The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials.
Antimicrobial resistance (AMR)
Computer-aided drug discovery (CADD)
Ligand-based virtual screening (LBVS)
Machine learning
Molecular docking and scoring
Pharmacophore
Quantitative structure-activity relationships (QSAR)
Structure-based virtual screening (SBVS)
Virtual screening
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
06
09
2023
revised:
25
12
2023
accepted:
01
01
2024
medline:
8
1
2024
pubmed:
8
1
2024
entrez:
7
1
2024
Statut:
aheadofprint
Résumé
Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.
Identifiants
pubmed: 38184864
pii: S0010-4825(24)00011-8
doi: 10.1016/j.compbiomed.2024.107927
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
107927Informations de copyright
Copyright © 2024. Published by Elsevier Ltd.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.