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

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成果类型:
期刊论文
作者:
Zhou, Wei;Dai, Zhijun;Chen, Yuan;Yuan, Zheming*
通讯作者:
Yuan, Zheming
作者机构:
[Yuan, Zheming; Zhou, Wei] Hunan Prov Key Lab Crop Germplasm Innovat & Utili, Changsha 410128, Hunan, Peoples R China.
[Yuan, Zheming; Dai, Zhijun; Chen, Yuan; Zhou, Wei] Hunan Agr Univ, Hunan Prov Key Lab Biol & Control Plant Dis & Ins, Coll Biosafety Sci & Technol, Changsha 410128, Hunan, Peoples R China.
通讯机构:
[Yuan, Zheming] H
Hunan Prov Key Lab Crop Germplasm Innovat & Utili, Changsha 410128, Hunan, Peoples R China.
语种:
英文
关键词:
ARC-111 analogues;P388 tumor cells;Quantitative structure–activity relationship (QSAR);Support vector regression (SVR);Descriptor selection
期刊:
Medicinal Chemistry Research
ISSN:
1054-2523
年:
2013
卷:
22
期:
1
页码:
278-286
基金类别:
Science Foundation for Distinguished Young Scholars of Hunan Province, ChinaNational Natural Science Foundation of China (NSFC)National Science Fund for Distinguished Young Scholars [10JJ1005]; Specialized Research Fund for the Doctoral Program of Higher Education of ChinaSpecialized Research Fund for the Doctoral Program of Higher Education (SRFDP) [20114320120005]; Research Foundation of Education Bureau of Hunan Province, China [09C502]; Postgraduate Scientific Research Innovation of Hunan Province, China [CX2011B289]
机构署名:
本校为其他机构
院系归属:
植物保护学院
摘要:
ARC-111 has potent topoisomerase I-targeting activity and pronounced antitumor activity. To design ARC-111 analogues with improved efficiency, we performed analyses on the quantitative structure–activity relationship of 22 ARC-111 analogues assessed in P388 tumor cells. First, the support vector regression (SVR) models were constructed and optimized based on literature descriptors (the low-dimensional descriptor space) and the worst descriptor elimination multi-round (WDEM) method. The optimized SVR model had greater generalization ability tha...

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