Current In Silico Drug Repurposing Strategies

Abstract

Over the years, drug discovery and development process has been transformed from "one drug, one target, one disease" to "one drug, multiple targets, multiple diseases." In this respect, a better understanding of the polypharmacological profiles of drugs has gained much attention. Deciphering the network-based pharmacology of drugs not only holds the promise of predicting efficacy and adverse effects prior to clinical studies but it also reveals the unknown off targets for existing drugs. Finding novel uses for already approved drugs coined as drug repurposing is an emerging field in drug discovery, because this new approach circumvents failures in optimization stages in drug development and preclinical trials and decrease the attrition rates in late clinical phases, hence reducing timeline, labor and resources spent before a molecule enters the open market. Drug repurposing benefits greatly from the rapid developments in bioinformatics and cheminformatics tools and omics technologies to integrate, analyze and interpret the ever-increasing information in biomedical field. In the present work we review most commonly used data ware systems for drug repurposing that host vast amount of chemical, biological and clinical information and mining tools. Moreover, an overview on computational drug repurposing methods and approaches based on similarity measures are briefly discussed and case studies are presented.