Computational Drug Discovery in Chemotherapy-Induced Alopecia via Text Mining and Biomedical Databases
April 2019
in “
Clinical Therapeutics
”
TLDR Computational tools identified 29 drugs that could potentially target 19 genes involved in chemotherapy-induced hair loss, which could lead to more effective treatments.
The study "Computational Drug Discovery in Chemotherapy-induced Alopecia via Text Mining and Biomedical Databases" conducted in 2019 used computational tools to analyze publicly available data and identify drugs for topical use that target the molecular pathways involved in chemotherapy-induced alopecia (CIA). The researchers determined the genes associated with CIA through text mining and studied the gene ontology using the Functional Enrichment analysis tool. They also performed protein-protein interaction network analysis using the String database. The 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. These findings could help discover more effective agents and facilitate drug repositioning efforts in the pharmaceutical industry.
