Exploring the conformational diversity of proteins.
G-protein coupled receptors
artificial intelligence
conformational dynamics
machine learning
molecular biophysics
none
protein structure prediction
structural biology
transmembrane protein
transporters
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
21 04 2022
21 04 2022
Historique:
entrez:
21
4
2022
pubmed:
22
4
2022
medline:
23
4
2022
Statut:
epublish
Résumé
An artificial intelligence-based method can predict distinct conformational states of membrane transporters and receptors.
Identifiants
pubmed: 35443909
doi: 10.7554/eLife.78549
pii: 78549
pmc: PMC9023052
doi:
pii:
Substances chimiques
Membrane Transport Proteins
0
Types de publication
Editorial
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2022, Schlessinger and Bonomi.
Déclaration de conflit d'intérêts
AS, MB No competing interests declared
Références
Nature. 2021 Aug;596(7873):590-596
pubmed: 34293799
Proc Natl Acad Sci U S A. 2021 Sep 14;118(37):
pubmed: 34507995
Nature. 2021 Aug;596(7873):583-589
pubmed: 34265844
Acta Crystallogr D Struct Biol. 2022 Jan 1;78(Pt 1):1-13
pubmed: 34981757
Nat Commun. 2019 Jul 31;10(1):3427
pubmed: 31366933
Elife. 2022 Mar 03;11:
pubmed: 35238773
Science. 2001 Oct 5;294(5540):93-6
pubmed: 11588250