Computational QSAR models with high-dimensional descriptor selection improve antitumor activity design of ARC-111 analogues

Medicinal Chemistry Research

Volumn 22, Issue 1, 2013, Pages 278-286

  Zhou, Wei ^a,b   Dai, Zhijun ^b   Chen, Yuan ^b   Yuan, Zheming ^a,b  

^a Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization   (China)

^b HUNAN AGRICULTURAL UNIVERSITY   (China)

Author keywords

ARC 111 analogues; Descriptor selection; P388 tumor cells; Quantitative structure activity relationship (QSAR); Support vector regression (SVR)

Indexed keywords

8,9 DIMETHOXY 5 (2 N, N DIMETHYLAMINOETHYL) 2,3 METHYLENEDIOXY 5H DIBENZO[C,H][1,6] NAPHTHYRIDIN 6 ONE; ANTINEOPLASTIC AGENT; DNA TOPOISOMERASE; UNCLASSIFIED DRUG;

ANTINEOPLASTIC ACTIVITY; ARTICLE; CANCER CELL CULTURE; CYTOTOXICITY; DRUG STRUCTURE; MULTIPLE LINEAR REGRESSION ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SUPPORT VECTOR MACHINE;

EID: 84872042752     PISSN: 10542523     EISSN: 15548120     Source Type: Journal    
DOI: 10.1007/s00044-012-0034-x     Document Type: Article

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