Using physical potentials and learned models to distinguish native binding interfaces from de novo designed interfaces that do not bind

Proteins: Structure, Function and Bioinformatics

Volumn 81, Issue 11, 2013, Pages 1919-1930

  Demerdash, Omar N A ^a   Mitchell, Julie C ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Machine learning; Protein binding; Protein complex; Protein design; Stacking interactions

Indexed keywords

ACCURACY; ARTICLE; BIOLOGICAL MODEL; ELECTRIC POTENTIAL; ENERGY TRANSFER; HYDROGEN BOND; KERNEL METHOD; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN PROTEIN INTERACTION; STATIC ELECTRICITY; SUPPORT VECTOR MACHINE;

MACHINE LEARNING; PROTEIN BINDING; PROTEIN COMPLEX; PROTEIN DESIGN; STACKING INTERACTIONS;

ALGORITHMS; MODELS, THEORETICAL; PROTEIN BINDING; PROTEINS; SOFTWARE;

EID: 84885809230     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.24337     Document Type: Article

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