{"title":"QSAR Studies of amino-pyrimidine derivatives as Mycobacterium tuberculosis Protein Kinase B inhibitors","authors":"S. Khamouli, S. Belaidi, H. Belaidi, L. Belkhiri","doi":"10.33435/TCANDTC.397449","DOIUrl":null,"url":null,"abstract":"Quantitative structure activity relationship (QSAR) analysis was applied to a series of amino-pyrimidine derivatives as PknB inhibitors using a combination of various physicochemical and quantum descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the chemotherapeutic activity of the amino-pyrimidine derivatives. Good agreement between experimental and predicted activity values, obtained in the validation procedure, indicated the good quality of the derived QSAR model. The statistically significant best QSAR model has a cross validated correlation coefficient R 2 CV = 0.973 and external predictive ability of prediction R 2 = 0.778 was developed by MLR. The proposed model has good robustness and predictability when verified by internal and external validation.","PeriodicalId":36025,"journal":{"name":"Turkish Computational and Theoretical Chemistry","volume":"88 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Computational and Theoretical Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33435/TCANDTC.397449","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: 2
Abstract
Quantitative structure activity relationship (QSAR) analysis was applied to a series of amino-pyrimidine derivatives as PknB inhibitors using a combination of various physicochemical and quantum descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the chemotherapeutic activity of the amino-pyrimidine derivatives. Good agreement between experimental and predicted activity values, obtained in the validation procedure, indicated the good quality of the derived QSAR model. The statistically significant best QSAR model has a cross validated correlation coefficient R 2 CV = 0.973 and external predictive ability of prediction R 2 = 0.778 was developed by MLR. The proposed model has good robustness and predictability when verified by internal and external validation.