Literature DB >> 15268227

Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules.

Donald Hamelberg1, John Mongan, J Andrew McCammon.   

Abstract

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution. (c)2004 American Institute of Physics.

Mesh:

Year:  2004        PMID: 15268227     DOI: 10.1063/1.1755656

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  413 in total

1.  Energy landscape of the prion protein helix 1 probed by metadynamics and NMR.

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Journal:  Biophys J       Date:  2012-01-03       Impact factor: 4.033

2.  Molecular simulation methods in drug discovery: a prospective outlook.

Authors:  Xavier Barril; F Javier Luque
Journal:  J Comput Aided Mol Des       Date:  2011-12-08       Impact factor: 3.686

3.  Nucleotide-dependent mechanism of Get3 as elucidated from free energy calculations.

Authors:  Jeff Wereszczynski; J Andrew McCammon
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-30       Impact factor: 11.205

4.  Resolving the complex role of enzyme conformational dynamics in catalytic function.

Authors:  Urmi Doshi; Lauren C McGowan; Safieh Tork Ladani; Donald Hamelberg
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-26       Impact factor: 11.205

5.  Multiscale ensemble modeling of intrinsically disordered proteins: p53 N-terminal domain.

Authors:  Tsuyoshi Terakawa; Shoji Takada
Journal:  Biophys J       Date:  2011-09-20       Impact factor: 4.033

6.  An improved structural characterisation of reduced French bean plastocyanin based on NMR data and local-elevation molecular dynamics simulation.

Authors:  Denise Steiner; Wilfred F van Gunsteren
Journal:  Eur Biophys J       Date:  2012-06-16       Impact factor: 1.733

Review 7.  Taming the complexity of protein folding.

Authors:  Gregory R Bowman; Vincent A Voelz; Vijay S Pande
Journal:  Curr Opin Struct Biol       Date:  2011-02       Impact factor: 6.809

8.  Allosteric Control of a Plant Receptor Kinase through S-Glutathionylation.

Authors:  Alexander S Moffett; Kyle W Bender; Steven C Huber; Diwakar Shukla
Journal:  Biophys J       Date:  2017-12-05       Impact factor: 4.033

Review 9.  Molecular dynamics simulations in photosynthesis.

Authors:  Nicoletta Liguori; Roberta Croce; Siewert J Marrink; Sebastian Thallmair
Journal:  Photosynth Res       Date:  2020-04-15       Impact factor: 3.573

10.  Molecular dynamics simulations of lipid nanodiscs.

Authors:  Mohsen Pourmousa; Richard W Pastor
Journal:  Biochim Biophys Acta Biomembr       Date:  2018-05-03       Impact factor: 3.747

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