Antitumor agents 252. Application of validated QSAR models to database mining: Discovery of novel tylophorine derivatives as potential anticancer agents

Journal of Computer-Aided Molecular Design

Volumn 21, Issue 1-3, 2007, Pages 97-112

  Zhang, Shuxing ^a   Wei, Linyi ^a   Bastow, Ken ^a   Zheng, Weifan ^a   Brossi, Arnold ^a   Lee, Kuo Hsiung ^a   Tropsha, Alexander ^a  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

Author keywords

Anti cancer agents; Phenanthrine based tylophrine derivatives (PBTs); QSAR modeling; Virtual screening

Indexed keywords

COMPUTATIONAL CHEMISTRY; MOLECULAR GRAPHICS; NEAREST NEIGHBOR SEARCH; STATISTICAL TESTS;

ANTI-CANCER AGENTS; ANTITUMOUR AGENTS; CORRELATION COEFFICIENT; MODEL SCREENING; PHENANTHRINE-BASED TYLOPHRINE DERIVATIVE; POTENTIAL ANTICANCER AGENTS; QSAR MODEL; QSAR MODELING; TEST SETS; VIRTUAL SCREENING;

BIOACTIVITY;

ANTINEOPLASTIC AGENT; ANTINEOPLASTIC ALKALOID; PHENANTHRENE DERIVATIVE; TYLOCREBRINE; TYLOPHORINE; UNCLASSIFIED DRUG;

ARTICLE; COMPUTER AIDED DESIGN; COMPUTER PROGRAM; CORRELATION COEFFICIENT; CYTOTOXICITY; DATA BASE; DATA MINING; DRUG DESIGN; DRUG SCREENING; DRUG STRUCTURE; HUMAN; HUMAN CELL; K NEAREST NEIGHBOR; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICAL SIGNIFICANCE; STRUCTURAL BIOINFORMATICS; VALIDATION PROCESS;

EID: 33947228423     PISSN: 0920654X     EISSN: 15734951     Source Type: Journal    
DOI: 10.1007/s10822-007-9102-6     Document Type: Article

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