Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study.
Journal
Journal of chemical information and modeling
ISSN: 1549-960X
Titre abrégé: J Chem Inf Model
Pays: United States
ID NLM: 101230060
Informations de publication
Date de publication:
28 08 2023
28 08 2023
Historique:
medline:
29
8
2023
pubmed:
7
8
2023
entrez:
7
8
2023
Statut:
ppublish
Résumé
Computer-aided drug design (CADD), especially artificial intelligence-driven drug design (AIDD), is increasingly used in drug discovery. In this paper, a novel and efficient workflow for hit identification was developed within the
Identifiants
pubmed: 37549337
doi: 10.1021/acs.jcim.3c00543
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM