Network Pharmacology and Molecular Docking Based Repurposing of ACE Inhibitors as a Potential Candidate for Rheumatoid Arthritis

The anti-arthritic potential of angiotensin converting enzyme inhibitors (ACEIs) was predicted by employing network pharmacology based approach. Information pertinent to the prediction of ACEIs targets and RA-related targets was mined from the BindingDB, Swiss target prediction, and DisGeNET databases. Second, the candidate targets for each component were compiled after the creation of the ACEIs-target gene and ACEIs-RA target gene networks in the Cytoscape program. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to look at the important targets and enriched pathways. Molecular docking with top most target gene was performed for predicting possible binding mode of selected drugs with target gene. A network analysis was performed on 935 probable ACEI targets and 2723 RA-associated targets. The 170 intersection targets revealed the main targets of ACEIs that have potential role in RA. Furthermore, 10 hub genes were screened from protein -protein interaction (PPI) network. GO analysis revealed 380 biological processes, 66 cellular components, and 107 molecular functions. KEGG analysis revealed 148 signaling pathways. The current study investigated the probable target genes and signaling pathways of ACEIs that can alter RA pathophysiology.