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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...

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Detalles Bibliográficos
Autores principales: Thakur, Zoozeal, Dharra, Renu, Saini, Vandana, Kumar, Ajit, Mehta, Promod K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2017
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.
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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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