Capturing and applying knowledge to guide compound optimisation.
Journal
Drug discovery today
ISSN: 1878-5832
Titre abrégé: Drug Discov Today
Pays: England
ID NLM: 9604391
Informations de publication
Date de publication:
05 2019
05 2019
Historique:
received:
09
11
2018
revised:
28
01
2019
accepted:
14
02
2019
pubmed:
23
2
2019
medline:
18
1
2020
entrez:
23
2
2019
Statut:
ppublish
Résumé
Successful drug discovery requires knowledge and experience across many disciplines, and no current 'artificial intelligence' (AI) method can replace expert scientists. However, computers can recall more information than any individual or team and facilitate the transfer of knowledge across disciplines. Here, we discuss how knowledge relating to chemistry and the biological and physicochemical properties required for a successful compound can be captured. Furthermore, we illustrate how, by combining and applying this knowledge computationally, a broader range of optimisation strategies can be rigorously explored, and the results presented in an intuitive way for consideration by the experts.
Identifiants
pubmed: 30794861
pii: S1359-6446(18)30377-5
doi: 10.1016/j.drudis.2019.02.004
pii:
doi:
Substances chimiques
Dipeptidyl-Peptidase IV Inhibitors
0
Pyrimidines
0
anagliptin
K726J96838
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1074-1080Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.