Construction and analysis of protein-protein interaction to identify the molecular mechanism in hypertension

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Abstract

Hypertension is a global health problem with high number of incidence and associated to a high mortality rate. However, the molecular mechanism of hypertension has not been further understood. There have been a series of computational approaches proposed to predict related proteins based on network topologies. This study was aimed to find related proteins and biological regulatory pathways involved in hypertension and further to explore the molecule connectivity between these pathways by topological analysis of the Protein-protein interaction (PPI) network. Protein involved in hypertension were extracted from OMIM, DrugBank, and UniProt database. PPI network was then integrated and visualized using Cytoscape 3.8.2, DAVID database for the gene ontology (GO) functional analysis, KEGG pathway enrichment analysis mechanism and target of hypertension. The giant component of our constructed PPI network consisted of 1033 nodes with 4089 edges, including 35 proteins with large degree (k) betweenness centrality (BC) and is identified as a backbone network. MAPK3 with the largest k and sixth highest BC was suggested to be central to the PPI network associated with hypertension. The result of the GO analysis showed that the most influential biological process was the positive regulation of transcription from RNA polymerase II promoter, the regulation of vascular endothelium, and vascular vasodilation. KEGG result indicated that the MAPK signaling pathways, including TNF signaling pathway, Wnt signaling pathway, ERK5 pathway, JNK and p38 MAP kinase pathway is related molecular mechanism in hypertension.

Original languageEnglish
Title of host publication2nd International Conference on Natural Sciences, Mathematics, Applications, Research, and Technology, ICON-SMART 2021
Subtitle of host publicationMaterials Science and Bioinformatics for Medical, Food, and Marine Industries
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735444614
DOIs
Publication statusPublished - 26 Apr 2023
Event2nd International Conference on Natural Sciences, Mathematics, Applications, Research, and Technology: Materials Science and Bioinformatics for Medical, Food, and Marine Industries, ICON-SMART 2021 - Virtual, Online
Duration: 21 Oct 202122 Oct 2021

Publication series

NameAIP Conference Proceedings
Volume2694
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd International Conference on Natural Sciences, Mathematics, Applications, Research, and Technology: Materials Science and Bioinformatics for Medical, Food, and Marine Industries, ICON-SMART 2021
CityVirtual, Online
Period21/10/2122/10/21

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