Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors

Journal of Computer-Aided Molecular Design

Volumn 27, Issue 12, 2013, Pages 1067-1073

  Tan, Wen ^a,b   Mei, Hu ^a,b   Chao, Li ^c   Liu, Tengfei ^c   Pan, Xianchao ^b   Shu, Mao ^c   Yang, Li ^a,b  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b CHONGQING UNIVERSITY   (China)

^c CHONGQING UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Inhibitor; P glycoprotein; Prediction; Support vector machine; Surflex dock

Indexed keywords

BINDING ENERGY; COMPUTATIONAL CHEMISTRY; DOCKS; FREE ENERGY; GLYCOPROTEINS; HYDRAULIC STRUCTURES; MOLECULAR MODELING; SUPPORT VECTOR MACHINES;

DOCKING STUDIES; INHIBITOR; MOLECULAR DOCKING; MULTIDRUG RESISTANCE; OVERALL ACCURACIES; P-GLYCOPROTEIN; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; SUPPORT VECTORS MACHINE; SURFLEX-DOCK; SVM MODEL;

FORECASTING;

GLYCOPROTEIN P INHIBITOR; LIGAND; MULTIDRUG RESISTANCE PROTEIN;

ALGORITHM; AROMATICITY; ARTICLE; BINDING AFFINITY; CHEMICAL PHENOMENA; COMPETITIVE INHIBITION; CONSENSUS DEVELOPMENT; CONTROLLED STUDY; CRYSTAL STRUCTURE; DRUG BINDING SITE; HUMAN; HYDROPHOBICITY; LIGAND BINDING; MEASUREMENT ACCURACY; MOLECULAR DOCKING; MOLECULAR VOLUME; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SEQUENCE HOMOLOGY; SUPPORT VECTOR MACHINE; SURFLEX DOCK;

DRUG RESISTANCE, MULTIPLE; HUMANS; MODELS, MOLECULAR; MOLECULAR DOCKING SIMULATION; P-GLYCOPROTEINS; PHARMACEUTICAL PREPARATIONS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SUPPORT VECTOR MACHINES;

EID: 84891844437     PISSN: 0920654X     EISSN: 15734951     Source Type: Journal    
DOI: 10.1007/s10822-013-9697-8     Document Type: Article

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