Computational drug repurposing: approaches, evaluation of in silico resources and case studies

Abstract

Repurposing of existing drugs for new indications has attracted substantial attention owing to its potential to accelerate drug development and reduce costs. Hundreds of computational resources such as databases and predictive platforms have been developed that can be applied for drug repurposing, making it challenging to select the right resource for a specific drug repurposing project. With the aim of helping to address this challenge, here we overview computational approaches to drug repurposing based on a comprehensive survey of available in silico resources using a purpose-built drug repurposing ontology that classifies the resources into hierarchical categories and provides application-specific information. We also present an expert evaluation of selected resources and three drug repurposing case studies implemented within the Horizon Europe REMEDi4ALL project to demonstrate the practical use of the resources. This comprehensive Review with expert evaluations and case studies provides guidelines and recommendations on the best use of various in silico resources for drug repurposing and establishes a basis for a sustainable and extendable drug repurposing web catalogue. Hundreds of computational resources have been developed that can be applied to repurposing existing drugs for new indications, making it challenging to select the right resource for a specific project. To help address this challenge, this article provides an overview of computational approaches to drug repurposing based on a comprehensive survey of available resources classified into hierarchical categories for a web catalogue, and presents an expert evaluation of selected resources, as well as case studies to illustrate their application.