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Chem 590 module NMR analysis of dynamic systems Outline A. Intro to dynamic systems B. Stoichiometry and K assoc by NMR C. Thermodynamic parameters by NMR D. Assembly kinetics by NMR E. Other techniques — Student presentations UV-Vis Fluorescence Isothermal titration calorimetry Potentiometry

Chem 590 moduleNMR analysis of dynamic systems Outline A. Intro to dynamic systems

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Chem 590 moduleNMR analysis of dynamic systems Outline A. Intro to dynamic systems B . Stoichiometry and K assoc by NMR C . Thermodynamic parameters by NMR D. Assembly kinetics by NMR E. Other techniques — Student presentations UV-Vis Fluorescence - PowerPoint PPT Presentation

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Page 1: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Chem 590 module NMR analysis of dynamic systems

Outline

A. Intro to dynamic systems

B. Stoichiometry and Kassoc by NMRC. Thermodynamic parameters by NMRD. Assembly kinetics by NMR E. Other techniques — Student presentations

UV-VisFluorescenceIsothermal titration calorimetryPotentiometry

Page 2: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Learning Aims

A. Become familiar with dynamic systems and the meanings of the quantities used to characterize them.B1. De-mystify the black-box of Kassoc determinations by all methods. B2. Obtain in-depth understanding of the math and models for 1:1 binding equilibria.B3. Understand the mathematics of the 1:1 binding isotherm, its applications, and its limitations.B4. Gain a comprehensive understanding of how d arises when looking at dynamic systems. B5. Get practical, step-by-step instructions for determining stoichiometry and Kassoc by NMR. C. Learn how NMR can be used to determine ∆H and ∆S for a given equilibrium D. Achieve a beginner-level understanding of studying kinetics by NMR. The goal is to allow you to understand literature, not to teach you how to do the experiments.E. Get a beginner-level understanding of other methods for determining Kassoc

UV-Vis, Fluorescence, Isothermal titration calorimetry, Potentiometry

Page 3: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Dynamic systems and supramolecular chemistry

Page 4: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Dynamic systems are driven by weak interactions

Electrostatic interactions

Dispersive forces

Hydrogen bonds

Aromatic-aromatic interactions and cation-pi interactions

The hydrophobic effect

+–+–+ –

Ion–Dipole interactions

Dipole–Dipole interactions

Page 5: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

6 H4L + 4 Ga(acac)3 + 12 KOH + 12 Et4NCl K5[Et4N]7[Ga4L6] (+ H2O, KCl, etc)

H4L [Ga4L6]12–

A complex metal-ligand assembly

Page 6: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A chiral guest allows resolution into enantiomeric cages

Et4N@[Ga4L6] + nicotine@[Ga4L6] nicotine@ ∆∆∆∆-[Ga4L6]

Resolution of diastereomers

Guest exchange

Et4N@ ∆∆∆∆-[Ga4L6]

Exchange back to achiral guest without loss of host chirality

Page 7: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exchange of L1 for L2 occurs without complete disassembly

Et4N@ ∆∆∆∆-[Ga4L16] + 6 L2 Et4N@ ∆∆∆∆-[Ga4L2

6] + 6 L1

Page 8: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Cation-π interactions: Factor Xa – inhibitor binding

Aromatic cage

Kd = 0.28 M Kd = 29 M

S4 pocket-lined by aromatic residues

Page 9: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Lysozyme mutants fold more weakly when hydrophobic groups are shrunk down to Ala

∆∆G correlates with hydrophobic (interfacial) surface area!

15-20 cal/mol for each Å2

Page 10: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Cyclodextrin hosts bind hydrophobic guests with different contributions from ∆H and T∆S

Page 11: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Rates of exchange and NMR

N-methylformamide (left) and methyl formate (right) in CDCl3 at 90 MHz

Page 12: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Calculated barriers to rotation

0

5

10

15

20

25

-180 -120 -60 0 60 120 180Dihedral angle (degrees)

Rel. energy (kcal/mol)

ThioesterEsterAmide

transcistrans

HF 3-21G

(Gas phase) cistrans

Page 13: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Rates change as a function of temperature

Variable temperature NMR of DMF

Page 14: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Slow exchange: integration to determine complex stoichiometry

*

Integration of methoxy (*) and adamantane (•) signals gave a 4:1 molar ratio.

(Later confirmed by X-ray)

*

Page 15: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A Practical Guide — Job plot sample prep

cA

cA•∆d

1. Prepare stocks[A stock] = 5 mM[B stock] = 5 mM

2. Create samples with fixed [At + Bt] as below:

3. Record Dd, calculate Dd•cA, Plot as shown at right

Page 16: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

More Examples of Job Plot Data

Page 17: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Diffusion-Ordered SpectroscopY (DOSY)

Stokes-Einstein relationship: D = kT / 6πhRH

D = diffusion coefficientk = Boltzmann constanth = solvent viscosity RH = hydrodynamic radius, which can be related to MW by calibration on related molecules

Page 18: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

DOSY for a host-guest complex

Page 19: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A system in fast exchange – real data for dfree and dbound

[peptide]t = 1 mM

Page 20: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Hypothetical curves for f11 vs. conc. plots based on the generalized 1:1 binding isotherm

Page 21: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exemplary NMR Titration Data

Schalley et al. Chem. Eur. J. 2003, 9, 1332.

Average Kassoc = 180 M–1

Page 22: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A Practical Guide — Sample preparation

Choose starting concentrations

1. Prepare 5 mL of stock A2. Remove 0.6 mL of stock and put in NMR tube3. Calculate amount of B needed to make 4 mL of B at 30x [A] 4. Weigh that amount of B into vial, and dissolve in 4 mL of stock A5. Transfer that titrant into a gas-tight 100 or 250 uL syringe

All of this ensures that At stays constant throughout titration.

1.

2. 3. 4.

Page 23: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A Practical Guide — Titration

1. Record NMR to determine dfree

2. Add 10 uL of titrant3. Record NMR again4. Repeat…

Hints: -You want to observe a significant Dd with each

addition. You want lots of data points on the curved part of the isotherm. You want to get as close to saturation as possible. This will require making judgments on the fly and increasing the amount you add as you go along. It is not unusual for the increments to start at 10 uL and to be 250 uL by the end of the titration.

- Mix well at each addition (invert >5 times). Mixing is slow in a narrow NMR tube.

Page 24: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

A Practical Guide — Data Analysis

1. In a spreadsheet, record dobs and total volume of titrant added for each spectrum.2. Convert to the y and x values needed for plotting, Ddobs and Bt.3. Input these two columns of data into Origin.4. Fit to the 1:1 binding isotherm to determine the parameters Ddmax and Kassoc. Be sure to try a few different initial guesses. Be sure to check the quality of fit. If you haven’t already done so, confirm stoichiometry by Job plot or other method.

Page 25: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exemplary Data — van’t Hoff Plots

Normally 4-5 values for T are enough

Rafaella Faraoni, PhD thesis, ETH Zurich

Page 26: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exemplary Data — Very Slow Exchange Kinetics

Exchange of guest P (complex 1•P•1; triangles) for guest A (complex 1•A•1; squares) was followed over 4 hours taking a new NMR measurement every 5 minutes.

Rebek et al. Proc. Nat. Acad. Sci. USA 1999, 96, 8344.

Page 27: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

NMR Line-Shape Analysis

A = intensity of NMR signal (y axis)

w= frequency (x axis)

M0 = some magnetization constant, determined in a separate experiment

W1 = wobs–w0 for signal 1 (offset)W2 = wobs–w0 for signal 2 (offset)

At a given temperature where intermediate exchange is observed, k = k1 + k–1 can be determined by fitting:

Page 28: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exemplary Data — NMR Line-Shape Analysis

k = 17.5 s–1

k = 735 s–1

k ~ 3500 s–1

- Red traces are fitted curves, black traces are actual data.- There is a built-in module in TOPSPIN that does this fitting (CG?).

Page 29: Chem  590 moduleNMR analysis of dynamic systems Outline A. Intro  to dynamic systems

Exemplary EXSY data for guest exchange

Integrate 3D on-axis peaks and cross peaks to obtain k1 and k–1

See Perrin, C. L.; Dwyer, T. J. Chem. Rev. 1990, 90, 935-967 for a review

“Meout” “Mein”