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Title: GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

Journal Article · · Bioinformatics
 [1];  [1];  [2];  [3];  [4];  [1];  [3];  [2];  [3];  [5];  [1];  [6]
  1. Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden)
  2. Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Univ. of Virginia, Charlottesville, VA (United States)
  4. Science for Life Lab., Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)
  5. Science for Life Lab., Stockholm (Sweden); Uppsala Univ., Uppsala (Sweden)
  6. Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)

In this study, 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. As a result, 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.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; Work for Others (WFO)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1265941
Journal Information:
Bioinformatics, Vol. 29, Issue 7; ISSN 1367-4803
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English

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