Machine learning in computational docking

Artificial Intelligence in Medicine

Volumn 63, Issue 3, 2015, Pages 135-152

  Khamis, Mohamed A ^a   Gomaa, Walid ^a,b   Ahmed, Walaa F ^a  

^a EGYPT JAPAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Egypt)

^b Alexandria University The Faculty Of Engineering   (Egypt)

Author keywords

Complex binding affinity; Computational docking; Drug discovery; Force field interaction; Ligands ranking accuracy; Machine learning; Pharmacophore fingerprint; Random forest; Scoring function; Support vector machine; Virtual screening

Indexed keywords

ARTIFICIAL INTELLIGENCE; CORRELATION METHODS; DECISION TREES; DESIGN; DRUG DELIVERY; DRUG PRODUCTS; DRUG THERAPY; FREE ENERGY; FUNCTIONS; LEARNING SYSTEMS; LIFE CYCLE; LIGANDS; MOLECULES; PHARMACODYNAMICS; PROTEINS; SUPPORT VECTOR MACHINES;

COMPLEX BINDING; COMPUTATIONAL DOCKINGS; DRUG DISCOVERY; FORCE FIELDS; PHARMACOPHORES; RANDOM FORESTS; SCORING FUNCTIONS; VIRTUAL SCREENING;

BINDING ENERGY;

BINDING AFFINITY; COMPUTER AIDED DESIGN; DATA BASE; DRUG DESIGN; HIGH THROUGHPUT SCREENING; LIFE CYCLE; MACHINE LEARNING; MATHEMATICAL MODEL; MOLECULAR BIOLOGY; MOLECULAR DOCKING; MOLECULAR MECHANICS; PRIORITY JOURNAL; QUANTUM CHEMISTRY; SHORT SURVEY; BIOLOGY; CHEMISTRY; HUMAN; PROCEDURES; PROTEIN CONFORMATION; PROTEIN DATABASE; QUANTUM THEORY; STATISTICAL ANALYSIS;

LIGAND; PROTEIN; PROTEIN BINDING;

COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; DATABASES, PROTEIN; HUMANS; LIGANDS; MACHINE LEARNING; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; QUANTUM THEORY;

EID: 84928585769     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2015.02.002     Document Type: Short Survey

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