组蛋白去乙酰化酶抑制剂的定量构效关系研究。

Aihua Xie, Chenzhong Liao, Zhibin Li, Zhiqiang Ning, Weiming Hu, Xianping Lu, Leming Shi, Jiaju Zhou
{"title":"组蛋白去乙酰化酶抑制剂的定量构效关系研究。","authors":"Aihua Xie,&nbsp;Chenzhong Liao,&nbsp;Zhibin Li,&nbsp;Zhiqiang Ning,&nbsp;Weiming Hu,&nbsp;Xianping Lu,&nbsp;Leming Shi,&nbsp;Jiaju Zhou","doi":"10.2174/1568011043352948","DOIUrl":null,"url":null,"abstract":"<p><p>Histone deacetylases (HDACs) play a critical role in gene transcription and have become a novel target for the discovery of drugs against cancer and other diseases. During the past several years there have been extensive efforts in the identification and optimization of histone deacetylase inhibitors (HDACIs) as novel anticancer drugs. Here we report a comprehensive quantitative structure-activity relationship (QSAR) study of HDACIs in the hope of identifying the structural determinants for anticancer activity. We have identified, collected, and verified the structural and biological activity data for 124 compounds from various literature sources and performed an extensive QSAR study on this comprehensive data set by using various QSAR and classification methods. A highly predictive QSAR model with R(2) of 0.76 and leave-one-out cross-validated R(2) of 0.73 was obtained. The overall rate of cross-validated correct prediction of the classification model is around 92%. The QSAR and classification models provided direct guidance to our internal programs of identifying and optimizing HDAC inhibitors. Limitations of the models were also discussed.</p>","PeriodicalId":10914,"journal":{"name":"Current medicinal chemistry. Anti-cancer agents","volume":"4 3","pages":"273-99"},"PeriodicalIF":0.0000,"publicationDate":"2004-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2174/1568011043352948","citationCount":"43","resultStr":"{\"title\":\"Quantitative structure-activity relationship study of histone deacetylase inhibitors.\",\"authors\":\"Aihua Xie,&nbsp;Chenzhong Liao,&nbsp;Zhibin Li,&nbsp;Zhiqiang Ning,&nbsp;Weiming Hu,&nbsp;Xianping Lu,&nbsp;Leming Shi,&nbsp;Jiaju Zhou\",\"doi\":\"10.2174/1568011043352948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Histone deacetylases (HDACs) play a critical role in gene transcription and have become a novel target for the discovery of drugs against cancer and other diseases. During the past several years there have been extensive efforts in the identification and optimization of histone deacetylase inhibitors (HDACIs) as novel anticancer drugs. Here we report a comprehensive quantitative structure-activity relationship (QSAR) study of HDACIs in the hope of identifying the structural determinants for anticancer activity. We have identified, collected, and verified the structural and biological activity data for 124 compounds from various literature sources and performed an extensive QSAR study on this comprehensive data set by using various QSAR and classification methods. A highly predictive QSAR model with R(2) of 0.76 and leave-one-out cross-validated R(2) of 0.73 was obtained. The overall rate of cross-validated correct prediction of the classification model is around 92%. The QSAR and classification models provided direct guidance to our internal programs of identifying and optimizing HDAC inhibitors. Limitations of the models were also discussed.</p>\",\"PeriodicalId\":10914,\"journal\":{\"name\":\"Current medicinal chemistry. Anti-cancer agents\",\"volume\":\"4 3\",\"pages\":\"273-99\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2174/1568011043352948\",\"citationCount\":\"43\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current medicinal chemistry. Anti-cancer agents\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1568011043352948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current medicinal chemistry. Anti-cancer agents","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1568011043352948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43

摘要

组蛋白去乙酰化酶(hdac)在基因转录中起着至关重要的作用,已成为发现抗癌和其他疾病药物的新靶点。在过去的几年里,人们在鉴定和优化组蛋白去乙酰化酶抑制剂(HDACIs)作为新型抗癌药物方面做了大量的工作。在这里,我们报道了一项全面的定量结构-活性关系(QSAR)研究,希望确定抗肿瘤活性的结构决定因素。我们从各种文献来源中鉴定、收集和验证了124种化合物的结构和生物活性数据,并使用各种QSAR和分类方法对这些综合数据集进行了广泛的QSAR研究。获得了一个高度预测的QSAR模型,R(2)为0.76,留一交叉验证R(2)为0.73。该分类模型的总体交叉验证预测正确率在92%左右。QSAR和分类模型为我们鉴定和优化HDAC抑制剂的内部程序提供了直接指导。讨论了模型的局限性。
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
Quantitative structure-activity relationship study of histone deacetylase inhibitors.

Histone deacetylases (HDACs) play a critical role in gene transcription and have become a novel target for the discovery of drugs against cancer and other diseases. During the past several years there have been extensive efforts in the identification and optimization of histone deacetylase inhibitors (HDACIs) as novel anticancer drugs. Here we report a comprehensive quantitative structure-activity relationship (QSAR) study of HDACIs in the hope of identifying the structural determinants for anticancer activity. We have identified, collected, and verified the structural and biological activity data for 124 compounds from various literature sources and performed an extensive QSAR study on this comprehensive data set by using various QSAR and classification methods. A highly predictive QSAR model with R(2) of 0.76 and leave-one-out cross-validated R(2) of 0.73 was obtained. The overall rate of cross-validated correct prediction of the classification model is around 92%. The QSAR and classification models provided direct guidance to our internal programs of identifying and optimizing HDAC inhibitors. Limitations of the models were also discussed.

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
自引率
0.00%
发文量
0
期刊最新文献
Inhibition of PI3K/Akt signaling: an emerging paradigm for targeted cancer therapy. Lanthanides as anticancer agents. Current drug therapy for prostate cancer: an overview. Sulfo-quinovosyl-acyl-glycerol (SQAG), a eukaryotic DNA polymerase inhibitor and anti-cancer agent. Lycopene: a review of its potential as an anticancer agent.
×
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