Topical application of BRAF inhibitors has been shown to accelerate wound healing in murine models, which can be extrapolated into clinical applications. The aim of the study was to identify suitable pharmacological targets of BRAF inhibitors and elucidate their mechanisms of action for therapeutic applicability in wound healing, by employing bioinformatics tools including network pharmacology and molecular docking. The potential targets for BRAF inhibitors were obtained from SwissTargetPrediction, DrugBank, CTD, Therapeutic Target Database, and Binding Database. Targets of wound healing were obtained using online databases DisGeNET and OMIM (Online Mendelian Inheritance in Man). Common targets were found by using the online GeneVenn tool. Common targets were then imported to STRING to construct interaction networks. Topological parameters were assessed using Cytoscape and core targets were identified. FunRich was employed to uncover the signaling pathways, cellular components, molecular functions, and biological processes in which the core targets participate. Finally, molecular docking was performed using MOE software. Key targets for the therapeutic application of BRAF inhibitors for wound healing are peroxisome proliferator‐activated receptor γ, matrix metalloproteinase 9, AKT serine/threonine kinase 1, mammalian target of rapamycin, and Ki‐ras2 Kirsten rat sarcoma viral oncogene homolog. The most potent BRAF inhibitors that can be exploited for their paradoxical activity for wound healing applications are Encorafenib and Dabrafenib. By using network pharmacology and molecular docking, it can be predicted that the paradoxical activity of BRAF inhibitors can be used for their potential application in wound healing.

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.

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