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Routine Access to Millisecond Time Scale Events with Accelerated Molecular Dynamics

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      Abstract

      In this work, we critically assess the ability of the all-atom enhanced sampling method accelerated molecular dynamics (aMD) to investigate conformational changes in proteins that typically occur on the millisecond time scale. We combine aMD with the inherent power of graphics processor units (GPUs) and apply the implementation to the bovine pancreatic trypsin inhibitor (BPTI). A 500 ns aMD simulation is compared to a previous millisecond unbiased brute force MD simulation carried out on BPTI, showing that the same conformational space is sampled by both approaches. To our knowledge, this represents the first implementation of aMD on GPUs and also the longest aMD simulation of a biomolecule run to date. Our implementation is available to the community in the latest release of the Amber software suite (v12), providing routine access to millisecond events sampled from dynamics simulations using off the shelf hardware.

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      Most cited references 28

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      Atomic-level characterization of the structural dynamics of proteins.

      Molecular dynamics (MD) simulations are widely used to study protein motions at an atomic level of detail, but they have been limited to time scales shorter than those of many biologically critical conformational changes. We examined two fundamental processes in protein dynamics--protein folding and conformational change within the folded state--by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equilibrium simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; separate simulations of the protein's constituent substructures shed light on possible determinants of this pathway. A 1-millisecond simulation of the folded protein BPTI reveals a small number of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.
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        Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules.

        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.
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          Bio3d: an R package for the comparative analysis of protein structures.

          An automated procedure for the analysis of homologous protein structures has been developed. The method facilitates the characterization of internal conformational differences and inter-conformer relationships and provides a framework for the analysis of protein structural evolution. The method is implemented in bio3d, an R package for the exploratory analysis of structure and sequence data. The bio3d package is distributed with full source code as a platform-independent R package under a GPL2 license from: http://mccammon.ucsd.edu/~bgrant/bio3d/
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            Author and article information

            Affiliations
            []Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, Urey Hall, La Jolla, California 92093-0365, United States
            []San Diego Supercomputer Center, University of California, San Diego, La Jolla, California 92093-0505, United States
            [§ ]Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California 92093, United States
            Author notes
            Journal
            J Chem Theory Comput
            J Chem Theory Comput
            ct
            jctcce
            Journal of Chemical Theory and Computation
            American Chemical Society
            1549-9618
            1549-9626
            27 July 2012
            11 September 2012
            : 8
            : 9
            : 2997-3002
            3438784
            22984356
            10.1021/ct300284c
            Copyright © 2012 American Chemical Society

            This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.

            Funding
            National Institutes of Health, United States
            Categories
            Article
            Custom metadata
            ct300284c
            ct-2012-00284c

            Computational chemistry & Modeling

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