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

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 9, Issue 5, 2012, Pages 1301-1313

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

^a Michigan State University   (United States)

Author keywords

Drug discovery; machine learning; protein ligand binding affinity; ranking power; scoring function; virtual screening

Indexed keywords

BINDING AFFINITIES; DRUG DISCOVERY; RANKING POWER; SCORING FUNCTIONS; VIRTUAL SCREENING;

BINDING ENERGY; BINDING SITES; COMPLEXATION; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; PROTEINS;

LIGANDS;

LIGAND; PROTEIN;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BINDING SITE; CHEMISTRY; COMPARATIVE STUDY; METABOLISM; PROTEIN CONFORMATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BINDING SITES; LIGANDS; PROTEIN CONFORMATION; PROTEINS;

EID: 84864950736     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2012.36     Document Type: Article

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