Literature DB >> 29120630

How Well Can Implicit Solvent Simulations Explore Folding Pathways? A Quantitative Analysis of α-Helix Bundle Proteins.

Qiang Shao1,2, Weiliang Zhu1,2.   

Abstract

Protein folding has been posing challenges for molecular simulation for decades. Implicit solvent models are sought as routes to increase the capability of simulation, with trade-offs between computational speed and accuracy. Here, we systematically investigate the folding of a variety of α-helix bundle proteins ranging in size from 46 to 102 amino acids using a state-of-the-art force field and an implicit solvent model. The accurate all-atom simulated folding is enabled for six proteins, including for the first time a successful folding of protein with >100 amino acids in implicit solvent. The detailed free-energy landscape analysis sheds light on a set of general principles underlying the folding of α-helix bundle proteins, suggesting a hybrid framework/nucleation-condensation mechanism favorably adopted in implicit solvent condition. The similarities and discrepancies of the folding pathways measured among the present implicit solvent simulations and previously reported experiments and explicit solvent simulations are deeply analyzed, providing quantitative assessment for the availability and limitation of implicit solvent simulation in exploring the folding transition of large-size proteins.

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Year:  2017        PMID: 29120630     DOI: 10.1021/acs.jctc.7b00726

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


  3 in total

1.  Open-Boundary Molecular Dynamics of a DNA Molecule in a Hybrid Explicit/Implicit Salt Solution.

Authors:  Julija Zavadlav; Jurij Sablić; Rudolf Podgornik; Matej Praprotnik
Journal:  Biophys J       Date:  2018-04-09       Impact factor: 4.033

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

3.  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

  3 in total

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