Predicting ligand binding modes from neural networks trained on protein-ligand interaction fingerprints

Journal of Chemical Information and Modeling

Volumn 53, Issue 4, 2013, Pages 763-772

  Chupakhin, Vladimir ^a   Marcou, Gilles ^a   Baskin, Igor ^a   Varnek, Alexandre ^a   Rognan, Didier ^a  

^a UNIVERSITÉ DE STRASBOURG   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BINDING ENERGY; FORECASTING; NEURAL NETWORKS; PROTEINS; X RAYS;

DOCKING SOLUTIONS; ENCODING PROTEINS; IMPORTANT FEATURES; LIGAND BINDING MODE; PROTEIN LIGANDS; PROTEIN-LIGAND INTERACTIONS; TWO-DIMENSIONAL STRUCTURES; VIRTUAL SCREENING;

LIGANDS;

CDK2 PROTEIN, HUMAN; CYCLIN DEPENDENT KINASE 2; HEAT SHOCK PROTEIN 90; HSP90ALPHA PROTEIN, HUMAN; LIGAND; MITOGEN ACTIVATED PROTEIN KINASE 14;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BINDING SITE; CHEMISTRY; HUMAN; MOLECULAR DOCKING; PEPTIDE MAPPING; PROTEIN BINDING; PROTEIN SECONDARY STRUCTURE; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICS; X RAY CRYSTALLOGRAPHY;

BINDING SITES; CRYSTALLOGRAPHY, X-RAY; CYCLIN-DEPENDENT KINASE 2; HSP90 HEAT-SHOCK PROTEINS; HUMANS; LIGANDS; MITOGEN-ACTIVATED PROTEIN KINASE 14; MOLECULAR DOCKING SIMULATION; NEURAL NETWORKS (COMPUTER); PEPTIDE MAPPING; PROTEIN BINDING; PROTEIN STRUCTURE, SECONDARY; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84876531629     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci300200r     Document Type: Article

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