A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach

Journal of Computer-Aided Molecular Design

Volumn 29, Issue 4, 2015, Pages 349-360

  Wang, Yu ^a   Guo, Yanzhi ^a   Kuang, Qifan ^a   Pu, Xuemei ^a   Ji, Yue ^a   Zhang, Zhihang ^a   Li, Menglong ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

Family specific model; Generic model; Protein ligand binding affinity prediction; Random forest

Indexed keywords

BINDING ENERGY; CARBONIC ANHYDRASE; COMPLEXATION; DECISION TREES; LEARNING SYSTEMS; LIGANDS;

BINDING AFFINITIES; COMPARATIVES STUDIES; FAMILY-SPECIFIC MODEL; GENERIC MODELING; HIV-1 PROTEASE; PROTEIN FAMILY; PROTEIN-LIGAND BINDING AFFINITIES; PROTEIN-LIGAND BINDING AFFINITY PREDICTION; PROTEIN-LIGAND COMPLEXES; RANDOM FORESTS;

FORECASTING;

CARBONATE DEHYDRATASE; HUMAN IMMUNODEFICIENCY VIRUS PROTEINASE; LIGAND; PROTEIN; THROMBIN; TRYPSIN; P16 PROTEASE, HUMAN IMMUNODEFICIENCY VIRUS 1; PROTEIN BINDING;

AMINO ACID SEQUENCE; ARTICLE; BINDING AFFINITY; BINDING SITE; CHEMICAL STRUCTURE; COMPARATIVE STUDY; COMPRESSION; LIGAND BINDING; MOLECULAR INTERACTION; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN FAMILY; PROTEIN PROCESSING; PROTEIN TARGETING; RANDOM FOREST; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; COMPUTER AIDED DESIGN; DRUG DESIGN; HUMAN; METABOLISM; PROTEIN DATABASE;

ARTIFICIAL INTELLIGENCE; CARBONIC ANHYDRASES; COMPUTER-AIDED DESIGN; DATABASES, PROTEIN; DRUG DESIGN; HIV PROTEASE; HUMANS; LIGANDS; MODELS, BIOLOGICAL; PROTEIN BINDING; PROTEINS; TRYPSIN;

EID: 84925496993     PISSN: 0920654X     EISSN: 15734951     Source Type: Journal    
DOI: 10.1007/s10822-014-9827-y     Document Type: Article

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