Computational Drug Repurposing for Neurodegenerative Diseases

Abstract Currently, most of the neurodegenerative diseases lack effective therapeutic drugs. The present burden of these diseases on society highlights the need to develop novel approaches for their treatment. The detection of novel indications for existing drugs, known as drug repurposing, is a promising alternative approach to the traditional drug-discovery process that can be used to identify therapeutic compounds. This chapter provides a comprehensive review of the various drug-repurposing methods focusing on the computational approach. The available computational methods, namely structure-based virtual screening, ligand-based, transcriptomics-based, GWAS-based, network-based, integration-based, machine learning-based, and literature-based methods, are discussed along with their advantages and disadvantages. In addition, case studies utilizing existing and available tools are presented. Finally, the challenges of drug repurposing are discussed including the validation methods and the investigation of drug combinations.