3D QSAR CoMFA/CoMSIA and docking studies on azole dione derivatives, as anti-cancer inhibitors.

Q4 Pharmacology, Toxicology and Pharmaceutics International Journal of Computational Biology and Drug Design Pub Date : 2012-01-01 Epub Date: 2012-07-31 DOI:10.1504/IJCBDD.2012.048280
Rohith Kumar Anugolu, Shravan Kumar Gunda, Shaik Mahmood
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引用次数: 2

Abstract

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on a series of 103 azole dione derivatives, as selective anti-cancer inhibitors. The atom and shape based root mean square alignment yielded the best predictive CoMFA model q² = 0.923, r² = 0.980, when compared with the CoMSIA model. Docking studies were employed to position the inhibitors into active site of Crystal Structure of Delta (4)-3-ketosteroid 5-beta-reductase (PDB id: 3BUR). Results that indicate steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor substituents play a significant role in design novel, potent and selective anti-cancer activity of the compounds.

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三维QSAR CoMFA/CoMSIA与唑类二酮衍生物抗癌抑制剂的对接研究。
采用比较分子场分析(CoMFA)和比较分子相似指数分析(CoMSIA)对103个唑二酮类化合物作为选择性抗癌抑制剂进行了分析。与CoMSIA模型相比,基于原子和形状的均方根对齐的CoMFA预测模型q²= 0.923,r²= 0.980。通过对接研究将抑制剂定位到δ(4)-3-酮类固醇5- β还原酶(PDB id: 3BUR)晶体结构的活性位点。结果表明,立体、静电、疏水、氢键给体和受体取代基在设计新颖、有效和选择性抗癌活性的化合物中起着重要作用。
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来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
自引率
0.00%
发文量
8
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