Literature DB >> 16323162

Monte Carlo simulations of biomolecules: The MC module in CHARMM.

Jie Hu1, Ao Ma, Aaron R Dinner.   

Abstract

We describe the implementation of a general and flexible Monte Carlo (MC) module for the program CHARMM, which is used widely for modeling biomolecular systems with empirical energy functions. Construction and use of an almost arbitrary move set with only a few commands is made possible by providing several predefined types of moves that can be combined. Sampling can be enhanced by noncanonical acceptance criteria, automatic optimization of step sizes, and energy minimization. A systematic procedure for improving MC move sets is introduced and applied to simulations of two peptides. The resulting move sets allow MC to sample the configuration spaces of these systems much more rapidly than Langevin dynamics. The rate of convergence of the difference in free energy between ethane and methanol in explicit solvent is also examined, and comparable performances are observed for MC and the Nosé-Hoover algorithm. Its ease of use combined with its sampling efficiency make the MC module in CHARMM an attractive alternative for exploring the behavior of biomolecular systems. Copyright 2005 Wiley Periodicals, Inc.

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Year:  2006        PMID: 16323162     DOI: 10.1002/jcc.20327

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  14 in total

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Review 2.  CHARMM: the biomolecular simulation program.

Authors:  B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus
Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

3.  Coordinate-dependent diffusion in protein folding.

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4.  Monte Carlo simulation of mixed nonionic Brij surfactants in water.

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5.  Methods for Monte Carlo simulations of biomacromolecules.

Authors:  Andreas Vitalis; Rohit V Pappu
Journal:  Annu Rep Comput Chem       Date:  2009-01-01

Review 6.  Equilibrium sampling in biomolecular simulations.

Authors:  Daniel M Zuckerman
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7.  Monte Carlo, harmonic approximation, and coarse-graining approaches for enhanced sampling of biomolecular structure.

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Journal:  F1000 Biol Rep       Date:  2009-06-29

8.  Myosin dynamics on the millisecond time scale.

Authors:  Thomas P Burghardt; Jimmy Yan Hu; Katalin Ajtai
Journal:  Biophys Chem       Date:  2007-09-11       Impact factor: 2.352

9.  Impact of electronic polarizability on protein-functional group interactions.

Authors:  Himanshu Goel; Wenbo Yu; Vincent D Ustach; Asaminew H Aytenfisu; Delin Sun; Alexander D MacKerell
Journal:  Phys Chem Chem Phys       Date:  2020-04-06       Impact factor: 3.676

10.  Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions.

Authors:  Orlando Acevedo; William L Jorgensen
Journal:  Acc Chem Res       Date:  2010-01-19       Impact factor: 22.384

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