Ligand and structure-based models for the prediction of ligand-receptor affinities and virtual screenings: development and application to the β2-adrenergic receptor

Journal of Computational Chemistry

Volumn 31, Issue 4, 2010, Pages 707-720

  Vilar, Santiago ^a   Karpiak, Joel ^a   Costanzi, Stefano ^a  

^a NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES   (United States)

Author keywords

2 adrenergic receptor; CoMFA; CoMSIA; Docking; G protein coupled receptors; QSAR; Statistical analysis; Virtual screening

Indexed keywords

ADRENERGIC RECEPTORS; APRIORI; BEST CHOICE; BEST MODEL; BIOACTIVE CONFORMATION; G PROTEIN COUPLED RECEPTORS; INDIVIDUAL COMPONENTS; LIGAND-RECEPTOR; MOLECULAR DOCKING; MULTIPLE MODELS; PARTIAL LEAST SQUARE REGRESSION; PREDICTIVE CAPABILITIES; STATISTICAL ANALYSIS; STRUCTURE-BASED; TRAINING SETS; VIRTUAL SCREENING;

DOCKING; LIGANDS; PROTEINS; STATISTICAL METHODS;

CRYSTAL STRUCTURE;

BETA 2 ADRENERGIC RECEPTOR; LIGAND;

ARTICLE; BINDING SITE; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; DRUG ANTAGONISM; DRUG POTENTIATION; DRUG SCREENING; METABOLISM; MOLECULAR DYNAMICS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; X RAY CRYSTALLOGRAPHY;

BINDING SITES; COMPUTER SIMULATION; CRYSTALLOGRAPHY, X-RAY; DISCRIMINANT ANALYSIS; DRUG EVALUATION, PRECLINICAL; LIGANDS; MODELS, MOLECULAR; MOLECULAR DYNAMICS SIMULATION; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RECEPTORS, ADRENERGIC, BETA-2;

EID: 76249121106     PISSN: 01928651     EISSN: 1096987X     Source Type: Journal    
DOI: 10.1002/jcc.21346     Document Type: Article

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