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gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations
Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030995/ https://www.ncbi.nlm.nih.gov/pubmed/29800260 http://dx.doi.org/10.1093/nar/gky381 |
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author | Serçinoğlu, Onur Ozbek, Pemra |
author_facet | Serçinoğlu, Onur Ozbek, Pemra |
author_sort | Serçinoğlu, Onur |
collection | PubMed |
description | Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io. |
format | Online Article Text |
id | pubmed-6030995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60309952018-07-10 gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations Serçinoğlu, Onur Ozbek, Pemra Nucleic Acids Res Web Server Issue Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io. Oxford University Press 2018-07-02 2018-05-25 /pmc/articles/PMC6030995/ /pubmed/29800260 http://dx.doi.org/10.1093/nar/gky381 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Serçinoğlu, Onur Ozbek, Pemra gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title | gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title_full | gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title_fullStr | gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title_full_unstemmed | gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title_short | gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
title_sort | grinn: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030995/ https://www.ncbi.nlm.nih.gov/pubmed/29800260 http://dx.doi.org/10.1093/nar/gky381 |
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