QSAR method for prediction of protein-peptide binding affinity: Application to MHC class I molecule HLA-A*0201

Journal of Molecular Graphics and Modelling

Volumn 26, Issue 1, 2007, Pages 246-254

  Zhao, Chunyan ^a   Zhang, Haixia ^a   Luan, Feng ^a   Zhang, Ruisheng ^a   Liu, Mancang ^a   Hu, Zhide ^a   Fan, Botao ^b  

^a LANZHOU UNIVERSITY   (China)

^b UNIVERSITÉ PARIS DESCARTES   (France)

Author keywords

Amino acids property; Binding affinity; Heuristic method (HM); HLA A*0201; QSAR; Support vector machine (SVM)

Indexed keywords

BINDING ENERGY; CHEMICAL ANALYSIS; HEURISTIC METHODS; LEARNING SYSTEMS; LIGANDS; SUPPORT VECTOR MACHINES; SYNTHESIS (CHEMICAL);

BINDING AFFINITY; PEPTIDIC LIGANDS; QSAR METHOD; TOPOLOGICAL DESCRIPTORS;

MOLECULAR DYNAMICS;

HLA A ANTIGEN; MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 1;

ARTICLE; BINDING AFFINITY; PEPTIDE SYNTHESIS; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; PROTEIN BINDING; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SUPPORT VECTOR MACHINE;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; DATABASES, PROTEIN; HLA-A ANTIGENS; HUMANS; LINEAR MODELS; MODELS, MOLECULAR; NONLINEAR DYNAMICS; OLIGOPEPTIDES; PROTEIN BINDING; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 34250845896     PISSN: 10933263     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmgm.2006.12.002     Document Type: Article

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