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      myPresto/omegagene: a GPU-accelerated molecular dynamics simulator tailored for enhanced conformational sampling methods with a non-Ewald electrostatic scheme

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          Abstract

          Molecular dynamics (MD) is a promising computational approach to investigate dynamical behavior of molecular systems at the atomic level. Here, we present a new MD simulation engine named “myPresto/omegagene” that is tailored for enhanced conformational sampling methods with a non-Ewald electrostatic potential scheme. Our enhanced conformational sampling methods, e.g., the virtual-system-coupled multi-canonical MD (V-McMD) method, replace a multi-process parallelized run with multiple independent runs to avoid inter-node communication overhead. In addition, adopting the non-Ewald-based zero-multipole summation method (ZMM) makes it possible to eliminate the Fourier space calculations altogether. The combination of these state-of-the-art techniques realizes efficient and accurate calculations of the conformational ensemble at an equilibrium state. By taking these advantages, myPresto/omegagene is specialized for the single process execution with Graphics Processing Unit (GPU). We performed benchmark simulations for the 20-mer peptide, Trp-cage, with explicit solvent. One of the most thermodynamically stable conformations generated by the V-McMD simulation is very similar to an experimentally solved native conformation. Furthermore, the computation speed is four-times faster than that of our previous simulation engine, myPresto/psygene-G. The new simulator, myPresto/omegagene, is freely available at the following URLs: http://www.protein.osaka-u.ac.jp/rcsfp/pi/omegagene/ and http://presto.protein.osaka-u.ac.jp/myPresto4/.

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          A flexible algorithm for calculating pair interactions on SIMD architectures

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            Designing a 20-residue protein.

            Truncation and mutation of a poorly folded 39-residue peptide has produced 20-residue constructs that are >95% folded in water at physiological pH. These constructs optimize a novel fold, designated as the 'Trp-cage' motif, and are significantly more stable than any other miniprotein reported to date. Folding is cooperative and hydrophobically driven by the encapsulation of a Trp side chain in a sheath of Pro rings. As the smallest protein-like construct, Trp-cage miniproteins should provide a testing ground for both experimental studies and computational simulations of protein folding and unfolding pathways. Pro Trp interactions may be a particularly effective strategy for the a priori design of self-folding peptides.
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              Molecular Dynamics Simulations Accelerated by GPU for Biological Macromolecules with a Non-Ewald Scheme for Electrostatic Interactions.

              A molecular dynamics (MD) simulation program for biological macromolecules was implemented with a non-Ewald scheme for long-ranged electrostatic interactions and run on a general purpose graphics processing unit (GPU). We recently developed several non-Ewald methods to compute the electrostatic energies with high precision. In particular, the zero-dipole summation (ZD) method, which takes into account the neutralities of charges and dipoles in a truncated subset, enables the calculation of electrostatic interactions with high accuracy and low computational cost, and its algorithm is simple enough to be implemented in a GPU. We developed an MD program with the space decomposition algorithm, myPresto/psygene, and applied it to several biological macromolecular systems with GPUs implementing the ZD method. Rapid computing performance with high accuracy was obtained.
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                Author and article information

                Journal
                Biophys Physicobiol
                Biophys Physicobiol
                Biophysics and Physicobiology
                The Biophysical Society of Japan (BSJ)
                2189-4779
                2016
                07 September 2016
                : 13
                : 209-216
                Affiliations
                [1 ]College of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan
                [2 ]College of Engineering, University of Illinois, Urbana-Champaign, United States
                [3 ]School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan
                [4 ]Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
                [5 ]Technology Research Association for Next Generation Natural Products Chemistry, Tokyo 135-0064, Japan
                [6 ]Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan
                Author notes
                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
                13_209
                10.2142/biophysico.13.0_209
                5060096
                27924276
                faf681aa-652e-4977-ad82-339c715dec63
                © 2016 The Biophysical Society of Japan

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 June 2016
                : 08 August 2016
                Categories
                Database and Computer Program

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

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