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Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates

Viral hemorrhagic septicemia virus (VHSV) is a rhabdovirus reported to cause economic loss in fish farms. Because of the lack of adequate preventative treatments, the identification of multipath genes involved in VHS infection might be an alternative to explore the possibility of using drugs for the...

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Autores principales: Ebrahimpour Gorji, Abdolvahab, Roudbari, Zahra, Ebrahimpour Gorji, Fatemeh, Sadeghi, Balal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Urmia University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8094140/
https://www.ncbi.nlm.nih.gov/pubmed/33953878
http://dx.doi.org/10.30466/vrf.2019.94179.2270
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author Ebrahimpour Gorji, Abdolvahab
Roudbari, Zahra
Ebrahimpour Gorji, Fatemeh
Sadeghi, Balal
author_facet Ebrahimpour Gorji, Abdolvahab
Roudbari, Zahra
Ebrahimpour Gorji, Fatemeh
Sadeghi, Balal
author_sort Ebrahimpour Gorji, Abdolvahab
collection PubMed
description Viral hemorrhagic septicemia virus (VHSV) is a rhabdovirus reported to cause economic loss in fish farms. Because of the lack of adequate preventative treatments, the identification of multipath genes involved in VHS infection might be an alternative to explore the possibility of using drugs for the seasonal prevention of this fish disease. We propose labeling a category of drug molecules by further classification and interpretation of the Drug Gene Interaction Database using gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment scores. The study investigated disease networks of up-and down-regulated genes to find those with high interaction as substantial genes in pathways among the different disease networks. We prioritized these genes based on their relationship to those associated with VHS infection in the context of human protein-protein interaction networks and disease pathways. Among the 29 genes as potential drug targets, nine were selected as promising druggable genes (ERBB2, FGFR3, ITGA2B, MAP2K1, NGF, NTRK1, PDGFRA, SCN2B, and SERPINC1). PDGFRA is the most important druggable up-and down-regulated gene and is considered an important gene in the IMATINIB pathway. This study findings indicate a promising approach for drug target prediction for VHS treatment, which might be useful for disease therapeutics.
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spelling pubmed-80941402021-05-04 Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates Ebrahimpour Gorji, Abdolvahab Roudbari, Zahra Ebrahimpour Gorji, Fatemeh Sadeghi, Balal Vet Res Forum Original Article Viral hemorrhagic septicemia virus (VHSV) is a rhabdovirus reported to cause economic loss in fish farms. Because of the lack of adequate preventative treatments, the identification of multipath genes involved in VHS infection might be an alternative to explore the possibility of using drugs for the seasonal prevention of this fish disease. We propose labeling a category of drug molecules by further classification and interpretation of the Drug Gene Interaction Database using gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment scores. The study investigated disease networks of up-and down-regulated genes to find those with high interaction as substantial genes in pathways among the different disease networks. We prioritized these genes based on their relationship to those associated with VHS infection in the context of human protein-protein interaction networks and disease pathways. Among the 29 genes as potential drug targets, nine were selected as promising druggable genes (ERBB2, FGFR3, ITGA2B, MAP2K1, NGF, NTRK1, PDGFRA, SCN2B, and SERPINC1). PDGFRA is the most important druggable up-and down-regulated gene and is considered an important gene in the IMATINIB pathway. This study findings indicate a promising approach for drug target prediction for VHS treatment, which might be useful for disease therapeutics. Urmia University Press 2021 2021-03-15 /pmc/articles/PMC8094140/ /pubmed/33953878 http://dx.doi.org/10.30466/vrf.2019.94179.2270 Text en © 2021 Urmia University. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-noncommercial 4.0 International License, (https://creativecommons.org/licenses/by-nc/4.0/) which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.
spellingShingle Original Article
Ebrahimpour Gorji, Abdolvahab
Roudbari, Zahra
Ebrahimpour Gorji, Fatemeh
Sadeghi, Balal
Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title_full Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title_fullStr Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title_full_unstemmed Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title_short Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
title_sort computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8094140/
https://www.ncbi.nlm.nih.gov/pubmed/33953878
http://dx.doi.org/10.30466/vrf.2019.94179.2270
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