Work

Network pharmacological approach to predict the herbal drug targets in Measles Virus infection

Year: 2025

Type: article

Abstract: The measles virus, which is spread by aerosols, kills a significant number of individuals and infects many children each year. It was previously believed to replicate in the respiratory epithelium before spreading, but it has now been shown to employ signaling lymphocytic activation molecule family member 1 as a receptor to initially infect airway dendritic cells and macrophages. The measles virus replicates quickly in lymphatic organs once these cells carry the infection there after navigating the respiratory epithelium. Here, we mainly aimed to the selected dataset which is publicly available and is related to measles infection where we had seven different types of cell lines and performed in-silico analysis of the gene expression patterns and the altered signaling pathways and finally, compared them between the cell lines. In this case, we selected a set of differentially expressed genes (DEGs) and prepared the protein-protein interaction and the inferred pathways network. In the DEGs and pathways network, we analyzed those proteins which are highly connected in terms of proteins and the biological functions. After predicting the set of proteins, we performed docking profiling of herbal drugs Curcumin, Resveratrol, Myricetin, and Diosmin with the predicted leading proteins. We conclude that Diosmin as the potential putative drugs against ITGA2, VAV3, and CCND2.

Source: Global Journal of Basic Science

DOI: 10.63454/jbs200014sa

Authors: Shiful Islam, Rifaquat Ahmed

Institution: Norwegian University of Science and Technology

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: Norges Teknisk-Naturvitenskapelige Universitet, Faculty of Medicine and Health, University of Sydney