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Current Pharmacogenomics and Personalized Medicine


ISSN (Print): 1875-6921
ISSN (Online): 1875-6913

Research Article

Prediction of Potential Targets of an Emerging Zoonotic Paramyxovirus: An Integrated Bioinformatics Analysis

Author(s): Minnikanti Venkata Satya Sai, Viswam Subeesh, Hema Sree GNS, Ganeshan Rajalakshmi Saraswathy and Nair Gouri*

Volume 18, Issue 1, 2021

Published on: 15 March, 2021

Page: [1 - 7] Pages: 7

DOI: 10.2174/1875692118666210315150037

Price: $65


Background: Nipah virus (NiV) is a zoonotic paramyxovirus that can cause severe respiratory illness and encephalitis in humans, with no effective targets and treatment.

Objective: To investigate potential targets involved in the progression of NiV infection by bioinformatics studies.

Methods: To identify the key gene involved in NiV infection, a microarray dataset (GSE32902) was downloaded from the National Centre of Biotechnology Information (NCBI). The differentially expressed genes were unraveled by using Geo2Enrichr, and the functional enrichment analysis was facilitated by using Database for Annotation, Visualization, and Integrated Discovery (DAVID). Search Tool for the Retrieval of Interacting Genes (STRING) was used to construct the Protein-protein interaction (PPI) network and visualized by using Cytoscape.

Results: A total of 500 genes (262 up-regulated and 238 down-regulated) were identified among NiV infected cells. Nineteen upregulated genes were found with a node degree of more than 10, Among which MX1, ISG15, and IFIT1 were found to have the highest node degree (degree=20), followed by RSAD2 and IRF7 with node degree 18 and MX2 and IFIT3 with node degree 17.

Conclusion: The above results explicitly demonstrate that the expressed genes attribute to a defensive response against the virus. Henceforth finding agonists for these genes would help in the effective management of Niv infection.

Keywords: Nipah virus, protein-protein interaction, differentially expressed genes, paramyxovirus, virology, infectious disease.

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