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      myPresto/omegagene 2020: a molecular dynamics simulation engine for virtual-system coupled sampling

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          Abstract

          The molecular dynamics (MD) method is a promising approach for investigating the molecular mechanisms of microscopic phenomena. In particular, generalized ensemble MD methods can efficiently explore the conformational space with a rugged free-energy surface. However, the implementation and acquisition of technical knowledge for each generalized ensemble MD method are not straightforward for end-users. Here, we present a new version of the myPresto/omegagene software, which is an MD simulation engine tailored for a series of generalized ensemble methods, which are virtual-system coupled multicanonical MD (V-McMD), virtual-system coupled adaptive umbrella sampling (V-AUS), and virtual-system coupled canonical MD (VcMD). This program has been applied in several studies analyzing free-energy landscapes of a variety of molecular systems with all-atom simulations. The updated version provides new functionality for coarse-grained simulations powered by the hydrophobicity scale method. The software package includes a step-by-step tutorial document for enhanced conformational sampling of the poly-glutamine (poly-Q) oligomer expressed as a one-bead per residue model. The myPresto/omegagene software is freely available at the following URL: https://github.com/kotakasahara/omegagene under the Apache2 license.

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          GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

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            Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

            We present an implementation of generalized Born implicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package that runs entirely on CUDA enabled NVIDIA graphics processing units (GPUs). We discuss the algorithms that are used to exploit the processing power of the GPUs and show the performance that can be achieved in comparison to simulations on conventional CPU clusters. The implementation supports three different precision models in which the contributions to the forces are calculated in single precision floating point arithmetic but accumulated in double precision (SPDP), or everything is computed in single precision (SPSP) or double precision (DPDP). In addition to performance, we have focused on understanding the implications of the different precision models on the outcome of implicit solvent MD simulations. We show results for a range of tests including the accuracy of single point force evaluations and energy conservation as well as structural properties pertainining to protein dynamics. The numerical noise due to rounding errors within the SPSP precision model is sufficiently large to lead to an accumulation of errors which can result in unphysical trajectories for long time scale simulations. We recommend the use of the mixed-precision SPDP model since the numerical results obtained are comparable with those of the full double precision DPDP model and the reference double precision CPU implementation but at significantly reduced computational cost. Our implementation provides performance for GB simulations on a single desktop that is on par with, and in some cases exceeds, that of traditional supercomputers.
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              Promoting transparency and reproducibility in enhanced molecular simulations

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                Author and article information

                Journal
                Biophys Physicobiol
                Biophys Physicobiol
                Biophysics and Physicobiology
                The Biophysical Society of Japan
                2189-4779
                2020
                15 October 2020
                : 17
                : 140-146
                Affiliations
                [1 ] College of Life Sciences, Ritsumeikan University , Kusatsu, Shiga 525-8577, Japan
                [2 ] Graduate School of Life Sciences, Ritsumeikan University , Kusatsu, Shiga 525-8577, Japan
                [3 ] Institute for Protein Research, Osaka University , Suita, Osaka 565-0871, Japan
                [4 ] Graduate School of Simulation Studies, University of Hyogo , Kobe, Hyogo 650-0047, Japan
                Author notes

                Edited by Akio Kitao

                Corresponding author: Kota Kasahara, College of Life Sciences, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577 Japan. e-mail: ktkshr@ 123456fc.ritsumei.ac.jp
                Article
                JST.JSTAGE/biophysico/BSJ-2020013 BSJ-2020013
                10.2142/biophysico.BSJ-2020013
                7671739
                33240741
                bc1d2d1f-009e-4ea5-904a-199efa7f84c9
                2020 THE BIOPHYSICAL SOCIETY OF JAPAN

                This article is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Inter­national License. To view a copy of this license, visit 
 https://creativecommons.org/licenses/by-nc-sa/4.0/.

                History
                : 15 June 2020
                : 10 October 2020
                Categories
                Database and Computer Program

                molecular simulation,software,generalized ensemble,high performance computing,gpgpu

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