A comparative assessment of predictive accuracies of conventional and machine learning scoring functions for protein-ligand binding affinity prediction

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 12, Issue 2, 2015, Pages 335-347

  Ashtawy, Hossam M ^a   Mahapatra, Nihar R ^a  

^a Michigan State University   (United States)

Author keywords

Drug discovery; Machine learning; Protein ligand binding affinity; Scoring function; Scoring power; Virtual screening

Indexed keywords

ARTIFICIAL INTELLIGENCE; BINDING ENERGY; BINDING SITES; COMPLEXATION; CORRELATION METHODS; COST EFFECTIVENESS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; LIGANDS;

DRUG DISCOVERY; PROTEIN-LIGAND BINDING AFFINITIES; SCORING FUNCTIONS; SCORING POWER; VIRTUAL SCREENING;

PROTEINS;

LIGAND; PROTEIN; PROTEIN BINDING;

BIOLOGY; CHEMISTRY; DRUG DEVELOPMENT; MACHINE LEARNING; METABOLISM; PROCEDURES; PROTEIN DATABASE;

COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; DRUG DISCOVERY; LIGANDS; MACHINE LEARNING; PROTEIN BINDING; PROTEINS;

EID: 84927634713     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2014.2351824     Document Type: Article

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