Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention.


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:
07 Mar 2024
Historique:
medline: 8 3 2024
pubmed: 8 3 2024
entrez: 7 3 2024
Statut: aheadofprint

Résumé

Identifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery, but it remains a difficult task where most campaigns rely on

Identifiants

pubmed: 38453912
doi: 10.1021/acs.jcim.3c01698
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Commentaires et corrections

Type : UpdateOf

Auteurs

Zachary Smith (Z)

Institute for Physical Science and Technology, University of Maryland, College Park 20742, United States.
Biophysics Program, University of Maryland, College Park 20742, United States.

Michael Strobel (M)

Department of Computer Science, University of Maryland, College Park 20742, United States.

Bodhi P Vani (BP)

Institute for Physical Science and Technology, University of Maryland, College Park 20742, United States.

Pratyush Tiwary (P)

Institute for Physical Science and Technology, University of Maryland, College Park 20742, United States.
Department of Chemistry and Biochemistry, University of Maryland, College Park 20742, United States.

Classifications MeSH