A quantitative connection of experimental and simulated folding landscapes by vibrational spectroscopy

Davis, Caitlin; Zanetti-Polzi, Laura; Gruebele, Martin; Amadei, Andrea; Dyer, R. Brian; Daidone, Isabella

doi:10.1039/c8sc03786h

Cited by 20 publications

(20 citation statements)

References 68 publications

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“…Therefore, it is a very general method that can be applied to compute different observables. It has been in fact applied to model electron transfer thermodynamics and kinetics − as well as to compute absorption and emission spectra. − It has however to be pointed out that the accuracy of the overall approach relies on the accuracy of both the quantum chemical calculations needed to obtain the unperturbed QC properties and the force-field employed for the classical MD simulations…”

Section: Theory and Methodsmentioning

confidence: 99%

Fully Atomistic Multiscale Approach for pK_a Prediction

2020

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The ionization state of titratable amino acids strongly affects proteins structure and functioning in a large number of biological processes. It is therefore essential to be able to characterize the pK a of ionizable groups inside proteins and to understand its microscopic determinants in order to gain insights into many functional properties of proteins. A big effort has been devoted to the development of theoretical approaches for the prediction of deprotonation free energies, yet the accurate theoretical/computational calculation of pK a values is recognized as a current challenge. A methodology based on a hybrid quantum/classical approach is here proposed for the computation of deprotonation free energies. The method is applied to calculate the pK a of formic acid, methylammonium, and methanethiol, providing results in good agreement with the corresponding experimental estimates. The pK a is also calculated for aspartic acid and lysine as single residues in solution and for three aspartic/glutamic acids inside a well-characterized protein: hen egg white lysozyme. While for small molecules the method is able to deal with multiple protonation states of all titratable groups, this becomes computationally very expensive for proteins. The calculated pK a values for the single amino acids (except for the zwitterionic aspartic acid) and inside the protein display a systematic shift with respect to the experimental values that suggests that the fine balance between hydrophobic and polar interactions might be not accurately reproduced by the usual classical force-fields, thus affecting the computation of deprotonation free energies. The calculated pK a shifts inside the protein are in good agreement with the corresponding experimental ones (within 1 pK a unit), well reproducing the pK a changes due to the protein environment even in the case of large pK a shifts.

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Section: Theory and Methodsmentioning

confidence: 99%

Fully Atomistic Multiscale Approach for pK_a Prediction

2020

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“…two-thirds of the time, and hairpin 2 ca. one-third of the time . Thus, GTT is an ideal testbed for simulating the effect of cytoplasmic crowding and sticking on folding dynamics.…”

Section: Introductionmentioning

confidence: 99%

Crowding, Sticking, and Partial Folding of GTT WW Domain in a Small Cytoplasm Model

et al. 2020

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Recent experimental data has shown that protein folding in the cytoplasm can differ from in vitro folding with respect to speed, stability, and residual structure. Here we investigate the all-atom molecular dynamics (MD) simulations of 9 copies of the model protein GTT WW domain in a small bacterial cytoplasm model using three force fields. GTT has been well-studied by MD in aqueous solution for comparison. We find that folded copies remain folded for up 25 μs, whereas unfolded copies do not fold for up to 190 μs. Unfolded GTT in our cytoplasm model does populate partly folded intermediates with one of the two hairpins formed. Relative to aqueous solution, GTT gets stuck in metastable states with a small RMSD and radius of gyration and extensive burial of surface area against other macromolecules. In particular, GTT is even able to form transient intermolecular β-sheets with other proteins, resulting in a “chimeric structure” that could be a precursor to oligomeric β-aggregates. We conclude that sticking, enhanced by the non-native mutations of GTT, is largely responsible, and we propose, on the basis of our result as well as recent experiments, that coevolution of protein surfaces with their solvation environment (including chaperones) is important for folding and diffusion of proteins in the cytoplasm.

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“…In a nice study, the experimental and the calculated time-resolved IR spectra at multiple frequencies for the fast-folding of GTT35 protein was compared. The analysis shows that the IR signal is consistent with folding through intermediates and allows the determination of the corresponding kinetic parameters [ 123 ].…”

Section: Fluorescence Uv–vis and Infrared Spectroscopiesmentioning

confidence: 99%

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

2020

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Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.

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A quantitative connection of experimental and simulated folding landscapes by vibrational spectroscopy

Abstract: We break the barrier between simulation and experiment by comparing identical computed and experimental infrared observables.

Cited by 20 publications

References 68 publications

Fully Atomistic Multiscale Approach for pK_a Prediction

Fully Atomistic Multiscale Approach for pK_a Prediction

Crowding, Sticking, and Partial Folding of GTT WW Domain in a Small Cytoplasm Model

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

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A quantitative connection of experimental and simulated folding landscapes by vibrational spectroscopy

Abstract: We break the barrier between simulation and experiment by comparing identical computed and experimental infrared observables.

Cited by 20 publications

References 68 publications

Fully Atomistic Multiscale Approach for pKa Prediction

Fully Atomistic Multiscale Approach for pKa Prediction

Crowding, Sticking, and Partial Folding of GTT WW Domain in a Small Cytoplasm Model

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Contact Info

Product

Resources

About

Fully Atomistic Multiscale Approach for pK_a Prediction

Fully Atomistic Multiscale Approach for pK_a Prediction