtained
by measuring ∆HvH and Tm at different pH conditions. Subsequently, the partition
function (Q) and conformational states probabilities can be calculated. Modula-
tion of the conformational ensemble promoted by mutations and LID deletion was
determined and the probabilities of the folded state between WT and mutants were
compared at 37 . The coupling between the LID and CORE-AMPbd was also
studied by comparing the unfolding transition of LIDLESS with those observed in
the other constructs.
3.3 Materials and methods
3.3.1 Protein preparation
Thermal unfolding experiments were carried out onWT, A55G, A73G ,V135G,V142,
A73G/V142G, V135G/V142G and on LIDLESS. Constructs were expressed and
purified according to protocols described in Chapter 2. Experiments were per-
formed with freshly prepared AK solutions dialyzed against calorimetric buffer
(60 mM PIPES, 1 mM EDTA pH 7.85). Protein concentrations were measured
with a UV spectrometer at 277 nm using ε = 13750 M−1cm−1 for WT, single and
22
double mutants and ε = 11653 M−1cm−1 for LIDLESS. Afterwards, the protein
concentration was corrected by multiplying the n value obtained from isothermal
titration calorimetry (ITC) experiments run at 25 by the protein concentration
previously measured (i.e., [AK]corrected = n[AK]UV). The inhibitor Ap5A [18] was
used as ligand in ITC experiments. DSC and ITC runs used protein solution from
the same preparation to minimize random errors. Protein concentrations of 20 !M
(≈ 0.5 mg/ml) were used in all the experiments. To determine ∆CP s accurately,
pH was lowered to pH 7.2. In this way, we observed change in Tm and ∆Hm. When
pH was lower than 7.2, proteins aggregated at temperatures higher than Tm. ITC
experiments were run according to details given in Chapter 4.
3.3.2 DSC experimental design
The heat capacity (CP ) as a function of temperature was measured by a high preci-
sion differential scanning microcalorimeter MicroCal VP-DSC (Malvern, Westbor-
ough, MA). The running parameters were selected as follows: starting temperature
= 10 ; final temperature = 80 ; scan rate = 60 /h; prescan thermostat= 15
min; postscan = 0 min; filtering period = 20 seconds and FB Mode/Gain = none.
Protein solution and calorimetric buffer were degassed and loaded into the sample
and reference cells, avoiding bubbles as much as possible. The cells were cleaned
before each experiment. For this purpose, nitric acid (70%) was left in the cells for
2 hours at 80 . Then, the temperature was lowered to 30 and the nitric acid
was discarded. Subsequently, the cells were cleaned up with filtered contrad 70
(1x) and rinsed with ddH2O. CP was processed at temperatures higher than 15
to eliminate perturbations associated with the instrument equilibration. It was
empirically observed that starting temperatures lower than 10 produced noisy
data. To determined the extent of reversibility, protein the sample was reheated
(10-80 ). Then, the unfolding profile areas of the two scans were compared. The
23
reversibility was also tested by heating the sample 3 more than the melting tem-
perature of the last transition. The sample was cooled down and then reheated
again. According to the first method, the extent of reversibility was between 72%
(A73G/V142G) and 82% (WT). However, the second method showed that unfold-
ing is highly reversible and that irreversibility arises because of high temperature
effects, [24, 25, 26], see Appendix 4.
3.3.3 Data analysis
To investigate the modulation of conformational ensemble promoted by entropy en-
hancing mutations, the probabilities of states for every construct were determined.
In general, the probability that a protein visits state i is given by
Pi =e−
∆GiRT
Q(3.1)
with the partition function defined as :
Q =n
∑
i=1
e−∆GiRT (3.2)
where ∆Gi is the stability of the state i, whereby the folded state is the reference
state (∆G1 = 0):
∆Gi = −RTln(Ki) = ∆Hi − T∆Si (3.3)
∆Hi is the enthalpy associated with the state i and it is described by the van’t
Hoff equation:
∆Hi = RT 2dlnKi
dT= ∆HvH,i +∆CP,i(T − Tm,i) (3.4)
∆Si is the entropy of the state i and it is expressed as:
∆Si =∆HvH,i
Tm,i
+∆CP,ilnT
Tm,i
(3.5)
Using the last two equations, ∆Gi can be expanded to the well-known Gibbs-
Helmholtz equation:
∆Gi = ∆HvH,i(1−T
Tm,i
) + ∆CP,i(T − Tm,i − lnT
Tm,i
) (3.6)
24
T and Tm are absolute temperatures. ∆CP s are assumed to be constant over the
temperature range used [27]. Stabilities and probabilities were calculated by ob-
taining ∆HvH,i, ∆CP,i and Tm,i from the transition excess heat capacity (〈∆CP,tr〉)
profiles. 〈∆CP,tr〉 was obtained by subtracting the sigmoidal (i.e. progressive)
baseline CP,bl from the apparent molar heat capacity (CP ), thus:
〈∆CP,tr〉 = CP − CP,bl (3.7)
where CP,bl was calculated according to:
CP,bl = (1− α)CP,N + αCP,U (3.8)
α is the probability of the unfolded state calculated following the method described
in [32] and [33]. CP,N and CP,U are the heat capacity of the native and unfolded
states respectively. Although equation 3.8 is only mathematically correct for a
two-state transition [27], it was also used for non-two-state transitions because the
progressive baseline was the method that produced the less perturbed 〈∆CP,tr〉.
Finally, the 〈∆CP,tr〉 profile is fitted according to [27]:
〈∆CP,tr〉 =n
∑
i=1
∆HidPi
dT(3.9)
To obtain thermodynamic parameters from 〈∆CP,tr〉 profiles of WT and mu-
tants (excepting V135G/V142G), a sequential three-state model was proposed
whereby the coupling parameter, φ, accounts for the interdomain interaction, and
therefore communication, between the LID and CORE-AMPbd, see Eq. 3.16 and
related reaction scheme. The three-state model was based on the observation that
the LID unfolds cooperatively [9], see Fig. 1.3 and that the CORE and AMPbd un-
folding as a single domain, see Fig. 3.4. Interaction between the LID and the rest
of the enzyme was evident when the removal of the LID (LIDLESS) decreased the
stability of the CORE-AMPbd, see Fig. 3.4. In addition, it was observed that in-
terdomain interactions are present although the LID is unfolded (V135G/V142G),
25
see Fig. 3.6. Close inspection of 〈∆CP,tr〉 profiles of WT and single mutants indi-
cates that thermal unfolding of the LID is not accompanied simultaneously by the
break of interdomain interactions. Actually, they are still acting on the CORE-
AMPbd as shown by thermal unfolding of V135G/V142G. Therefore, φ was placed
on the transition associated with the CORE-AMPbd unfolding. Following these
observations, unfolding of LIDLESS was analyzed using a two-state model, see Eq.
3.10. Unfolding of V135G/V142G was also characterized with a two-state model
incluiding φ, see Eq. 3.14.
In general, coupling interactions can contribute to the stabilization or destabi-
lization of associated domains when ∆Gφ = −RTlnφ 6= 0. For the case ∆Gφ > 0,
it is energetically more favorable to unfold one of the interacting domains when
the other is unfolded or removed. This situation could arise when the interface
between domains is composed of two complementary hydrophobic surfaces that in-
teract energetically more favorable with each other than with solvent [13]. On the
other hand, ∆Gφ < 0 means that unfolding or removal of one domain would make
the other more stable. This is the case when interfaces would prefer to interact
with solvent rather than with each other. This situation could arise for a specific
arrangement of charge residues or for complementary hydrophobic surfaces at low
temperature [13].
It has been shown that thermodynamic parameters can be estimated using the
accessible surface areas [34]. Since the interface area associated with φ is assumed
to be small, and therefore the accessible surfaces areas, compared with those of
the LID and CORE-AMPbd domain; ∆CP,φ was assumed to be zero.
The thermal unfolding of LIDLESS was analyzed using the following two-state
reaction scheme :
FCORE-AMPbdKCA−−−−−−−−−−−−−−−−−− UCORE-AMPbd
26
which gives the partition function:
QLIDLESS = 1 +KCA (3.10)
where KCA is the equilibrium constant related to the unfolding of the CORE-
AMPbd. The associated 〈∆CP,tr〉 function was determined by using Eq. 3.10 into
Eq. 3.9, giving:
〈∆CP,tr〉 =1
RT 2[PU(1− PU)∆H
2CA] (3.11)
PU is the related probability of the unfolded state. The effect of the flexible linker
of the stability of LIDLESS is corrected according to the expression:
Tm,New =∆HvH
∆HvH/Tm +∆Slinker
(3.12)
with
∆Slinker = −Rln[(3
2πNL2)3/2
1
6πd3] (3.13)
where d is the distance between the first and last residues of the loop, N is the
number of residues of the loop, and L is the statistical length of an amino acid,
see [35]. For our case, d=5.6 a, N=8 and L=3.8 a.
Since unfolding of V135G/V142G showed coupling effects between the LID and
CORE-AMPbd domains even though the LID is unfolded (LU). The unfolding
reaction was modeled according to a two-state model that includes φ:
LUφKCA−−−−−−−−−−−−−−−− U
with the partition function:
QV 135G/V 142G = 1 + φKCA (3.14)
and:
〈∆CP,tr〉 =1
RT 2[PU(1− PU)(∆Hφ +∆HCA)
2] (3.15)
27
It was determined that the folded state of AK is composed of compact and
extended coexisting conformations. The compact conformation is populated even
in the absence of substrates [15]. In our model, it is assumed that these two con-
formations have the same stability and therefore they are treated as one single
state, the folded state. In addition, it was shown that V142G and V148G muta-
tions promote marginal perturbations in the NMR spectra of unligated and crystal
structure of ligated AK respectively [9], see Chapter 1. Therefore, the folded state
was assumed to be conserved by mutants.
WT and mutants showing two transitions were studied with the sequential
reaction:
FKLID−−−−−−−−−−−−−−−−−− LU
φKCA−−−−−−−−−−−−−−−− U
giving rise to the partition function:
Q = 1 +KLID +KLIDφKCA (3.16)
and:
〈∆CP,tr〉 =1
RT 2[ PF (1− PF )∆H
2LID + 2PFPU∆HLID(∆Hφ +∆HCA) (3.17)
+PU(1− PU)(∆Hφ +∆HCA)2]
PF and PU are the probabilities of the folded and unfolded states calculated from
Q, see Eq. 3.16. The ∆CP s associated with KLID and KCA were set to zero
to obtain 〈∆CP,tr〉 because progressive baseline subtraction makes CP,N and CP,U
equal to zero. Since ∆Cp was assumed to be constant [27], it was taken as the slope
of the linear function of the plot ∆Hm vs Tm. Therefore, ∆CP,CA was determined
by calculating the slope associated to the ∆Hm and Tm values obtained at pH of
7.2 and 7.85, see Fig. 3.8. ∆CP,LID was the calculated slope related to the ∆Hm
and Tm values from the thermal characterization of the LID from WT, V135G and
28
V142G, see Fig. 3.9. As mentioned above, ∆Cp,φ was assumed to be zero in our
calculations. Our experimental data were analyzed using software written in our
lab, see Appendices 1 and 2.
3.4 Results and discussion
3.4.1 The CORE-AMPbd unfolds as a single domain and
it is coupled to the LID
The effect of the flexible linker on the stability of LIDLESS was corrected accord-
ing to Eq. 3.12, see Fig. 3.3. Comparison between the heat capacity function of
WT and the corrected one of LIDLESS is shown in Fig. 3.4. It reveals that the
CORE-AMPbd region unfolds as a cooperative domain, as previously suggested
by NMR experiments, see Fig. 1.3. This result also suggests that the CORE and
AMPbd are positively (or favorably) coupled. In addition, the apparent Tm is
shifted downwards by 2.5 when the LID is removed, indicating that the LID and
CORE-AMPbd are also positively coupled. 〈∆CP,tr〉 of WT exhibits an asymmet-
ric shape, showing that at least one other transition is present. The presence of
additional state(s) was also confirmed by the van’t Hoff to calorimetric enthalpy ra-
tio (∆Hcal/∆HvH = 1.15), see Appendix 3. On the other hand, thermal unfolding
of LIDLESS follows a two-state mechanism (∆Hcal/∆HvH = 1.00). The thermal
unfolding is characterized by an enthalpy change (∆HCA) of 109.1 kcal/mol and a
melting temperature (Tm,CA) of 53.4 . 〈∆CP,tr〉 of WT was fitted according to
Eq. 3.17 using the ∆HCA and Tm,CA obtained from LIDLESS. Unfolding of the
LID was described by a ∆HvH,LID of 43.6 kcal/mol11, Tm,LID of 51.0 , ∆HvH,φ
of 22.6 kcal/mol and Tm,φ of 67.8 . ∆CP,LID and ∆CP,CA were determined to be
0.4 and 2.7 kcal/mol*K respectively for WT and mutants, see the Data analysis
section. These results indicate that the LID and CORE-AMPbd are positively
29
coupled at temperatures lower than 67.8 , see Fig. 3.11. The coupling interac-
tion between the LID and CORE as well as the stabilities of AK domains also were
studied through HX-NMR [12]. Rundqvist and colleagues showed that the CORE
is the most stable region and that LID and AMPbd exhibit low stability (exchange
of amide protons in the LID and AMPbd were too fast to be detected). They con-
cluded that the stabilities of the LID and AMPbd do not affect the stability of the
CORE. However, our thermal unfolding analysis of WT and LIDLESS revealed the
presence of coupling between the LID and CORE-AMPbd regions. Furthermore,
unfolding of the CORE and AMPbd as a single domain suggests the presence of
positive coupling. Coupling characterization in AK can be further investigated by
removing the AMPbd as well as the LID and AMPbd simultaneously.
3.4.2 Single and double mutants promote local unfolding
It is clearly observed that our entropy enhancing mutations promote local unfolding
and their impact is higher in the LID than in the CORE, see Fig. 3.5 and 3.6.
Direct evidence of local unfolding regulation is given by the downward shift of
Tm of the LID transition promoted by V135G and V142G. Moreover, A55G and
A73G also destabilize the CORE but not to the same extent as Gly mutations
do to the LID. Destabilizing effects of mutations are relative to the stability of
the affected region. In other words, the more stable the region, the less impact
on stability mutations will have. Moreover, mutations in the CORE-AMPbd have
no appreciable impact, if any, on the stability of the LID, Fig. 3.5. The reverse
is also valid. Mutations in the LID do not perturb the stability of the CORE-
AMPbd, see Fig. 3.7, and Table 3.1. Importantly, these results are not predicated
on a communicating pathway between domains. Only stabilities and coupling
interactions are necessary to explain our DSC data.
30
3.4.3 Coupling interactions are still present even though
the LID is unfolded
V135G, V142G, V135G/V142G and A73G/V142G reduce the unfolding transition
area associated with the CORE-AMPbd by the same extent. However, the center
peak corresponding to the CORE-AMPbd transition of WT, single and double
mutants present small but significant differences in Tm, meaning that coupling
interactions are still present. Fitted values, Table 3.1, that characterized the un-
folding profiles of WT, V135G, V142G and V135G/V142G in Fig. 3.6 show how
one mutation in the LID such is enough to reduce the coupling enthalpy change by
≈ 19 kcal/mol. Moreover, the coupling Tm is increase to be temepratures higher
than 130 . When two mutations are present in the LID, the enthalpy loss is 14.4
kcal/mol and the coupling Tm is decreased to 102.5 . This result suggests that
local unfolding can induce compensatory effects. Interestingly, the coupling is only
perturbed by mutations in the LID (Fig. 3.6) but not by those in the CORE or
AMPbd (Fig. 3.5), probably because A55G and A73G are distal mutations to the
LID-CORE interface.
3.4.4 Local unfolding mechanism for stability change
Thermodynamic parameters were obtained from DSC, Table 3.1. ∆CP,LID and
∆CP,CA were calculated according to the Data analysis section, see Fig. 3.8 and
3.9. ∆CP,φ was assumed to be zero. Stabilities were calculated at 37 according
to the Gibs-Helmholtz equation, see Eq. 3.3. Modulation of thermal stabilities
of constructs are shown in Fig. 3.10. The total stability of WT is 8.1 kcal/mol.
∆∆GTotal,37 indicates the degree of mutational effects on stability. Gly mutations
in a specific domain promote similar effects. A55G and A73G decrease the global
stability by 0.5 and 0.6 kcal/mol respectively. However, V135G and V142G de-
crease stability by 2.6 and 2.8 kcal/mol respectively. These results can be explained
31
by the increased conformational flexibility produced by Val to Gly substitutions.
A73G/V142G decreased stability by 2.8 kcal/mol. This value shows that muta-
tional effects are not additive. The stability of the CORE-AMPbd (LIDLESS) was
4.3 kcal/mol, 1.4 kcal/mol lower than the stability of V135G/V142G. The differ-
ence is the consequence of the positive coupling interaction between the LID and
CORE-AMPbd.
3.4.5 Local unfolding modulates the conformational en-
semble
Probabilities of states were calculated according to Eq. 3.1 using the thermody-
namic values obtained from DSC, see Table 3.1. Probabilities of states were plotted
(Fig. 3.12) and the folded state probabilities were calculated at 37 and then com-
pared with those of the mutants, see Fig. 3.13. V135G/V142G and LIDLESS are
two special cases. In the former, unfolding of the LID was not detected by the
calorimeter at the range of the experimental scan (10 to 80 ), Fig 3.6, and in the
latter, LIDLESS has a different native state because the LID was removed. Un-
folding of V135G/V142G is computationally explored in the Chapter 4. Changes
of probabilities of the folded state show clearly how local unfolding promoted by
Gly mutations modulates the conformational ensemble. In WT, A55G and A73G,
95% of the total enzyme is folded at 37 . The population of the folded state goes
down to 54%, 71% and 75% in V135G, V142G and A73G/V142G respectively.
According to the model used in this chapter, the population of the folded state is
zero in V135G/V142G.
3.5 Conclusions
Local unfolding promoted by Gly mutations modulates the conformational ensem-
ble. At 37 , the folded state population represents 95% of the ensemble. While
32
the other 5% is populated by the locally unfolded state (LU), defined as having
the LID unfolded. AK unfolds following a three-state process. The LID is the
less stable domain. On the other hand, the CORE-AMPbd, which unfold as a
single domain, is the most stable region of the enzyme. In addition, the LID and
CORE-AMPbd are positively coupled. In the next chapters, we will investigate
the impact of local unfolding in protein function.
33
Figure 3.1: Mutation positions in AK used for DSC experiments shown in red.Double mutants V135G/V142G and A73G/V142G, as well as LIDLESS, were alsotested.
34
(a) LIDLESS
(b) WT
Figure 3.2: Thermal unfolding simulation of the CORE-AMPbd and the LID basedon Eq. 3.17. Parameters used in the simulations: ∆HvH,LID=43.0 kcal/mol,∆HvH,CA= 109.0 kcal/mol, ∆HvH,φ=22.0 kcal/mol, Tm,φ=68 , ∆CP,CA =∆CP,LID = ∆CP,φ= 0.0 kcal/mol*K. In (a), Tm,LID = 51.0; Tm,CA was set to 53.4 (black), 52.4 (green) and 51.4 (blue). In (b), Tm,CA = 53.4 . Tm,LID was setto 51.0 (black), 41.0 (orange) and 36.0 (dark red). *CA = CORE-AMPbd
35
Figure 3.3: Corrected 〈∆CP,tr〉 of LIDLESS upon removing the stability effects ofthe flexible linker, see Eq. 3.12. Tm is decreased by 7.2 .
36
Figure 3.4: Comparison of 〈∆CP,tr〉 profiles of WT and LIDLESS. Decreased Tmof LIDLESS is clearly evident.
37
Figure 3.5: 〈∆CP,tr〉 profiles of WT, A55G and A73G. Single mutants exhibit asmall decrease in Tm as compared to WT.
38
Figure 3.6: 〈∆CP,tr〉 profiles of WT, V135G, V142G and V135G/V142G. Theunfolding of the LID is observed in single mutants (see small unfolding transitions)but not in the double mutant. Mutants present small decrease in Tm of the CORE-AMPbd as compared to WT.
39
Figure 3.7: 〈∆CP,tr〉 profiles of WT, A73G, V142G and A73G/V142G. All mutantsclearly demonstrate decrease in Tm.
40
Figure 3.8: ∆CP associated with the unfolding of the CORE-AMPbd (CA). Calcu-lated from the thermal unfolding characterization of LIDLESS at two pH values.Itis assumed that the flexible linker has no effect on ∆CP,CA. *Estimated valuedetermined with COREX [38], based on accessible surface areas.
41
Figure 3.9: ∆CP associated with the unfolding of the LID. Calculated from the LIDunfolding characterization of WT, V135G and V142G, see Table 3.1. *Estimatedvalue determined with COREX [38], based on accessible surface areas.
42
AK Tm,LID ∆HvH,LID ∆CP,LID Tm,φ ∆HvH,φ Tm,CA∗ ∆HvH,CA∗ ∆CP,CA∗ ∆GTotal,37 ∆∆GTotal,37
Construct (kcal/mol) (kcal/mol ∗ K) (kcal/mol) (kcal/mol) (kcal/mol ∗ K) (kcal/mol) (kcal/mol)
LIDLESS NA NA NA NA NA 53.4!0.1 109.1!0.1 2.7!0.4 4.3!0.2 -3.8!0.3
WT 51.0!0.1 43.6!0.7 0.4!0.1 67.8!0.2 22.6!0.5 53.4!0.1 109.1!0.1 2.7!0.4 8.1!0.2 0.0!0.0
A55G 51.0!0.1 43.6!0.7 0.4!0.1 67.8!0.2 22.6!0.5 52.0!0.1 103.0!0.1 2.7!0.4 7.6!0.2 -0.5!0.3
A73G 51.0!0.1 43.6!0.7 0.4!0.1 67.8!0.2 22.6!0.5 51.2!0.1 105.5!0.1 2.7!0.4 7.5!0.2 -0.6!0.3
V135G 37.8!0.1 38.0!0.4 0.4!0.1 163.0!0.8 4.0!0.1 53.4!0.1 109.1!0.1 2.7!0.4 5.6!0.2 -2.6!0.3
V142G 41.3!0.1 41.0!0.7 0.4!0.1 133.3!0.9 2.0!0.1 53.4!0.1 109.1!0.1 2.7!0.4 5.3!0.2 -2.8!0.3
A73G/V142G 42.2!0.3 42.0!1.0 0.4!0.1 109.9!2.0 4.5!0.2 51.2!0.1 105.5!0.1 2.7!0.4 5.3!0.2 -2.8!0.3
V135G/V142G NA NA NA 102.5!2.2 8.2!0.3 53.4!0.1 109.1!0.1 2.7!0.4 5.7!0.2 -2.4!0.3
Table 3.1: Summary of the thermodynamics parameters obtained from DSC. ∆GTotal = ∆GCA + ∆GLID + ∆Gφ. ∆CP,φ wasfixed to zero. Errors are from three replicates. NA = Not aplicable. *CA = CORE-AMPbd.
43
Affected ∆∆GA55G ∆∆GA73G ∆∆GV 135G ∆∆GV 142G ∆∆GA73G/V 142G ∆∆GV 135G/V 142G
Domain (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol)
LID 0.0 0.1 0.0 0.1 -1.7 0.1 -1.2 0.1 -1.1 0.1 -1.8 0.1
*CA -0.5 0.2 -0.6 0.2 0.0 0.3 0.0 0.3 -0.6 0.2 0.0 0.3
φ 0.0 0.1 0.0 0.1 -0.9 0.1 -1.6 0.1 -1.2 0.1 -0.6 0.1
∆∆GTotal -0.5 0.3 -0.6 0.3 -2.6 0.3 -2.8 0.3 -2.8 0.3 -2.4 0.3
Table 3.2: Stability perturbation of AK domains promoted by Gly mutations.∆∆G were calculated at 37 using values from Table 3.1. Errors in ∆∆G weredetermined by propagation of errors associated with ∆G.*CA = CORE-AMPbd
44
(a) LIDLESS (b) WT
(c) A55G (d) A73G
(e) V135G (f) V142G
(g) A73G/V142G (h) V135G/V142G
Figure 3.10: Thermal stabilities calculated according to thermodynamic parame-ters from Table 3.1. ∆GTotal = ∆GCORE−AMPbd + ∆GLID + ∆Gφ
45
Figure 3.11: Coupling interaction (φ) between the LID and CORE-AMPbd in WTat 37 , based on Fig. 3.10 (b)
46
(a) LIDLESS (b) WT
(c) A55G (d) A73G
(e) V135G (f) V142G
(g) A73G/V142G (h) V135G/V142G
Figure 3.12: Theoretical state probabilities vs temperature plots determined usingvalues from Table 3.1 and Eq. 3.1. Since the unfolding of the LID in V135G/V142Gwas not detected by DSC experiments (h), it was assumed that the folded state wasnot populated at the temperature range of the experiment. States probabilities ofthe double mutant were calculated using to Eq. 3.14.
47
Figure 3.13: Probabilities of the folded state of different constructs calculated at37 using values from Table 3.1. Mutants reduce the population of the foldedstate. According to model used in V135G/V142G, the folded state population iszero in this construct.
48
Chapter 4
Calorimetric determination of
inhibitor binding affinity of AK
constructs
4.1 Abstract
The impact of induced local unfolding on binding affinity is investigated in this
chapter at temperatures ranging from 7 to 47 . Binding affinity was character-
ized with isothermal titration calorimetry (ITC) [54], using the non-hydrolyzable
inhibitor Ap5A [18] as ligand. Ap5A is composed of ATP covalently bound to
AMP by the last phosphate group. ITC is an efficient technique that determines
the apparent change in enthalpy (∆Ha) and apparent free energy (∆Ga) associ-
ated with the binding process in one single experiment. Our results show that a
state with little affinity for the ligand is also present in WT at physiological tem-
perature (37 ). Moreover, the increase of the population of the this low-affinity
state promoted by Gly mutations is responsible for the modulation of ∆Ha and
∆Ga. Interestingly, AK can also bind Ap5A in the absence of the LID (LID-
LESS). However, the binding affinity is marginal (Ka,WT/Ka,LIDLESS = 37.2 at
21 ). ∆Ha of this construct followed a linear relationship with temperature, indi-
cating a binding process in the absence of any binding incompetent state between
49
7 and 47 . Intriguingly, when the LID possessed two simultaneous Gly muta-
tions (i.e. V135G/V142G), ∆Ha showed small change at temperatures higher than
30 . Our simulations suggested that this unexpected trend can be reconciled if
it is assumed that the ensemble is highly populated by the state having the LID
unfolded (LU) at the investigated temperatures and if it is assumed that binding
affinity of LU is equal to that of LIDLESS. Overall, our ITC experiments indicate
that local unfolding events modulate binding affinity through modulation of the
conformational ensemble.
4.2 Introduction
Binding affinity is the propensity of a enzyme to bind a specific ligand. Modulation
of binding affinity promoted by local unfolding was characterized by determining
∆Ha and ∆Ga of different constructs at different temperatures between 7 and
47 . The inhibitor Ap5A was used as ligand instead of original substrates be-
cause heat released during ATP hydrolysis obscures the heat evolution related to
the binding process. ∆Ha and ∆Ga of WT and mutants were investigated using a
thermodynamic model at which AK can visit three states, as indicated by DSC ex-
periments. In this model, it is assumed that the folded, and at much lesser extent,
the LU state are able to bind ligand. For WT, single mutants and A73G/V142G,
it is safe to assume that the presence of LU has no effect on apparent affinity.
However, in V135G/V142G, the marginal affinity of LU has to be considered to
reconcile experimental observations. Binding affinity of LIDLESS was also inves-
tigated between 7 and 47 . Finally, to investigate V135G/V142G trend, it is
assumed that LU present the same binding parameters as LIDLESS.
50
4.3 Materials and methods
4.3.1 Protein preparation
ITC experiments were performed onWT, A55G, A73G ,V135G,V142, A73G/V142G,
V135G/V142G, V135G/V148G, V142G/V148G and on LIDLESS. Constructs were
expressed and purified according to protocols described in Chapter 2. Binding
affinity experiments were carried out with freshly prepared AK solutions dialyzed
against calorimetric buffer (60 mM PIPES, 1 mM EDTA pH 7.85). PIPES buffer
was selected because of its small heat of ionization. The number of protons
(nH+) transfered from the buffer to the protein-inhibitor complex was negligi-
ble (-0.04±0.07 for WT and 0.17±0.17 for V142G) [40], AK concentrations were
measured with a UV spectrometer at 277 nm using ε = M-1cm-1 for WT, single
and double mutants and ε = 11653 M-1cm-1 for LIDLESS. The inhibitor Ap5A
(Sigma-Aldrich) solution was prepared using the same buffer used to dialyze the
AK solution. Ap5A concentration was measured with ε259 = 30882 M-1cm-1. Initial
protein concentrations of ≈ 40 M and inhibitor concentration ≈ 400 Mwere used
for WT, A55G, A73G, V135G and V142G and A73G/V142G. For V135G/V142G,
V135G/V148G and V142G/V148G, protein and inhibitor concentrations of ≈ 80
M and 1200 M were used. For LIDLESS, the protein and inhibitor concentration
were ≈ 80 M and ≈ 2100 M respectively. Since constructs with double muta-
tions in the LID and LIDLESS presented lower binding affinity constants (Ka), the
protein and inhibitor concentrations were increased to obtain complete titration
curves.
4.3.2 ITC experimental design
Binding parameters were obtained by measuring the heat released or absorbed
while a ligand was titrated into the sample cell containing the AK solution to be
studied. The initial ligand concentration was at least ten times the concentration of
51
the enzyme to ensure a complete saturation. The area generated by every injection
of ligand under the heat evolution was recalculated as function of the molar ratio
of ligand to enzyme. Subsequent analysis of the resulting titration curves gave the
apparent change of free energy (∆Ga), apparent enthalpy (∆Ha), and apparent
entropy (∆Sa) of binding as well as the binding stoichiometry number (n) of the
binding process. The n value gives the number of ligand molecules bound to
the enzyme. The expected n value for our experiments is one because one AK
molecule binds only one Ap5A molecule. Binding parameters were measured at
different temperatures (from 7 to 47 ) with a VP-ITC (Malvern, Westborough,
MA). Injection parameters were selected as follows: total number of injections =
55; volume injection = 5 !l ; spacing between injections = 220 or 300 seconds ;
duration= 10 seconds; filter period = 2 seconds. The stirring speed and Feedback
Mode/gain option were set up to 307 rpm and high respectively. Reference and
sample cells were cleaned extensively before every running. The reference cell was
filled with ddH2O. Protein solutions were degassed for at least 30 minutes. Binding
parameters (∆Ga,∆Ha,∆Sa and n) were determined from titration binding curves
using the software Originr version 7.0 (Malvern, Westborough, MA).
4.3.3 Linkage analysis between local unfolding and ensem-
ble modulation
Effects of local unfolding promoted by Gly mutations on the free energy ∆Ga and
enthalpy ∆Ha of binding were studied using the following reaction scheme:
We assumed that the folded and LU states are the only states able to bind
inhibitor and that AK unfolds through a three-state process. LU, which is regarded
to be have little affinity for the inhibitor, is the state having the LID unfolded.
As we mentioned in Chapter 3, the folded state is composed of a extended and
a compact conformation that is also populated in the absence of substrates, [15].
Due to the addition of inhibitor, the compact conformation is populated while
52
the extended is depopulated. Based on the scheme, the apparent binding affinity
constant is defined as:
Ka =[F − I] + [LU − I]
([F ] + [LU ] + [U ])[I]=
Ko +KLUKLID
1 +KLID +KLIDφKCA
=Ko +KLUKLID
Q(4.1)
where Ko is the intrinsic binding constant between the folded and the inhibitor
and it was expected no to be affected by mutants because the crystallographic
structure is not perturbed. KLU is the intrinsic binding constant between LU and
the inhibitor. KLID, φ and KCA are the equilibrium constants associated to the
unfolding of the LID, coupling and CORE-AMPbd respectively. Q is the parti-
tion function in the absence of inhibitor, see chapter 3. Therefore, the apparent
enthalpy of binding ∆Ha is defined as
∆Ha = RT 2dln(Ka)
dT=
1
(1 +KLUKLID
Ko
)
[
∆Ho +KLUKLID
Ko
(∆HLU +∆HLID)]
− (PLU + PU)∆HLID − PU(∆Hφ +∆HCA) (4.2)
where ∆HLID, ∆Hφ and ∆HCA are the changes of enthalpies related to the un-
folding of the LID, coupling and CORE-AMPbd respectively. PLU and PU are the
probability of the state at which the LID is unfolded and the probability of the
unfolded state, respectively, in the absence of inhibitor. They were calculated from
the partition function Q. When Ko ≫ KLUKLID, Eq. 4.2 is reduced to:
∆Ha = ∆Ho − (PLU + PU)∆HLID − PU(∆Hφ +∆HCA) (4.3)
53
The apparent free energy of binding (∆Ga) is defined as:
∆Ga = −RTln(Ko(1 +KLUKLID
Ko
)) +RTln(Q) (4.4)
When Ko ≫ KLUKLID, Eq. 4.4 is reduced to:
∆Ga = ∆Go +RTln(Q) = ∆Go +∆GConf (4.5)
4.3.4 Prediction of ∆Ha and ∆Ga
Since it is expected that Ko ≫ KLUKLID, ∆Ha and ∆Ga trends as function of
temperature were calculated using Eqs. 4.3 and 4.5, see Figs. 4.1 and 4.2. These
equations carry the assumptions that Ko ≫ KLUKLID. Therefore, the effect of
low affinity of LU on the measured affinity is considered to be negligible. Since it
is expected that mutations do not disturb the protein structure, only the equilib-
rium between the folded and locally unfolded state (LU), simulated curves were
determined by assuming that the intrinsic enthalpy (∆Ho) and intrinsic free en-
ergy (∆Go) are not perturbed. ∆Ho and ∆Go were calculated from actual WT
titration curves. ∆Ho was determined by using ∆Ha at 7 and 11 to calculate
the intrinsic heat capacity of binding, ∆CP,o, and therefore to determine ∆Ho up
to 47 , see dashed line in Fig. 4.1. ∆Go was calculated between 20 and 47
by using Eq. 4.5. This temperature range was used because ∆Ga measurements
become noisy at lower temperatures. ∆Ha and ∆Ga for V135G/V142G were de-
termined by assuming that the LID is 50% unfolded at 10 (Tm,LID = 10 ).
This assumption was included because unfolding of the LID was not observed in
DSC experiments performed on V135G/V142G between 10 and 80 . ∆HvH,LID
was determined by extrapolating ∆HvH,LID of WT to 10 . The thermodynamic
parameters of the coupling interaction and CORE-AMPbd in V135G/V142G were
taken from DSC experiments, see Table 3.1.
54
4.4 Results and discussion
4.4.1 Local unfolding promoted by mutations modulates
binding affinity
Local unfolding promoted by mutations affects ∆Ha and ∆Ga. Our data show
the temperature dependence of mutational effects, see Figs. 4.3 and 4.4(b)-(d).
According to our model, the presence of the low-affinity LU state, which also pop-
ulates the WT ensemble at physiological temperature, it is principal responsible
for deviations from ∆Ho, see Fig. 4.1. Mutations in the CORE-AMPbd (A55G
and A73G) exhibit similar effects on binding affinity of AK. A55G decreases ∆Ga
by 0.4 kcal/mol at 37 . On the other hand, A73G has statistically no effects on
∆Ga. However, both mutations do not affect ∆Ha between 7 and 47 . This
small change on binding affinity can be explained by the small perturbation of
the ensemble exerted by A55G and A73G, see Figs. 3.5, 3.12 and 3.13. However,
V135G and V142G promote larger and similar effects on ∆Ha and ∆Ga. This
can be explained by lower stability of the LID and the higher capacity of Gly
substitution to promote local unfolding, and therefore, the low-affinity state (LU),
especially at temperatures higher than 20 . Consequently, larger population of
LU state induces larger deviations from ∆Ho and ∆Go, see Eq. 4.3. It is shown
that A73G/V142G presents statistically the same effects on binding as V142G
because A73G has negligible effects on binding affinity and does not destabilize
the LID. V135G and V142G exhibit similar effects on binding affinity. However,
V135G/V142G trend is different from our predictions. Experimental ∆Ha de-
creases monotonically from 7 to 30 ; then, ∆Ha presents small changes with
temperature. To understand this behavior, a computational parameter exploration
was performed using Eqs. 4.2 and 4.4.
55
4.4.2 The CORE-AMPbd can also bind Ap5A in the ab-
sence of the LID
LIDLESS was also able to bind Ap5A but to a much lower extent than WT, see
Fig. 4.4 (a) and (b). At 37 , ∆∆Ha is -7.5 kcal/mol and ∆∆Ga is 2.8 kcal/mol.
This value corresponds to ratio of Ka,WT/Ka,LIDLESS ≈ 95. ∆Ha follows a linear
relationship with temperature between 7 and 47 . This trend is characteristic
of a enzyme with only one state that is binding competent at that range of temper-
ature. This observation is consistent with the two-state unfolding of the CORE-
AMPbd observed in Chapter 3. The intrinsic heat capacity of binding (∆CP,o) of
AK constructs, excepting simultaneous mutation in the LID, corresponds to -0.6
kcal/mol*K, implying that the area buried during inhibitor binding belongs to the
CORE-AMPbd, see Table 4.1. This result is a strong evidence that the short linker
that replaces the LID does not perturb the structure of the CORE-AMPbd. The
assumption that the low affinity of LU have negligible effect on the observed affin-
ity on WT, single mutants and A73G/V142G was tested by determining the value
of KLUKLID/Ko at 21 . It was assumed that KLU = KLIDLESS. KLID values
were determined from Table 3.1. Additionally, it was considered that Ko = Ka,WT
because the WT ensemble is only populated by the folded states (Q = 1) at 21 .
Calculated values of KLUKLID/Ko at 21 supported the above assumption and
they were: 6.4×10−5, 6.4×10−5, 6.4×10−5, 6.4×10−5, 1.0×10−3, 4.2×10−4 and
3.2× 10−4 for WT, A55G, A73G, V135G, V142G and A73G/V142g respectively.
4.4.3 Trends of free energy and enthalpy of binding as
functions of temperature can be predicted using EAM
In general, simulated ∆Ha and ∆Ga curves agree with those obtained by ITC
experiments. This similarity in trends indicates that modulation of the ensemble
plays an important role in the regulation of ∆Ha and ∆Ga. According to Eqs.
4.3 and 4.5, the decrease of ∆Ha and increase of ∆Ga can be explained by the
56
larger population of the low-affinity LU state promoted by Gly mutations, see
Figs. 4.1 and 4.2. Although our model predicts the binding signature trends of
single mutants and A73G/V142G, it does not completely capture the trend of ΔGa
and ΔHa of mutants having two simultaneous Gly mutations on the LID. After a
steady decrease of ΔHa as temperature was raised, ΔHa presented small changes
at temperature higher than 30, crossing the ΔHa profiles of V135G and V142G,
see Figs. 4.1 and 4.3 (c). In addition, experimental ΔGa exhibits more positive
values when compared with the simulated curve specially at temperatures higher
than 30 , see Figs. 4.2 and 4.4 (c). A plausible explanation for this unexpected
trend is presented below.
4.4.4 Double mutations in the LID completely depopulate
the folded state at 40.
Effects of two simultaneous mutations in the LID on binding affinity, see Figs.4.7
and 4.8, could be explained if double mutations in the LID promotes high depopu-
lation of the folded state at temperatures higher than 20. Our simulations shows
that the ensemble is populated by the LU state, which is regarded a low-affinity
state, at temperatures between 40 and 47. On the other hand, the popula-
tion of the folded state is 50% at 13 and 1% at 37, see Fig. 4.9. Simulation
also suggest that double mutantions in the LID do not change the crystallographic
structure. They just modulate the ensemble as expected. This simulation also
suggests that DSC experiments were not able to detect the unfolding of the LID
in V135G/V142G because of the low stability promoted by two simultaneous Gly
mutations in the LID.
57
4.5 Conclusions
Our ITC experiments support the view that the redistribution of the conforma-
tional ensemble promoted by local unfolding is the principal mechanism in binding
affinity regulation. The population of the low-affinity LU state, which is present on
the WT ensemble, is increased by Gly mutations. Surprisingly, AK can marginally
bind Ap5A although the LID is removed. Furthermore, computational investi-
gation of ∆Ha and ∆Ga of V135G/V142G strongly suggests that simultaneous
mutations in the LID do not change the structure. They only modulate the en-
semble.
58
(a) Apparent (∆Ha) and intrinsic (∆Ho) binding enthalpies ofWT
(b) Simulations of ∆Ha of Gly mutants
Figure 4.1: Simulation of ∆Ha as a function of temperature of AK mutants usingEq. 4.3. (a) ∆Ho,WT as a function of temperature was determined by using∆Ha,WT at 7 and 11 to calculate ∆CPo,WT . Then, ∆Ha,WT at 7 was taken asreference and it was extrapolated up to 47 . (b) In mutants, ∆Ha was determinedby using ∆Ho,WT and associated partition function calculated from DSC, see Table3.1. Since DSC experiments performed on V135G/V142G did not detect unfoldingof the LID between 10 and 80 , it was assumed that the associated Tm,LID is10 . ∆HvH,LID of V135G/V142G was calculated using ∆HvH,LID of WT and∆Cp,LID.
59
(a) Apparent (∆Ga) and intrinsic (∆Go) free energies of bindingof WT
(b) Simulation of ∆Ga of AK mutants
Figure 4.2: Simulation of ∆Ga at different temperatures of AK mutants using Eq.4.5. (a) ∆Go,WT as function of temperature was calculated by rewriting Eq. 4.5.That is, ∆Go,WT = ∆Ga,WT −RTln(QWT ). (b) ∆Ga of mutants were determinedby using ∆Go,WT and the associated partition function (Q) calculated from DSC,see Table 3.1. For V135G/V142G, it was assumed that the associated Tm,LID is10 . ∆HvH,LID of V135G/V142G was calculated using ∆HvH,LID of WT and∆Cp,LID.
60
(a) LIDLESS (b) Mutations in the CORE-AMPbd
(c) Mutations in the LID (d) Mutations in the LID and CORE-AMPbd
Figure 4.3: Apparent enthalpies of binding of AK constructs vs temperature (∆Ha
vs T). Temperature varies from 7 to 37 . The inhibitor Ap5A was used asligand. (a) LIDLESS is also able to bind the inhibitor. (b)-(d) Gly mutations in-crease the population of the low-afinity state (LU), especially at high temperatures.Larger population of LU results in lower values of ∆Ha.
61
(a) LIDLESS (b) Mutations in the CORE-AMPbd
(c) Mutations in the LID (d) Mutations in the LID and CORE-AMPbd
Figure 4.4: Apparent free energies of binding of AK constructs vs temperature(∆Ga vs T). Temperature varies from 7 to 37 . The inhibitor Ap5A was usedas ligand. (a) LIDLESS binds the inhibitor at much less extent than WT does,approximately 37 fold less at 21 . (b)-(d) Gly mutations increase the popula-tion the binding incompetent (LU) state, especially at high temperatures. Largerpopulation of LU results in more positive values of ∆Ga.
62
(a) LIDLESS (b) WT (c) A55G
(d) V135G (e) V142G (f) V135G/V142G
Figure 4.5: Representative ITC titration curves at 37 with respective fittingparameters.
63
(a) LIDLESS (b) WT (c) A55G
(d) V135G (e) V142G (f) V135G/V142G
Figure 4.6: Representative binding signatures at 37 . These plots show the effectsof entropy-enthalpy compensation on AK constructs. Relative small changes in∆Ga are accompanied by large changes in ∆Ha and −T∆Sa, which show opposingeffects.
64
(a) Simulated ∆Ha of V135G/V142G. ∆Ho,WT and ∆HLIDLESS
are shown as comparison
(b) Comparison of ∆Ha constructs with simulated ∆Ha ofV135G/V142G
Figure 4.7: Simulated ∆Ha of V135G/V142G as a function of temperature usingEq. 4.2 (dotdash line). (a) Simulated curve of ∆Ha involves the terms Ho,WT
and ∆HLU . It was assumed that KLU = KLIDLESS and ∆HLU = ∆HLIDLESS
(b) Simulated ∆Ha was calculated using the following values: ∆HvH,LID = 28.4kcal/mol, ∆CP,LID = 0.4 kcal/mol*K , Tm,LID = 13 , ∆HvH,φ = 8.1 kcal/mol,∆CP,φ = 0.0 kcal/mol*K , Tm,φ = 102.5 , ∆HvH,CA = 109.1 kcal/mol, ∆CP,CA =2.7 kcal/mol*K , Tm,CA = 53.4 . ∆Ha of WT, V135G, V142G and V135G/V142Gwere plotted for comparison.
65
(a) Simulated∆Ga of V135G/V142G. ∆Go,WT and ∆GLIDLESS
is shown as comparison
(b) Comparison of ∆Ga of constructs with simulated ∆Ga ofV135/V142G
Figure 4.8: Simulated ∆Ga of V135G/V142G as a function of temperature usingEq. 4.4 (dotdash line). (a) Simulated curve of ∆Ga involves the terms ∆Go,WT
and ∆GLU . It was assumed that ∆GLU = ∆GLIDLESS. (b) Simulated ∆Ga wascalculated using the following values: ∆HvH,LID = 28.4 kcal/mol, ∆CP,LID = 0.4kcal/mol*K , Tm,LID = 13 , ∆HvH,φ = 8.1 kcal/mol, ∆CP,φ = 0.0 kcal/mol*K ,Tm,φ = 102.5 , ∆HvH,CA = 109.1 kcal/mol, ∆CP,CA = 2.7 kcal/mol*K , Tm,CA =53.4 . ∆Ga of WT, V135G, V142G and V135G/V142G were plotted for compar-ison (b).
66
Figure 4.9: Calculated probabilities of states of simulated V135G/V142G in theabsence of Ap5A. Probabilities of states as function of temperature were calculatedusing values in Fig. 4.7 on Eq. 3.1. According to our simulations, V135G/V142Gdoes not change intrinsic affinity, only depopulates the folded state to at largerextent than V135G and V142G.
67
AK constructs: LIDLESS WT A55G A73G V135G V142G A73G/V142G
∆CP,o (kcal/mol*K) -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6
Table 4.1: Intrinsic enthalpy of binding (∆CP,o) of AK constructs, calculated ac-cording to: ∆CP,o = (∆Ha,11 − ∆Ha,7 )/(11 − 7 ). Although the LID wasremoved, LIDLESS exhibits the same ∆CP,o as WT.
68
Chapter 5
Measurement of catalytic rate of
AK constructs
5.1 Abstract
Catalytic rate (kcat) describes how fast a enzyme converts substrates into products.
In this chapter, we investigate the effects of promoted local unfolding by Gly
mutations on kcat associated with the reverse catalytic reaction [41] (Mg2+ADP +
ADP →Mg2+ATP+AMP ) between 15 and 50 . Our data indicate that single
mutations in the CORE-AMPbd (A55G and A73G) cause an increase in kcat by a
factor of 29% and 16% at 37 respectively. On the other hand, single mutations in
the LID (V135G and V142G) have no impact in kcat between 15 and 40 . After
40 , kcat was lower in V135G and V142G, implying that mutational effects increase
with temperature. However, two simultaneous mutations in the LID, promoted
lower values of kcat at any temperature. Surprisingly, when A73G and V142G
were simultaneously present, kcat reached similar values to those observed in A55G.
This result suggests that mutational effects are not necessarily additive. Removal
of the LID dramatically decreases kcat by a factor of 52 at 25 , indicating that
the CORE-AMPbd by itself is also able to poorly catalyze nucleotides. Overall,
our data show that promoted local unfolding outside the active site can modulate
kcat, and the magnitude of the effect depends on the location of the perturbation.
69
5.2 Introduction
Enzymes speed up reactions without altering the equilibrium between the sub-
strates and products, meaning that the depletion rate of substrate and formation
rate of products are increased by the same factor. According to the transition
state theory (TST), enzymes catalyze reactions by decreasing the activation en-
ergy barrier, by binding more tightly the transition state than the ground state,
[60]. Thus, higher binding propensity of enzymes for transition states favors the
crossing of the barrier, increasing the formation of products. Catalytic activity is
characterized by the catalytic rate (kcat) and the activation energy barrier (∆G‡).
kcat is defined as the rate of substrate-to-product conversion when the enzyme is
saturated with substrate. As stated by the Eyring-Polanyi equation [61, 62], kcat
can be described as a function of temperature and ∆G‡, see Eq. 5.1. In this chap-
ter, we study the impact of induced local unfolding on kcat on the reverse catalytic
reaction (Mg2+ADP + ADP → Mg2+ATP + AMP ) at different temperatures.
kcat was measured at saturating concentration of Mg2+ and ADP . Then, the
enthalpy (∆H‡) and entropy (∆S‡) of the transition state, and therefore ∆G‡,
were determined by using the linear Eyring-Polanyi equation, see Eq. 5.3. It has
been proposed that AK catalysis follows a random Bi Bi mechanism [58] at which
two different substrates bind their corresponding site randomly. In addition, it
has been determined that the rate-limiting step in AK catalysis is the conforma-
tional change of the LID related to the release of the products (kLID)[29]. This
conformational change is also regarded as the opening of the LID to release the
products. Simulations based on the random Bi Bi mechanism, see Fig. 5.1, were
also employed to improve our understanding of the effects of local unfolding on
kcat.
70
5.3 Materials and methods
5.3.1 Measurements of catalytic activity in the reverse re-
action
Reverse reaction was measured by coupling the formation of Mg2+ATP to the
hexokinase and glucose-6-phosphate dehydrogenase reactions [40]. The reaction
mixture was composed of 50 mM HEPES, 10 mM D-Glucose, 20 mM MgCl2,
100 mM KCl, 15 mM ADP, 1.2 mM NADP and 0.5 mg/ml BSA, 10 UN/ml of
hexokinase and glucose-6-phosphate dehydrogenase (diluted in 50% w/v glycerol),
pH 8.0. The reaction was equilibrated at the desired temperature for at least 5
min. and then started by the addition of 10 l of 0.4 M AK. The total mixture
volume was 1 ml. The rate of increase in absorbance produced by the formation of
NADPH (kNADPH) was measured at 340 nm. To test that Mg2+ADP +ADP →
Mg2+ATP + AMP was the slowest reaction, 1.5 mM of ATP was added to the
reaction mixture at 25!. The rate of NADPH conversion was more than 10 times
greater than the fastest AK rate measured at the same temperature. Finally, kcat
was determined according to:
kcat =kNADPH
2 εNADPH [E]T(5.1)
where, εNADPH is the extinction coefficient of NADPH and is equal to 6220 AU
M−1cm−1 and [E]T is the final concentration of AK in the reaction solution. En-
zyme concentrations were determined with a UV spectrometer and corrected by
using the number of sites (n) obtained from Ap5A-ITC experiments run at the
same temperature as the activity assay. All the chemical compounds used in this
assay were acquired from Sigma-Aldrich.
71
5.3.2 Transition state characterization
According to the TST, a reaction rate k is a function of temperature and a high-
energy barrier, [61] and it is described by the Eyring-Polanyi equation as follows:
k =kBT
he−
∆G‡
RT (5.2)
where, ∆G‡ is free energy of the transition state and corresponds to the highest
point in the energy profile. For enzyme kinetics, kcat is the apparent rate in a
catalytic process and it can be linked to the TST parameters by linearizing the
Eyring-Polanyi equation, thus:
ln(kcatT
) = −∆H‡
R
1
T+
∆S‡
R+ ln(
kBh) (5.3)
In this equation, ∆H‡ and ∆S‡ are assumed to be temperature independent. The
transition state of every AK construct was characterized by taking the linear region
of the ln(kcat/T ) vs 1000/T plot, see Table 5.2 and Fig. 5.3.
5.3.3 Exploration of kcat modulation through a random Bi
Bi mechanism
kcat was modeled according to the reaction scheme shown in Fig. 5.1. The model
assumes that substrates and the enzyme bind very fast compared with the phos-
phate transfer and the release of products. Therefore, substrates and the enzyme
achieve a state of quasi-equilibrium, [63]. This model also assumes that the con-
formational change of the LID (kLID) associated with the release of the product
is the rate-limiting step in AK catalysis. In other words, the conversion of ADP
into ATP and AMP and the release of AMP are regarded as fast compared with
kLID. All the AK species formed after the phosphate transfer were assumed to be
negligible. The folded state was assumed to be the only binding competent state,
see Chapter 4. Mg2+ADP and Mg2+ATP bind to residues in the LID and CORE
(ATP site) and the ADP and AMP bind to residues in the CORE and AMPbd
72
(AMP site), [18]. Although, there is evidence that either AMP or Mg2+ can bind
to the ATP site at high concentrations, [58, 64], this model does not consider those
effects. Thus, the expression used to simulate kcat as function of temperature was:
kcat =kLIDKMg2+ADPKADP [Mg2+ADP ][ADP ]
Q+KMg2+ADP [Mg2+ADP ]+KADP [ADP ]+KMg2+ADPKADP [Mg2+ADP ][ADP ](5.4)
where, KMg2+ADP and KADP are the binding affinity constant related to the as-
sociation of AK with Mg2+ADP and AK with ADP respectively. [ADP ] and
[Mg2+ADP ] were calculated as follows:
[ADP ]=−(KMg2+ ([Mg2+]T−[ADP ]T )+1)+
√
(KMg2+ ([Mg2+]T−[ADP ]T )+1)2+ 4KMg2+ [ADP ]T
2KMg2+
(5.5)
[Mg2+ADP ]=[ADP ]T−[ADP ] (5.6)
KMg2+ is the association constant for Mg2+ and ADP. [Mg2+]T and [ADP ]T are
the total concentration of Mg and ADP. kLID was assumed to follow Eq. 5.2.
Binding constants (KMg2+ADP and KADP ) were calculated assuming free energies
of binding as constants with temperature. Prediction of ln(kcat/T ) vs 1000/T for
AK constructs were determined by assuming that Gly mutations do not change
kLID,KMg2+ADP and KADP , see Fig. 5.2. Partition functions were calculated accord-
ing to thermodynamic values from Table 3.1, with the exception of V135G/V142G.
For this double mutant, we used the partition function used to explain the trend
of ∆Ha and ∆Ga observed in ITC experiments, see Figs. 4.7 and 4.8. The propose
model was also used to analyze our experimental data, see Figs. 5.4 and 5.5.
5.4 Results and discussion
5.4.1 Mutational effects are temperature dependent
All constructs increase kcat with temperature, indicating the importance of thermal
motion in protein function. However, kcat drops dramatically at high temperatures.
It was observed that the catalytic activity ceases at 55 in all the AK constructs.
73
While some mutants maintain or decrease kcat, others such as A55G, A73G and
A73G/V142G increase it. The dramatic drop of kcat observed in AK constructs at
high temperatures, see Fig. 5.3, can be reconciled by inspection of Eq. 5.4. This
equation indicates that the partition function (Q) becomes the dominant term in
the denominator at high temperatures. Higher values of Q are associated with
larger population of low-affinity (LU) and unfolded states (U).
5.4.2 Local unfolding modulates kcat
A55G and A73G increase kcat by 36% and %9 respectively at 25 , see Fig. 5.3(a)
and Table 5.1 by lowering the activation energy, see Table 5.2. The increase is ob-
served for the whole temperature range (15-55 ). According to our kinetic model,
see Fig. 5.1, higher kcat values can be achieved by faster kLID, by higher binding
affinity between AK and substrates (KMg2+ADP , and KADP ) or combination of both
effects. ITC experiments show that our mutants do not increase binding affinity
(Ka). In fact, A55G slightly decreases it. Therefore, the simplest explanation is
that higher kcat can be the result of faster release of [Mg2+ATP ] (that is, higher
kLID), see Fig 5.4. Single mutations in the LID have no impact in kcat between
15-40 , see Fig. 5.3(b). After this temperature, single mutants exhibit higher
drops in kcat. Our model can explain this trend by the larger population of LU
induced by Gly mutations without any change in kLID, KMg2+ADP or KADP . In
other words, single mutants do not perturb the folded state. Double mutations
in the LID decreases kcat. This trend can be explained if double mutations only
lower kLID, see Fig 5.5. Finally, simultaneous single mutations in the LID and
CORE-AMPbd (A73G/V142G) increase kcat to the same extent as A55G does,
see Fig. 5.3(c). Again, this result can be the effect of higher kLID. This result
indicates that mutational effects are not necessarily additive.
74
5.4.3 LIDLESS exhibits marginal catalytic activity
LIDLESS also catalyzes substrates. However, the catalytic activity is dramatically
reduced by the absence of the LID, see Fig. 5.3(c). The observed trend can be
described considering only that KMg2+ADP is close to zero and the transfer of the
phosphate group is the rate-limiting step. This result raises the question of what
is the catalytic function of the LID. It has been suggested that the LID protects
the phosphate-group transfer from water during catalysis [52]. However, AKs from
different organisms have a short (e.g. porcine AK, domain: eukaryota, pdb file:
3ADK) or no LID domain (e.g. sulfolobus solfataricus AK, domain: archaea, pdb
file: 3HOK).
5.5 Conclusions
Local unfolding can modulate kcat. Single mutations in the LID maintain catalytic
activity. Single mutations in the CORE and AMPbd increase it; and, two simul-
taneous mutations in the LID decrease it. According to our kinetic model, kcat
modulation can result by slowing down or increasing the release of the products
(kLID modulation). Unexpectedly, AK can also catalyze nucleotides without the
LID (LIDLESS), but to a marginal extent.
75
Figure 5.1: Kinetic model for AK. The model is based on the random Bi Bi mechanism [58]. In this model, the LID only bindsMg2+ADP andMg2+ATP , [18]. The AMPbd only binds ADP and AMP. It was assumed that a there AK and substrates reacha state of quasi-equilibrium followed by a slow catalytic event [63]. In this model, the rate-limiting step is the conformationalchange of the LID (kLID) before the release of Mg2+ATP, [29, 15]. KMg2+ADP and KADP are the binding affinity constants relatedto the association of AK with Mg2+ADP and AK with ADP respectively. F, LU and U are the folded, LID unfolded andunfolded states respectively.
76
Figure 5.2: Expected ln(kcat/T ) vs 1000/T using Eq. 5.4. It was assumed thatmutations did not change KMg2+ADP , KADP and kLID. Values used in our simu-lation were: [ADP ]T = 4 mM, [Mg2+]T = 2 mM, ∆H‡ = 11.7 kcal/mol, ∆S‡ =-0.01 kcal/mol*K, KMg2+ = 4000 M−1, KMg2+ADP = 30303 M−1, KADP = 3570 M−1.Binding affinity constants were taken from [59]. Temperature varies from 15 to60 . Partition functions, with the exception of V135G/V142G, were calculatedusing values in Table 3.1 in Chapter 3. Since DSC experiments performed onV135G/V142G did not detect unfolding of the LID between 15 and 80 . Parti-tion functions were calculated using the values to simulate the trend of ∆Ha and∆Ga observed in ITC experiments. In sum, ∆HvH,LID = 28.4 kcal/mol, ∆CP,LID =0.4 kcal/mol*K , Tm,LID = 13 , ∆HvH,φ = 8.1 kcal/mol, ∆CP,φ = 0.0 kcal/mol*K,Tm,φ = 102.5 , ∆HvH,CA∗ = 109.1 kcal/mol, ∆CP,CA∗ = 2.7 kcal/mol*K, Tm,CA∗= 53.4 . *CA = CORE-AMPbd.
77
(a) Mutations in the CORE-AMPbd (b) Mutations in the LID
(c) Mutations in the LID and CORE-AMPbd (d) LIDLESS
Figure 5.3: Experimental data fitted to the linear form of the Eyring-Polanyiequation, see Eq. 5.3. Temperature varies from 15 to 50 .
78
AK kcat,25
Construct (1/s)
WT 124.6 4.0
A55G 169.9 4.0
V135G 135.2 4.0
V142G 132.0 4.0
A73GV142G 174.2 4.0
V135GV142G 69.8 2.0
V135GV148G 101.3 2.0
V142GV148G 102.7 4.0
LIDLESS 2.4 0.1
Table 5.1: Representative values of kcat at 25!.
79
AK ∆H‡ −T∆S‡ ∆G‡25
Construct (kcal/mol) (kcal/mol) (kcal/mol)
WT 10.6 0.3 4.1 0.3 14.6 0.4
A55G 10.9 0.2 3.7 0.2 14.4 0.3
A73G 10.9 0.4 3.7 0.4 14.5 0.6
V135G 10.7 0.3 3.9 0.3 14.5 0.5
V142G 10.7 0.3 4.0 0.3 14.6 0.4
A73GV142G 10.9 0.3 3.7 0.3 14.4 0.5
V135GV142Ga 12.8 1.3 2.3 1.3 14.9 1.8
V135GV148Gb 10.1 0.7 4.9 0.7 14.8 1.0
V142GV148Gc 10.9 0.2 4.0 0.2 14.7 0.3
LIDLESS 8.2 1.1 9.1 1.1 16.9 1.5
Table 5.2: Characterization of the transition state using the linear Eyring-Polanyiequation, see Eq. 5.3. Activation free energy barrier at 25!. Curve fitting wasperfomed on data collected between 15! and 40!, excepting (a) V135G/V142G(15!-25!), (b) V135G/V148G (15!-35!) and (c) V142G/V148G (15!-30!)∆H‡ and −T∆S‡ and related errors were obtained from least square fitting. Errorsin ∆G‡37 were calculated by propagation of errors associated to ∆G‡ and −T∆S‡.
80
Figure 5.4: Simulation of mutational effects of A55G and A73G on kcat. It isassumed that these mutations only lower ∆G‡ by decreasing ∆S‡. Similar effectscan be explained if it is assumed that mutations increase binding affinity. However,this effect is not supported for ITC binding experiments. Partition functions werecalculated from Table 3.1. The binding constants, KMg2+ADP and KADP , wereassumed not to be affected by mutations. Parameter used in this simulation were:[ADP ]T = 4 mM, [Mg2+]T = 2 mM, ∆H‡ = 11.7 kcal/mol, KMg2+ = 4000 M−1,KMg2+ADP = 30303 M−1, KADP = 3570 M−1. ∆S‡ for WT, A55G and A73G were-0.01, -0.094 and -0.097 kcal/mol*K respectively. Temperature varies from 15 to60 .
81
Figure 5.5: Simulation of mutational effects of V135G and V142G on kcat. It isassumed that single mutations do not change kLID, KMg2+ADP andKADP . See valuesin Fig. 5.2. V135G/V142G only decreases kcat by decreasing kLID (∆S‡ = -0.11).Temperature varies from 15 to 60 .
82
Chapter 6
Characterization of the ensemble
modulation using HX-NMR and
ITC
6.1 Abstract
The ensemble modulation was investigated using hydrogen/deuterium exchange
NMR (HX-NMR) and ITC at 37 . Stability of the LID (∆GLID) and stability of
the CORE-AMPbd, including the coupling interaction, (∆Gφ+∆GCA) were deter-
mined at 37 by using a method previously developed in our lab, [65]. According
to this method, ∆GLID and ∆Gφ +∆GCA were 1.3 and 7.3 kcal/mol respectively.
In V142G the stability of the LID was reduced to -0.2 kcal/mol. Subsequently,
the probability of the folded state of WT and V142G were calculated. Our results
show that the population of the folded state in WT represents 90% of the ensem-
ble. As expected, V142G modulates the ensemble by depopulating the folded state
from 90% to 43% and by increasing the locally unfolded state from 10% to 57%.
Although, the values obtained by this method slightly differ from those determined
by DSC, they also show the effect of a Gly mutation on the ensemble modulation.
83
6.2 Introduction
Hydrogen/deuterium exchange NMR (HX-NMR) [21] is used to determined the
stability (∆GHX) at 37 of different regions and to describe partially folded states.
Because of conformational fluctuations, exchange-incompetent amide protons (due
to burial or hydrogen bonding) are exposed to the solvent and become susceptible
to be exchanged with deuterium (D2O). If the rate of the amide proton to become
exchange-incompetent again is much larger than the rate to exchange with D2O
(condition known as the EX2 regime), the equilibrium constant (KHX) between
the exchange-competent (HX-C) and the exchange-incompetent (HX-I) state can
be determined. The equilibrium constant in turn gives the stability (∆GHX) asso-
ciated with the corresponding conformational fluctuation, [36]. HX-NMR exper-
iments have been previously performed on E. coli AK at 20 , [12]. It has been
reported that the CORE is the most stable region. It was also observed that the
residues in the LID and the AMPbd exchanged during the dead time for exchange,
which is the time between the very first exposure of AK to D2O and the very
first NMR measurement. Consequently, they were not observed during the actual
experiment. To determine the modulation of the ensemble, ∆GLID, ∆Gφ +∆GCA
as well as the impact of Gly mutation on the LID stability (∆gmut) were deter-
mined by using a method developed in our lab, [65]. This method combines ∆GHX
measured in the absence of ligand and ∆Ga from HX-NMR and ITC experiments,
respectively, to access domains stabilities. In this chapter, the probability of the
folded states for WT and V142G were measured at 37 and compared with those
values obtained from DSC experiments.
84
6.3 Materials and methods
6.3.1 Sample preparation
WT and V142G were 15N-labeled using the protocol presented in [37] and pu-
rified according to details described in Chapter 2. Protein samples were then
concentrated to ≈ 1mM using centrifugal filter units Amicon Ultra-15 30K (EMD
millipore) at 900xg (2500 rpm) in a Sorvall GS-3 rotor at 4 . A D2O solu-
tion was made using deuterium 99 atom % D from Sigma-Aldrich with 30 mM
PIPES buffer (AmericanBio). The pH was then measured using sodium deuterox-
ide (Sigma-Aldrich) at 37 . Subsequently, the pD was calculated according to
the formula pD = pH + 0.4, [12]). Concentrated AK solutions were exchanged to
D2O using the above-mentioned filter units under the same temperature and rotor
speed. The filter units were previously washed with D2O through centrifugation.
To ensure that the solution contained more than 90% of deuterium, the AK solu-
tion (≈ 600 !l) was mixed with the D2O (≈ 1800 !l) solution with a volume ratio
of 1 to 3. The mixed solution was then centrifuged until getting the same volume
of the initial AK solution. Then, the resulting mixed solution was again mixed
with the D2O solution with the same volume ratio. The new mixed solution was
centrifuged again to recover the initial AK solution volume. The exchange to D2O
took around 1 hour. The percent of D2O in the final solution was determined to
be 96% and it was calculated according to:
%D2O = [(Vratio + 1)n − 1
(Vratio + 1)n] · 100% (6.1)
where Vratio is the volume ratio of D2O solution to AK solution. n is the number
of repetitions. The pD of the AK exchanged solution was measured at 37 .
Thereafter, the solution was transfered to a NMR tube and immediately sent to
the NMR spectrometer. The corresponding pD values were measured again after
the NMR data was acquired. As expected, pD did not change.
85
6.4 Data acquisition and processing
Data were acquired in the Varian Inova 800 MHz NMR spectrometer at 37 . Ap-
parent hydrogen exchange rates (kex) were determined by collecting 1H-15N HSQC
NMR spectra for 48-60 hours. NMR data were processed using NMRPipe [68] and
Sparky [69] for Linux. Peak intensities were measured by volume integration and
kex was determined by fitting the function:
I = Ioe−kext + C (6.2)
where I is the intensity as a function of time, Io is the initial intensity and C
is a constant that corresponds to the baseline noise caused by residual H2O in
the sample, see [70]. Experiments were performed at different pD conditions to
determine the exchange regime (EX2 or EX1). WT Spectra were collected at pD
values of 6.8 and 7.2, and V142G spectra at pD values of 6.9 and 7.3. Then,
the slope of the log10(kex) vs ∆pD curve was determined. A slope equal to one
is associated with the EX2 regime, assuming that the equilibrium constant KHX
is pD independent, and slope of zero with the EX1 regime. ∆GHX values were
calculated only in residues that exchanged under the EX2 regime according to :
∆GHX = −RTln(kexkrc
) (6.3)
where krc is the intrinsic rate exchange. It corresponds to the rate at which an
solvent-exposed amide hydrogen is exchanged to deuterium. krc is pD and tem-
perature dependent and it was calculated at 37 according to [70], [71] and [72].
6.5 Domain stabilities
Since the stability of the LID cannot be monitored by HX-NMR, our lab developed
a method [65] to access the LID stability and therefore the probability of the folded
state. For this purpose, ∆Ga (free energy of binding) along with ∆GHX of WT
86
and V142G were combined to determine the stability of the LID and the CORE,
and subsequently, the probabilities of the folded states at 37 . The unfolding
reaction scheme for WT is similar to the scheme used in DSC experiments, see
Chapter 3, and it is defined as:
FKLID−−−−−−−−−−−−−−−−−− LU
φKCA−−−−−−−−−−−−−−−− U
F is the folded state, LU is the locally unfolded state whereby the LID is unfolded,
and U is the unfolded state. For V142G, the unfolded reaction is:
FΩKLID−−−−−−−−−−−−−−−−−−−− LU
φKCA−−−−−−−−−−−−−−−− U
where Ω represents the effect of the Gly mutation in the stability of the LID by
increasing the conformational entropy. Since it is assumed that single mutations
introduce only entropic perturbations, Ω is constant and is equal to:
Ω = e−∆gmut
RT = e∆SR (6.4)
We assumed that the unfolded state is the only exchange-competent state. F and
LU states were regarded as exchange-incompetent states. Thus the equilibrium
between the exchange-competent and exchange-incompetent state is for WT:
KHX,WT =[U ]
[F ] + [LU ]=KLIDφKCA
1 +KLID
(6.5)
and for V142G:
KHX,V 142G =ΩKLIDφKCA
1 + ΩKLID
(6.6)
thus,
∆∆GHX = −RTln(Ω(1 +KLID)
1 + ΩKLID
) (6.7)
More relationships between Ω, KLID and KCA were obtained from ∆Ga through
the following binding scheme:
In this scheme used for WT, it is assumed that the folded state (F) is the only
state able to bind the inhibitor Ap5A, see Chapter 4. For V142G, the scheme
reaction was:
87
F-I represents the bound state and Ko is the intrinsic affinity and it is the same
for WT and V142G. It was assumed that V142G substitution did not change Ko
and that the probability of the unfolded state is close to zero at 37 , therefore:
∆∆Ga = −RTln(1 +KLID
1 +ΩKLID
) (6.8)
By using Eqs. 6.5, 6.7 and 6.8, we obtained the mutational perturbation ∆gmut,
∆GLID and ∆Gφ + ∆GCA, thus:
∆gmut = ∆∆GHX −∆∆Ga (6.9)
∆GLID = −RTln(e−
∆∆GaRT − 1
1− e−∆∆GHX
RT
) (6.10)
∆Gφ +∆GCA = ∆GHX,WT −∆GLID −RTln(1 + e−∆∆GLID
RT ) (6.11)
It is assumed that ∆Gφ + ∆GCA is the same for both WT and V142G. However
the stability of the LID in V142G was calculated according to:
∆GLID,V 142G = ∆GLID +∆gmut (6.12)
Finally, the probability of the folded state (F) was determined using Eq. 3.1.
88
6.6 Results and discussion
6.6.1 The CORE is the most stable domain.
HX-NMR experiments clearly showed that residues L83 and V106 in the CORE
are the most stable residues in E.coli AK at 37 . see Figs. 6.1 and 6.4 and Tables
6.1 and 6.2. It is important to mention that only residues in the CORE were
detected and that L83 and V106 were the only residues in the EX2 regime, see Figs.
6.3 and 6.6. Residues in the LID and AMPbd were not detected during the data
acquisition, indicating the high conformational flexibility of both domains. Similar
conclusions were reached by Rundqvist and colleagues, see [12], by measuring
∆GHX through urea denaturation at 20 . Overall, amide hydrogen/deuterium
exchange experiments clearly show the intrinsic flexibility of proteins whereby the
most buried residues can also visit the solvent.
6.6.2 V142G modulates the conformational ensemble.
According to the methods employed in the material and methods section of this
Chapter, V142G depopulates the folded state (F) from 90% to 43%, and at the
same time, it increases the population of the locally unfolded state (LU) from
10% to 57% at 37 . This results also show that the LU state is also populated
at the physiological temperature of AK (37 ). At this temperature, ∆GLID is
1.3!0.2 kcal/mol and ∆Gφ + ∆GCA is 7.3!0.2 kcal/mol in WT. In V142G, the
Gly substitution decreases ∆GLID to -0.2!0.2 kcal/mol entropically. Although
the probabilities of the folded state in WT and V142G determined by HX-NMR
and ITC differ from those determined using DSC (95% and 71% respectively), the
effect of promoted local unfolding in the ensemble modulation is clearly evident.
89
6.7 Conclusions
Gly substitutions can modulate the ensemble of states by depopulating the folded
state and populating the locally unfolded state. Interestingly, the locally unfolded
state (LU), at which the LID is unfolded, is also visited by AK at physiological
temperatures. Finally, high flexibility, and therefore the low stability, of the LID
and AMPbd domains as well as the higher stability of the CORE were all confirmed.
90
Figure 6.1: Location of residues in the EX2 in WT.
Residues ∆GHX,37 (kcal/mol)
L83 8.7 0.1
V106 8.7 0.1
∆GHX,WT (average) 8.7 0.1
Table 6.1: ∆GHX of L83 and V106 in WT. Values were calculated according toEq. 6.3.
91
(a) L83, pD=6.8 (b) L8, pD=7.2
(c) V106, pD=6.8 (d) V106, pD=7.2
Figure 6.2: The apparent rate constant (kex) of residues L83 and V106 in WT.Data points were fitted to Eq.6.2.
92
Figure 6.3: Residues in the EX2 regime in WT. A value of log10(kex)/pD = 1indicates that kex can be used to determine ∆GHX .
93
Figure 6.4: Location of residues in the EX2 regime in V142G.
Residues ∆GHX,37 (kcal/mol)
L83 7.5 0.1
V106 7.7 0.1
∆GHX,V 142G (average) 7.6 0.1
Table 6.2: ∆GHX of residues L83 and V106 in V142G. Values were calculatedaccording to Eq. 6.3.
94
(a) L83, pD=6.9 (b) L8, pD=7.3
(c) V106, pD=6.9 (d) V106, pD=7.3
Figure 6.5: The apparent rate constant (kex) of residues L83 and V106 in V142G.Data points were fitted to Eq.6.2.
95
Figure 6.6: Residues in the EX2 regime in V142G. A value of log10(kex)/pD = 0.9indicates that L83 and V142 are just leaving the EX2 regime.
96
AK ∆Ga ∆GHX
Constructs (kcal/mol) (kcal/mol)
WT -9.3 0.1 8.7 0.1
V142G -8.9 0.1 7.6 0.1
Table 6.3: ∆Ga and ∆GHX values for WT and V142G at 37!. ∆Ga values weretaken from ITC experiments, see Chapter 4.
∆G (kcal/mol) WT V142G
∆GLID 1.3 0.2 -0.2 0.2*
∆Gφ + ∆GCA∗∗ 7.3 0.2 7.3 0.2
∆GTotal 8.6 0.2 7.1 0.2
Table 6.4: Domain stabilities values in WT and V142G at 37!. Values weredetermined by using experimental values from Table 6.3 in Eqs. 6.10, 6.11,6.9 and 6.12. *The stability of the LID in V142G was calculated according to∆GLID,V 142G = ∆GLID + ∆gmut, where ∆gmut = -1.5 0.2 kcal/mol. **CA =CORE-AMPbd
97
Figure 6.7: Graphical representation of ∆GLID and ∆gmut. ∆∆Ga (∆Ga,V 142G −∆Ga,WT ) and ∆∆GHX (∆GHX,V 142G−∆GHX,WT ) at 37 were plotted accordingto Eqs. 6.8 and 6.7. ∆gmut is always constant between the two curves.
98
Figure 6.8: Probabilities of the folded state of WT and V142G at 37 using valuesfrom Table 6.4. V142G reduces the population of the folded state from 90% to43%.
99
Chapter 7
Concluding remarks
7.1 Summary
Allostery was investigated by biophysical characterization of the effects promoted
by entropy enhancing mutations. Our fundamental conclusion is that proteins
can use local unfolding to regulate enzyme function, whereby the redistribution of
the probability of states promoted by local unfolding is the predominant mecha-
nism. Although, it was reported [12] that the LID and AMPbd are not coupled
to the CORE, our DSC experiments clearly shows that coupling interaction be-
tween the domains exists, see Fig. 3.4. The coupling between the LID and the
CORE-AMPbd is favorable (positive) at functional temperatures, and according
to our model, unfavorable (negative) at temperatures higher than 67.8 . Since
the CORE and AMPbd unfold as a single domain, it is possible that they are also
favorably coupled. The folded state is not the only state populated at physiological
temperature (37 ). At this temperature, the folded state represents 95% of the
ensemble, while the other 5% corresponds to the state having the LID unfolded.
The population of the folded state was decreased by mutations and high tempera-
tures. Another important observation is that binding affinity and catalytic rate can
be decoupled. Higher catalytic rates can arise even if binding affinity is maintained
(A73G). Last but not least, our research supports the view of allostery as the ef-
fect of structural flexibility modulation rather than the effect of crystallographic
100
distortion. That is, allostery can arise by affecting the excited states without any
crystallographic distortion.
7.2 Future directions and experiments
In this dissertation, we investigated allostery and its mechanisms. However, one
question arises, how local unfolding can promote higher kcat values? What is(are)
the mechanisms behind this effects? Our simulations suggest that faster release
of products is the underlying mechanism. To answer the above questions and test
our prediction, CPMG relaxation dispersion NMR experiments (to determine kLID)
along with enzyme kinetics assays (to measure kcat) can be performed in WT and
compared with results of A55G, A73G and A73G/V142G.
Our data also show a trend regarding binding affinity constants (Ka) and cat-
alytic activity rates (kcat) in AK. It is observed that mutations in the LID change
Ka but not kcat; and, that mutations in the CORE and AMPbd have little or no
effect on Ka but the increase kcat. Characterization of A99G (CORE) and A37G
(AMPbd) can confirm this trend. Finally, to characterize the coupling between
the AMPbd and the rest of the enzyme, a DSC experiment can be performed in a
construct at which the AMPbd has been removed.
101
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Appendix 1. Code in R to fit a
DSC profile using a three state
model
108
109
110
111
112
To run this code, we should type:
> R> source( DSC 3s!)The following steps show how to use the R code:
(a) Select for points to determine the baseline (b) The baseline is plotted
(c) The < ∆Cp,Tr > is plotted (d) Fitting parameters are determined
113
Appendix 2. Code in R to fit a
DSC profile using a two state
model
This code is run in the same way as the previous code.
114
115
116
117
118
Appendix 3. Two state model
test in WT
Figure 7.1: Comparisson between the area under the data points (∆Hcal) andthe van’t Hoff enthalpy (∆HvH), determined from a two state model. The ratio∆Hcal/∆HvH greater than one indicates the presence of at least one intermediatestate.
119
Appendix 4. Reversibility test
Reversibility was tested by determining the percentage of the DSC profile arearecovered after reheating the protein sample. If the area is completely recovered,the thermal unfolding is reversible. If no area is recovered after the second scan,the unfolding is therefore irreversible. The extent of reversibility of AK constructswere between 70-82%.
(a) WT (b) A73G/V142G
(c) V135G/V142G (d) LIDLESS
120
To know whether irreversibility is the effect of high temperatures or is inherentto the unfolding process [24, 25], AK was heated up to a temperature equal to 3 higher than the melting temperature of the last peak. Then the sample is cooleddown and reheated up to a high temperature (≈ 80 for AK). Our results indicatethat irreversibility is caused by the effects of high temperatures and predominatelyappears after the AK was unfolded. High temperature effects include misfoldedstructure, peptide bond hydrolysis and other chemical alteration of residues, [25,26].
(a) WT (b) A73G/V142G
(c) V135G/V142G (d) LIDLESS
121
122
123