Deciphering the Precise Target for Saroglitazar Associated Antiangiogenic Effect: A Computational Synergistic Approach.

Abstract

Antidiabetic drugs that have a secondary pharmacological effect on angiogenesis inhibition may help diabetic patients delay or avoid comorbidities caused by angiogenesis including malignancies. In recent studies, saroglitazar has exhibited antiangiogenic effects in diabetic retinopathy. The current study investigates the antiangiogenic effects of saroglitazar utilizing the chicken chorioallantoic membrane (CAM) assay and then identifies its precise mode of action on system-level protein networks. To determine the regulatory effect of saroglitazar on the protein-protein interaction network (PIN), 104 target genes were retrieved and tested using an acid server and Swiss target prediction tools. A string-based interactome was created and analyzed using Cytoscape. It was determined that the constructed network was scale-free, making it biologically relevant. Upon topological analysis of the network, 37 targets were screened on the basis of centrality values. Submodularization of the interactome resulted in the formation of four clusters. A total of 20 common targets identified in topological analysis and modular analysis were filtered. A total of 20 targets were compiled and were integrated into the pathway enrichment analysis using ShinyGO. The majority of hub genes were associated with cancer and PI3-AKT signaling pathways. Molecular docking was utilized to reveal the most potent target, which was validated by using molecular dynamic simulations and immunohistochemical staining on the chicken CAM. The comprehensive study offers an alternate research paradigm for the investigation of antiangiogenic effects using CAM assays. This was followed by the identification of the precise off-target use of saroglitazar using system biology and network pharmacology to inhibit angiogenesis.