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Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems
Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investig...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712783/ https://www.ncbi.nlm.nih.gov/pubmed/29225431 http://dx.doi.org/10.6026/97320630013380 |
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author | Thakur, Zoozeal Dharra, Renu Saini, Vandana Kumar, Ajit Mehta, Promod K. |
author_facet | Thakur, Zoozeal Dharra, Renu Saini, Vandana Kumar, Ajit Mehta, Promod K. |
author_sort | Thakur, Zoozeal |
collection | PubMed |
description | Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investigated. The topological properties of PPI network were examined by 'Network analyzer' a cytoscape plugin app and STRING database. The key enriched biological processes and the molecular functions of Mtb TA systems were analyzed by STRING. Manual curation of the PPI data identified four proteins (i.e. Rv2762c, VapB14, VapB42 and VapC42) to possess the highest number of interacting partners. The top 15% hub proteins were identified in the PPI network by employing two statistical measures, i.e. betweenness and radiality by employing cytohubba. Insights gained from the molecular protein models of VapC9 and VapC10 are also documented. |
format | Online Article Text |
id | pubmed-5712783 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-57127832017-12-08 Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems Thakur, Zoozeal Dharra, Renu Saini, Vandana Kumar, Ajit Mehta, Promod K. Bioinformation Hypothesis Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investigated. The topological properties of PPI network were examined by 'Network analyzer' a cytoscape plugin app and STRING database. The key enriched biological processes and the molecular functions of Mtb TA systems were analyzed by STRING. Manual curation of the PPI data identified four proteins (i.e. Rv2762c, VapB14, VapB42 and VapC42) to possess the highest number of interacting partners. The top 15% hub proteins were identified in the PPI network by employing two statistical measures, i.e. betweenness and radiality by employing cytohubba. Insights gained from the molecular protein models of VapC9 and VapC10 are also documented. Biomedical Informatics 2017-11-30 /pmc/articles/PMC5712783/ /pubmed/29225431 http://dx.doi.org/10.6026/97320630013380 Text en © 2017 Biomedical Informatics http://creativecommons.org/licenses/by/3.0/ This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Hypothesis Thakur, Zoozeal Dharra, Renu Saini, Vandana Kumar, Ajit Mehta, Promod K. Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title | Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title_full | Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title_fullStr | Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title_full_unstemmed | Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title_short | Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems |
title_sort | insights from the protein-protein interaction network analysis of mycobacterium tuberculosis toxin-antitoxin systems |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712783/ https://www.ncbi.nlm.nih.gov/pubmed/29225431 http://dx.doi.org/10.6026/97320630013380 |
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