Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.
ProtoMD: A prototyping toolkit for multiscale molecular dynamics

ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from Program summary Program title: ProtoMD Catalogue identifier: AEZN_v1_0 Program summary URL: Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 281345 No. of bytes in distributed program, including test data, etc.: 3706191 Distribution format: tar.gz Programming language: Python 2.7.3. Computer: x86/x86 64. Operating system: Linux. RAM: Depends on the size of the system being simulated and duration of the simulation (few MBs to TBs) Classification: 3, 4.12, 16.9, 23. External routines: GROMACS (tested with versions 4.6x and 5.0x), MDAnalysis, GromacsWrapper, numpy, scipy, MPI Nature of problem: Prototyping multiscale coarse-grained algorithms for molecular dynamics. Solution method: Combining the open-source GROMACS molecular dynamics package and the python based MDAnalysis library for running, debugging, and analyzing multiscale simulations Restrictions: The system under study must be characterized by a clear separation of timescales; otherwise, the multiscale algorithm fails to capture the slowly-varying modes. Running time: Depending on the problem size, simulations can take few hours to months. (C) 2016 Elsevier B.V. All rights reserved.


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