Literature DB >> 30514080

Why Computed Protein Folding Landscapes Are Sensitive to the Water Model.

Ramu Anandakrishnan1, Saeed Izadi2, Alexey V Onufriev3.   

Abstract

We investigate the effect of solvent models on the computed thermodynamics of protein folding. Atomistic folding simulations of a fast-folding mini-protein, CLN025, were employed to compare two commonly used explicit solvent water models, TIP3P and TIP4P/Ew, and one implicit solvent (AMBER generalized Born) model. Although all three solvent models correctly identify the same native folded state (RMSD = 1.5 ± 0.1 Å relative to the experimental structure), the corresponding free energy landscapes vary drastically between water models: almost an order-of-magnitude difference is seen in the predicted fraction of the unfolded state between the two explicit solvent models, with even larger differences between the implicit and the explicit models. Quantitative arguments are presented for why the sensitivity is expected to hold for other proteins, as well as for other conformational transitions involving large changes in solvent exposed areas such as protein-ligand binding. Comparing protein-solvent and solvent-solvent contributions to the folding energy between different water models, water-water electrostatic interactions are identified as the largest contributor to the differences in the predicted folding energy, which helps explain the strong sensitivity of the folding landscape to subtle details of the water model. For the two explicit solvent models, differences in water model parameters also result in the average number of water molecules surrounding the protein being noticeably different. Water models that poorly reproduce certain bulk properties of liquid water such as self-diffusion are likely to misrepresent water-water interactions; we argue that within a pairwise additive energy function this error cannot, in general, be compensated by an adjustment to the solute-solute and solute-solvent parts of the energy.

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Year:  2018        PMID: 30514080     DOI: 10.1021/acs.jctc.8b00485

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  8 in total

1.  Computational Estimation of Microsecond to Second Atomistic Folding Times.

Authors:  Upendra Adhikari; Barmak Mostofian; Jeremy Copperman; Sundar Raman Subramanian; Andrew A Petersen; Daniel M Zuckerman
Journal:  J Am Chem Soc       Date:  2019-04-12       Impact factor: 15.419

2.  Exploring Conformational Change of Adenylate Kinase by Replica Exchange Molecular Dynamic Simulation.

Authors:  Jinan Wang; Cheng Peng; Yuqu Yu; Zhaoqiang Chen; Zhijian Xu; Tingting Cai; Qiang Shao; Jiye Shi; Weiliang Zhu
Journal:  Biophys J       Date:  2020-01-09       Impact factor: 4.033

Review 3.  Water in Nanopores and Biological Channels: A Molecular Simulation Perspective.

Authors:  Charlotte I Lynch; Shanlin Rao; Mark S P Sansom
Journal:  Chem Rev       Date:  2020-08-25       Impact factor: 60.622

4.  Significant compaction of H4 histone tail upon charge neutralization by acetylation and its mimics, possible effects on chromatin structure.

Authors:  Parviz Seifpanahi Shabane; Alexey V Onufriev
Journal:  J Mol Biol       Date:  2020-10-21       Impact factor: 5.469

5.  Exploring optimization strategies for improving explicit water models: Rigid n-point model and polarizable model based on Drude oscillator.

Authors:  Yeyue Xiong; Alexey V Onufriev
Journal:  PLoS One       Date:  2019-11-14       Impact factor: 3.240

6.  Effect of Water Models on Transmembrane Self-Assembled Cyclic Peptide Nanotubes.

Authors:  Martin Calvelo; Charlotte I Lynch; Juan R Granja; Mark S P Sansom; Rebeca Garcia-Fandiño
Journal:  ACS Nano       Date:  2021-03-19       Impact factor: 18.027

7.  Understanding the role of water on temperature-dependent structural modifications of SARS CoV-2 main protease binding sites.

Authors:  Pushyaraga P Venugopal; Omkar Singh; Debashree Chakraborty
Journal:  J Mol Liq       Date:  2022-07-20       Impact factor: 6.633

8.  Sampling of the conformational landscape of small proteins with Monte Carlo methods.

Authors:  Nana Heilmann; Moritz Wolf; Mariana Kozlowska; Elaheh Sedghamiz; Julia Setzler; Martin Brieg; Wolfgang Wenzel
Journal:  Sci Rep       Date:  2020-10-23       Impact factor: 4.379

  8 in total

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