Exploration of Ultralarge Compound Collections for Drug Discovery.

DNA-encoded libraries autonomous laboratory chemical space de novo drug design drug design fragment-based drug design generative models navigating chemical space review structure search ultralarge libraries

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:
09 05 2022
Historique:
pubmed: 15 4 2022
medline: 11 5 2022
entrez: 14 4 2022
Statut: ppublish

Résumé

Designing new medicines more cheaply and quickly is tightly linked to the quest of exploring chemical space more widely and efficiently. Chemical space is monumentally large, but recent advances in computer software and hardware have enabled researchers to navigate virtual chemical spaces containing billions of chemical structures. This review specifically concerns collections of many millions or even billions of enumerated chemical structures as well as even larger chemical spaces that are not fully enumerated. We present examples of chemical libraries and spaces and the means used to construct them, and we discuss new technologies for searching huge libraries and for searching combinatorially in chemical space. We also cover space navigation techniques and consider new approaches to

Identifiants

pubmed: 35421301
doi: 10.1021/acs.jcim.2c00224
doi:

Substances chimiques

Small Molecule Libraries 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

2021-2034

Auteurs

Wendy A Warr (WA)

Wendy Warr & Associates, 6 Berwick Court, Holmes Chapel, Crewe, Cheshire CW4 7HZ, United Kingdom.

Marc C Nicklaus (MC)

NCI, NIH, CADD Group, NCI-Frederick, Frederick, Maryland 21702, United States.

Christos A Nicolaou (CA)

Discovery Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46285, United States.

Matthias Rarey (M)

Universität Hamburg, ZBH Center for Bioinformatics, 20146 Hamburg, Germany.

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Classifications MeSH