Repurposing FDA approved drugs for psoriasis indications through integrated molecular docking, one-SVM algorithm, and molecular dynamics simulation approaches.

The exact cause of psoriasis is still unclear and there is no treatment available for its permanent reemission. The available biologics for disease treatment, are stated to be associated with a high cost of treatment, a significantly increased risk of serious infections, and have also been reported to show major contradictions in patients with tuberculosis and cardiovascular disorders. Therefore, drug repurposing could be an appealing strategy to find novel treatments for psoriasis, saving time, cost and with viable chance of success. The goal of the present study was to identify the FDA approved drugs which can be proposed as potential anti-psoriasis drugs. The known drug target interactions of 19 autoimmune diseases, 4 cardiovascular risk factors, and each of infectious, lung, and mood disorders were retrieved using various public databases, i.e., DrugBank, PharmGKB, clinicaltrial.gov database, TTD, CTD, and the Unified Medical Language System NDF-RT. The drug target interaction of prioritised drugs, obtained using molecular function GO mappings from the QuickGO database through NBI score was analysed using a molecular docking approach. Further, one-SVM algorithm prediction was done to validate the docking outcome and molecular dynamics simulation of top drug-target molecule was performed to propose potential anti-psoriasis drugs. The study identified Pioglitazone, Trimipramine and Dimetindene as top three contender amongst many other drugs as a new indication against psoriasis.