三维QSAR CoMFA/CoMSIA与唑类二酮衍生物抗癌抑制剂的对接研究。

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
{"title":"三维QSAR CoMFA/CoMSIA与唑类二酮衍生物抗癌抑制剂的对接研究。","authors":"Rohith Kumar Anugolu,&nbsp;Shravan Kumar Gunda,&nbsp;Shaik Mahmood","doi":"10.1504/IJCBDD.2012.048280","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":39227,"journal":{"name":"International Journal of Computational Biology and Drug Design","volume":"5 2","pages":"111-36"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJCBDD.2012.048280","citationCount":"2","resultStr":"{\"title\":\"3D QSAR CoMFA/CoMSIA and docking studies on azole dione derivatives, as anti-cancer inhibitors.\",\"authors\":\"Rohith Kumar Anugolu,&nbsp;Shravan Kumar Gunda,&nbsp;Shaik Mahmood\",\"doi\":\"10.1504/IJCBDD.2012.048280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":39227,\"journal\":{\"name\":\"International Journal of Computational Biology and Drug Design\",\"volume\":\"5 2\",\"pages\":\"111-36\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJCBDD.2012.048280\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computational Biology and Drug Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJCBDD.2012.048280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2012/7/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"Pharmacology, Toxicology and Pharmaceutics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Biology and Drug Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCBDD.2012.048280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2012/7/31 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 2

摘要

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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
3D QSAR CoMFA/CoMSIA and docking studies on azole dione derivatives, as anti-cancer inhibitors.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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
期刊最新文献
Assessment and Validation of Emulgel Based Salicylic acid Formulation Development to Drug release and Optimization by Statistical Design EyeRIS: Image-Based Identification of Goats using Iris Advanced DEEPCNN Breast Cancer Mammogram Image Detection and Classification with Butterfly Optimization Algorithm A Unique Noise Detector Developed for the Filtering of X-Ray Images of Bone Fractures Residue Interaction Network analysis and Molecular dynamics simulation of 6K Viroporin: Chikungunya Virus Channel Proteins
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1