Literature DB >> 25762327

Speed of conformational change: comparing explicit and implicit solvent molecular dynamics simulations.

Ramu Anandakrishnan1, Aleksander Drozdetski2, Ross C Walker3, Alexey V Onufriev4.   

Abstract

Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between ∼1- and ∼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, ∼1- to 60-fold, and ∼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.
Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 25762327      PMCID: PMC4375717          DOI: 10.1016/j.bpj.2014.12.047

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  70 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Implicit solvation based on generalized Born theory in different dielectric environments.

Authors:  Michael Feig; Wonpil Im; Charles L Brooks
Journal:  J Chem Phys       Date:  2004-01-08       Impact factor: 3.488

3.  Improving Convergence of Replica-Exchange Simulations through Coupling to a High-Temperature Structure Reservoir.

Authors:  Asim Okur; Daniel R Roe; Guanglei Cui; Viktor Hornak; Carlos Simmerling
Journal:  J Chem Theory Comput       Date:  2007-03       Impact factor: 6.006

4.  Insight into the role of hydration on protein dynamics.

Authors:  Donald Hamelberg; Tongye Shen; J Andrew McCammon
Journal:  J Chem Phys       Date:  2006-09-07       Impact factor: 3.488

5.  Coupling of replica exchange simulations to a non-Boltzmann structure reservoir.

Authors:  Adrian E Roitberg; Asim Okur; Carlos Simmerling
Journal:  J Phys Chem B       Date:  2007-02-15       Impact factor: 2.991

Review 6.  Biomolecular simulation: a computational microscope for molecular biology.

Authors:  Ron O Dror; Robert M Dirks; J P Grossman; Huafeng Xu; David E Shaw
Journal:  Annu Rev Biophys       Date:  2012       Impact factor: 12.981

Review 7.  The protein folding problem.

Authors:  Ken A Dill; S Banu Ozkan; M Scott Shell; Thomas R Weikl
Journal:  Annu Rev Biophys       Date:  2008       Impact factor: 12.981

Review 8.  Equilibrium sampling in biomolecular simulations.

Authors:  Daniel M Zuckerman
Journal:  Annu Rev Biophys       Date:  2011       Impact factor: 12.981

9.  Generalized born model with a simple smoothing function.

Authors:  Wonpil Im; Michael S Lee; Charles L Brooks
Journal:  J Comput Chem       Date:  2003-11-15       Impact factor: 3.376

10.  H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations.

Authors:  Ramu Anandakrishnan; Boris Aguilar; Alexey V Onufriev
Journal:  Nucleic Acids Res       Date:  2012-05-08       Impact factor: 16.971

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  43 in total

1.  Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation.

Authors:  R B Pandey; D J Jacobs; B L Farmer
Journal:  J Chem Phys       Date:  2017-05-21       Impact factor: 3.488

2.  Partially Assembled Nucleosome Structures at Atomic Detail.

Authors:  Georgy N Rychkov; Andrey V Ilatovskiy; Igor B Nazarov; Alexey V Shvetsov; Dmitry V Lebedev; Alexander Y Konev; Vladimir V Isaev-Ivanov; Alexey V Onufriev
Journal:  Biophys J       Date:  2016-12-28       Impact factor: 4.033

3.  Explicit ions/implicit water generalized Born model for nucleic acids.

Authors:  Igor S Tolokh; Dennis G Thomas; Alexey V Onufriev
Journal:  J Chem Phys       Date:  2018-05-21       Impact factor: 3.488

4.  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

5.  Implicit Solvent Model for Million-Atom Atomistic Simulations: Insights into the Organization of 30-nm Chromatin Fiber.

Authors:  Saeed Izadi; Ramu Anandakrishnan; Alexey V Onufriev
Journal:  J Chem Theory Comput       Date:  2016-11-07       Impact factor: 6.006

Review 6.  Generalized Born Implicit Solvent Models for Biomolecules.

Authors:  Alexey V Onufriev; David A Case
Journal:  Annu Rev Biophys       Date:  2019-03-11       Impact factor: 12.981

7.  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

8.  Multivalent ion-mediated nucleic acid helix-helix interactions: RNA versus DNA.

Authors:  Yuan-Yan Wu; Zhong-Liang Zhang; Jin-Si Zhang; Xiao-Long Zhu; Zhi-Jie Tan
Journal:  Nucleic Acids Res       Date:  2015-05-27       Impact factor: 16.971

9.  Nucleosome Histone Tail Conformation and Dynamics: Impacts of Lysine Acetylation and a Nearby Minor Groove Benzo[a]pyrene-Derived Lesion.

Authors:  Iwen Fu; Yuqin Cai; Nicholas E Geacintov; Yingkai Zhang; Suse Broyde
Journal:  Biochemistry       Date:  2017-03-22       Impact factor: 3.162

10.  A Structural, Functional, and Computational Analysis of BshA, the First Enzyme in the Bacillithiol Biosynthesis Pathway.

Authors:  Kelsey R Winchell; Paul W Egeler; Andrew J VanDuinen; Luke B Jackson; Mary E Karpen; Paul D Cook
Journal:  Biochemistry       Date:  2016-08-11       Impact factor: 3.162

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