The impact of protein structure and sequence similarity on the accuracy of machine-learning scoring functions for binding affinity prediction

Biomolecules

Volumn 8, Issue 1, 2018, Pages

  Li, Hongjian ^a,b   Peng, Jiangjun ^b,c   Leung, Yee ^b   Leung, Kwong Sak ^b   Wong, Man Hon ^b   Lu, Gang ^b   Ballester, Pedro J ^d,e,f  

^a SDIVF RD Centre   (Hong Kong)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^c XI'AN JIAOTONG UNIVERSITY   (China)

^d AIX MARSEILLE UNIVERSITY   (France)

^e INSTITUT PAOLI CALMETTES   (France)

^f AIX MARSEILLE UNIVERSITY   (France)

Author keywords

Binding affinity prediction; Machine learning; Molecular docking; Scoring function

Indexed keywords

ARTICLE; BINDING AFFINITY; LINEAR REGRESSION ANALYSIS; MACHINE LEARNING; MOLECULAR DOCKING; PREDICTION; PROTEIN STRUCTURE; RANDOM FOREST; PROCEDURES; PROTEIN ANALYSIS; SEQUENCE ANALYSIS; STANDARDS;

MACHINE LEARNING; MOLECULAR DOCKING SIMULATION; PROTEIN INTERACTION MAPPING; SEQUENCE ANALYSIS, PROTEIN;

EID: 85044292801     PISSN: None     EISSN: 2218273X     Source Type: Journal    
DOI: 10.3390/biom8010012     Document Type: Article

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