GENESIS 1.1: A hybrid‐parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms. Issue 25 (18th July 2017)

• Record Type: Journal Article
• Authors: Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji
• Is Part Of: Journal of computational chemistry. Volume 38:Issue 25(2017)
• Page Start: 2193
• Page End: 2206
• Publication Date: 2017-07-18
• Subjects: molecular dynamics -- string method -- replica exchange molecular dynamics -- graphics processing unit -- multiple time step integration; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.24874
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract : GENeralized‐Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all‐atom and coarse‐grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time‐step integration, and hybrid (CPU + GPU) computing. The string method and replica‐exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free‐energy pathway and obtaining free‐energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. Abstract : We updated GENESIS software for molecular dynamics simulations of biological systems. In the update, AMBER force fields and several coarse‐grained models become available. The performance has been greatly improved by the use of multiple time‐step integration and hybrid (CPU + GPU) computing. The string method and replica‐exchange umbrella sampling with flexible collective variable choice are also implemented for free‐energy analysis on large conformational changes of proteins and nucleic acids.