Gromacs 4.5
Sander Pronk,Szilárd Páll,Szilárd Páll,Roland Schulz,Roland Schulz,Per Larsson,Pär Bjelkmar,Pär Bjelkmar,Rossen Apostolov,Rossen Apostolov,Michael R. Shirts,Jeremy C. Smith,Jeremy C. Smith,Peter M. Kasson,David van der Spoel,David van der Spoel,Berk Hess,Berk Hess,Erik Lindahl,Erik Lindahl,Erik Lindahl +20 more
TLDR
A range of new simulation algorithms and features developed during the past 4 years are presented, leading up to the GROMACS 4.5 software package, which provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.Abstract:
Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources.
Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.
Availability: GROMACS is an open source and free software available from http://www.gromacs.org.
Contact: erik.lindahl@scilifelab.se
Supplementary information:Supplementary data are available at Bioinformatics online.read more
Citations
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GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers
Mark Abraham,Teemu Murtola,Roland Schulz,Roland Schulz,Szilárd Páll,Jeremy C. Smith,Jeremy C. Smith,Berk Hess,Erik Lindahl,Erik Lindahl +9 more
TL;DR: GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules, and provides a rich set of calculation types.
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g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations.
TL;DR: A new tool, g_mmpbsa, which implements the MM-PBSA approach using subroutines written in-house or sourced from the GROMACS and APBS packages is described, and the calculated interaction energy of 37 structurally diverse HIV-1 protease inhibitor complexes is compared.
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The Atomic Simulation Environment - A Python library for working with atoms
Ask Hjorth Larsen,Ask Hjorth Larsen,Jens Jørgen Mortensen,Jakob Blomqvist,Ivano E. Castelli,Rune Christensen,Marcin Dulak,Jesper Friis,Michael N. Groves,Bjørk Hammer,Cory Hargus,Eric D. Hermes,Paul C. Jennings,Peter Bjerre Jensen,James R. Kermode,John R. Kitchin,Esben L. Kolsbjerg,Joseph Kubal,Kristen Kaasbjerg,Steen Lysgaard,Jon Bergmann Maronsson,Tristan Maxson,Thomas Olsen,Lars Pastewka,Andrew A. Peterson,Carsten Rostgaard,Jakob Schiøtz,Ole Schütt,Mikkel Strange,Kristian Sommer Thygesen,Tejs Vegge,Lasse B. Vilhelmsen,Michael Walter,Zhenhua Zeng,Karsten Wedel Jacobsen +34 more
TL;DR: The atomic simulation environment (ASE) provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.
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Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics
TL;DR: Deep potential molecular dynamics (DPMD) as discussed by the authors is based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data.
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PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models.
Martin K. Scherer,Benjamin Trendelkamp-Schroer,Fabian Paul,Guillermo Pérez-Hernández,Moritz Hoffmann,Nuria Plattner,Christoph Wehmeyer,Jan-Hendrik Prinz,Frank Noé +8 more
TL;DR: The open-source Python package PyEMMA is presented, derived a systematic and accurate way to coarse-grain MSMs to few states and to illustrate the structures of the metastable states of the system.
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