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
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

1074-1080

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Matthew Segall (M)

Optibrium Limited, F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK. Electronic address: matt.segall@optibrium.com.

Tamsin Mansley (T)

Optibrium Limited, F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK.

Peter Hunt (P)

Optibrium Limited, F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK.

Edmund Champness (E)

Optibrium Limited, F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK.

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Classifications MeSH