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pyProGA—A PyMOL plugin for protein residue network analysis
The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software w...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323899/ https://www.ncbi.nlm.nih.gov/pubmed/34329304 http://dx.doi.org/10.1371/journal.pone.0255167 |
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author | Sladek, Vladimir Yamamoto, Yuta Harada, Ryuhei Shoji, Mitsuo Shigeta, Yasuteru Sladek, Vladimir |
author_facet | Sladek, Vladimir Yamamoto, Yuta Harada, Ryuhei Shoji, Mitsuo Shigeta, Yasuteru Sladek, Vladimir |
author_sort | Sladek, Vladimir |
collection | PubMed |
description | The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga. |
format | Online Article Text |
id | pubmed-8323899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-83238992021-07-31 pyProGA—A PyMOL plugin for protein residue network analysis Sladek, Vladimir Yamamoto, Yuta Harada, Ryuhei Shoji, Mitsuo Shigeta, Yasuteru Sladek, Vladimir PLoS One Research Article The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga. Public Library of Science 2021-07-30 /pmc/articles/PMC8323899/ /pubmed/34329304 http://dx.doi.org/10.1371/journal.pone.0255167 Text en © 2021 Sladek et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Sladek, Vladimir Yamamoto, Yuta Harada, Ryuhei Shoji, Mitsuo Shigeta, Yasuteru Sladek, Vladimir pyProGA—A PyMOL plugin for protein residue network analysis |
title | pyProGA—A PyMOL plugin for protein residue network analysis |
title_full | pyProGA—A PyMOL plugin for protein residue network analysis |
title_fullStr | pyProGA—A PyMOL plugin for protein residue network analysis |
title_full_unstemmed | pyProGA—A PyMOL plugin for protein residue network analysis |
title_short | pyProGA—A PyMOL plugin for protein residue network analysis |
title_sort | pyproga—a pymol plugin for protein residue network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323899/ https://www.ncbi.nlm.nih.gov/pubmed/34329304 http://dx.doi.org/10.1371/journal.pone.0255167 |
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