Computational Drug Discovery in Chemotherapy-induced Alopecia via Text Mining and Biomedical Databases

Purpose: Chemotherapy-induced alopecia (CIA) is a common and often stressful adverse effect associated with chemotherapy. CIA can cause more psychosocial pressure in patients, including effects on sexuality, self-esteem, and social relationships. We analyzed publicly available data to identify drugs formulated for topical use targeting the relevant CIA molecular pathways by using computational tools. Methods: The genes associated with CIA were determined by text mining, and the gene ontology of the gene set was studied using the Functional Enrichment analysis tool. Protein-protein interaction network analysis was performed using the String database. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in CIA. Findings: Our analysis identified 427 genes common to CIA text-mining concepts. Gene enrichment analysis and protein-protein interaction analysis yielded 19 genes potentially targetable by a total of 29 drugs that could possibly be formulated for topical application. (C) 2019 Published by Elsevier Inc.