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A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease of the synovial joints. Though the current RA therapeutics such as disease-modifying antirheumatic drugs (DMARDs), nonsteroidal anti-inflammatory drugs (NSAIDs) and biologics can halt the progression of the disease, none of these would eith...

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Autores principales: Panga, Venugopal, Raghunathan, Srivatsan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013252/
https://www.ncbi.nlm.nih.gov/pubmed/29928007
http://dx.doi.org/10.1371/journal.pone.0199530
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author Panga, Venugopal
Raghunathan, Srivatsan
author_facet Panga, Venugopal
Raghunathan, Srivatsan
author_sort Panga, Venugopal
collection PubMed
description Rheumatoid arthritis (RA) is a chronic inflammatory disease of the synovial joints. Though the current RA therapeutics such as disease-modifying antirheumatic drugs (DMARDs), nonsteroidal anti-inflammatory drugs (NSAIDs) and biologics can halt the progression of the disease, none of these would either dramatically reduce or cure RA. So, the identification of potential therapeutic targets and new therapies for RA are active areas of research. Several studies have discovered the involvement of cytokines in the pathogenesis of this disease. These cytokines induce signal transduction pathways in RA synovial fibroblasts (RASF). These pathways share many signal transducers and their interacting proteins, resulting in the formation of a signaling network. In order to understand the involvement of this network in RA pathogenesis, it is essential to identify the key transducers and their interacting proteins that are part of this network. In this study, based on a detailed literature survey, we have identified a list of 12 cytokines that induce signal transduction pathways in RASF. For these cytokines, we have built a signaling network using the protein-protein interaction (PPI) data that was obtained from public repositories such as HPRD, BioGRID, MINT, IntAct and STRING. By combining the network centrality measures with the gene expression data from the RA related microarrays that are available in the open source Gene Expression Omnibus (GEO) database, we have identified 24 key proteins of this signaling network. Two of these 24 are already drug targets for RA, and of the remaining, 12 have direct PPI links to some of the current drug targets of RA. Therefore, these key proteins seem to be crucial in the pathogenesis of RA and hence might be treated as potential drug targets.
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spelling pubmed-60132522018-07-06 A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis Panga, Venugopal Raghunathan, Srivatsan PLoS One Research Article Rheumatoid arthritis (RA) is a chronic inflammatory disease of the synovial joints. Though the current RA therapeutics such as disease-modifying antirheumatic drugs (DMARDs), nonsteroidal anti-inflammatory drugs (NSAIDs) and biologics can halt the progression of the disease, none of these would either dramatically reduce or cure RA. So, the identification of potential therapeutic targets and new therapies for RA are active areas of research. Several studies have discovered the involvement of cytokines in the pathogenesis of this disease. These cytokines induce signal transduction pathways in RA synovial fibroblasts (RASF). These pathways share many signal transducers and their interacting proteins, resulting in the formation of a signaling network. In order to understand the involvement of this network in RA pathogenesis, it is essential to identify the key transducers and their interacting proteins that are part of this network. In this study, based on a detailed literature survey, we have identified a list of 12 cytokines that induce signal transduction pathways in RASF. For these cytokines, we have built a signaling network using the protein-protein interaction (PPI) data that was obtained from public repositories such as HPRD, BioGRID, MINT, IntAct and STRING. By combining the network centrality measures with the gene expression data from the RA related microarrays that are available in the open source Gene Expression Omnibus (GEO) database, we have identified 24 key proteins of this signaling network. Two of these 24 are already drug targets for RA, and of the remaining, 12 have direct PPI links to some of the current drug targets of RA. Therefore, these key proteins seem to be crucial in the pathogenesis of RA and hence might be treated as potential drug targets. Public Library of Science 2018-06-21 /pmc/articles/PMC6013252/ /pubmed/29928007 http://dx.doi.org/10.1371/journal.pone.0199530 Text en © 2018 Panga, Raghunathan http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Panga, Venugopal
Raghunathan, Srivatsan
A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title_full A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title_fullStr A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title_full_unstemmed A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title_short A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
title_sort cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013252/
https://www.ncbi.nlm.nih.gov/pubmed/29928007
http://dx.doi.org/10.1371/journal.pone.0199530
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