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SMOG 2: A versatile software package for generating structure-based models

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Item Type:Article
Title:SMOG 2: A versatile software package for generating structure-based models
Creators Name:Noel, J.K., Levi, M., Raghunathan, M., Lammert, H., Hayes, R.L., Onuchic, J.N. and Whitford, P.C.
Abstract:Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.
Keywords:Algorithms, Chemical Models, Molecular Dynamics Simulation, Protein Conformation, Proteins, Software, Software Design, Software Validation
Source:PLoS Computational Biology
ISSN:1553-734X
Publisher:Public Library of Science
Volume:12
Number:3
Page Range:e1004794
Date:10 March 2016
Official Publication:https://doi.org/10.1371/journal.pcbi.1004794
PubMed:View item in PubMed

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