Design and Diversity Analysis of Chemical Libraries in Drug Discovery.
Artificial intelligence
chemical libraries
chemical space
chemoinformatics
compound databases
natural products.
Journal
Combinatorial chemistry & high throughput screening
ISSN: 1875-5402
Titre abrégé: Comb Chem High Throughput Screen
Pays: United Arab Emirates
ID NLM: 9810948
Informations de publication
Date de publication:
05 Jul 2023
05 Jul 2023
Historique:
received:
05
04
2023
accepted:
30
05
2023
medline:
6
7
2023
pubmed:
6
7
2023
entrez:
6
7
2023
Statut:
aheadofprint
Résumé
Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a fundamental role in the development of studies: chemoinformatics, food informatics, in silico pharmacokinetics, computational toxicology, bioinformatics, and molecular modeling to generate computational hits that will continue the optimization process of drug candidates. The prospects for growth in drug discovery and development processes in chemical, biotechnological, and pharmaceutical companies began a few years ago by integrating computational tools with artificial intelligence methodologies. It is anticipated that it will increase the number of drugs approved by regulatory agencies shortly.
Identifiants
pubmed: 37409545
pii: CCHTS-EPUB-132761
doi: 10.2174/1386207326666230705150110
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
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