Computational biology approaches for drug repurposing.
Bioinformatics
Computational
Disease-target
Drug repositioning
Drug-disease
Machine learning
Molecular dynamics
Network models
Repurposing
Journal
Progress in molecular biology and translational science
ISSN: 1878-0814
Titre abrégé: Prog Mol Biol Transl Sci
Pays: Netherlands
ID NLM: 101498165
Informations de publication
Date de publication:
2024
2024
Historique:
medline:
25
5
2024
pubmed:
25
5
2024
entrez:
24
5
2024
Statut:
ppublish
Résumé
The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.
Identifiants
pubmed: 38789189
pii: S1877-1173(24)00073-5
doi: 10.1016/bs.pmbts.2024.03.018
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
91-109Informations de copyright
Copyright © 2024. Published by Elsevier Inc.