QSAR and Molecular Docking Studies Of novel thiophene, pyrimidine, coumarin, pyrazole and pyridine derivatives as Potential Anti-Breast Cancer Agent.

Q3 Biochemistry, Genetics and Molecular Biology
İdris Momohjimoh Ovaku, Abechi Stephehe Eyije, Gideon Adamu Shallangwa, Uzairu Adamu
{"title":"QSAR and Molecular Docking Studies Of novel thiophene, pyrimidine, coumarin, pyrazole and pyridine derivatives as Potential Anti-Breast Cancer Agent.","authors":"İdris Momohjimoh Ovaku, Abechi Stephehe Eyije, Gideon Adamu Shallangwa, Uzairu Adamu","doi":"10.33435/tcandtc.614263","DOIUrl":null,"url":null,"abstract":"Abstract : Quantitative Structure Activity Relationship (QSAR) and molecular Docking studies were carried out on some novel compounds to generate a good QSAR models that relate the anti-breast cancer activity values with the molecular structure of the compounds. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors that were used to build the models. The best model built was found to have statistical validation values of squared correlation coefficient ( R 2 ) = 0.999, adjusted squared correlation coefficient (  = 0.998, cross validation coefficient  = 0.998 and an external squared correlation coefficient = 0.879 which was used to confirm the validation of the model. The docking results showed that ligands 6 and 5 with binding energy (-9.2kcalmol -1 and -9.0kcalmol -1 ) respectively have the highest binding affinity when compared to the reference drug doxorubicin with binding energy (-6.8kcalmol -1 ). The stability and robustness of the built model showed that new anti-breast cancer agents can be design from these derivatives.","PeriodicalId":36025,"journal":{"name":"Turkish Computational and Theoretical Chemistry","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Computational and Theoretical Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33435/tcandtc.614263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract : Quantitative Structure Activity Relationship (QSAR) and molecular Docking studies were carried out on some novel compounds to generate a good QSAR models that relate the anti-breast cancer activity values with the molecular structure of the compounds. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors that were used to build the models. The best model built was found to have statistical validation values of squared correlation coefficient ( R 2 ) = 0.999, adjusted squared correlation coefficient (  = 0.998, cross validation coefficient  = 0.998 and an external squared correlation coefficient = 0.879 which was used to confirm the validation of the model. The docking results showed that ligands 6 and 5 with binding energy (-9.2kcalmol -1 and -9.0kcalmol -1 ) respectively have the highest binding affinity when compared to the reference drug doxorubicin with binding energy (-6.8kcalmol -1 ). The stability and robustness of the built model showed that new anti-breast cancer agents can be design from these derivatives.
新型噻吩、嘧啶、香豆素、吡唑和吡啶衍生物潜在抗乳腺癌药物的QSAR和分子对接研究。
摘要:对一些新化合物进行定量构效关系(Quantitative Structure - Activity Relationship, QSAR)和分子对接研究,建立抗乳腺癌活性值与分子结构之间良好的QSAR模型。采用遗传函数算法(GFA)和多元线性回归分析(MLRA)选择描述符构建模型。建立的最佳模型的统计验证值为平方相关系数(r2) = 0.999,校正后的平方相关系数(0.998),交叉验证系数= 0.998,外部平方相关系数= 0.879,验证模型的有效性。对接结果表明,与参比药物阿霉素的结合能(-6.8kcalmol -1)相比,结合能为-9.2kcalmol -1和-9.0kcalmol -1的配体6和5具有最高的结合亲和力。所建模型的稳定性和鲁棒性表明,可以从这些衍生物中设计出新的抗乳腺癌药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Turkish Computational and Theoretical Chemistry
Turkish Computational and Theoretical Chemistry Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
CiteScore
2.40
自引率
0.00%
发文量
4
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信