Abstract
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Psoriasis is a skin disease which results in scales on the skin caused by flaky patches. Psoriasis is triggered by various conditions such as drug reactions, trauma, and skin infection etc. Globally, there are 125 million people affected by psoriasis and yet there is no effective treatment available, and it emphasizes the need for discovery of efficacious treatments. De-novo drug development takes 10–17 years and $2–$3 billion of investment with <10 % success rate to bring drug from concept to a market ready product. A possible alternative is drug repurposing, which aims at finding other indications of already approved drugs. In this study, a computational drug repurposing framework is developed and applied to differential gene expressions of Psoriasis targets obtained from the publicly available database (GEO). This strategy uses the gene expression signatures of the Psoriasis and compares it with perturbagen available in the CMap. Based on the connected signature drugs are ranked which could possibly reverse the signatures to stop the psoriasis. The drugs with most negative connectivity scores are ranked efficient and vice versa. The top hit drugs are verified using the literature survey of the peer reviewed journal, electronic health records, patents, and hospital database. As a result, 50/150 and 37/150 drugs are confirmed to have anti-psoriasis efficacy in two datasets. Top 10 drugs are suggested as potential repurposable drugs for psoriasis. This study offers, a powerful yet simple approach for rapid identification of potential drug repurposing candidates in Psoriasis and any disease of interest.