{"title":"苯酚毒性的预测QSAR模型","authors":"Auteur Hamada Hakim","doi":"10.52711/0974-4150.2022.00076","DOIUrl":null,"url":null,"abstract":"Toxicity data for the 50% growth inhibitory concentration against Tetrahymena pyriformis pCIC50 = -logCIC50 for 85 phenols substituted were obtained experimentally. Log (CIC50)-1 along with the hydrophobicity, the logarithm of the 1-octanol/water partition coefficient (log Kow), and R2u (GETAWAY descriptors). The entire data set was randomly split into a training set (60chemicals) used to establish the QSAR model, and a test set (25 chemicals) for statistical external validation The descriptors models were selected from an extensive set of several descriptors (topological, geometrical and quantum). Quantitative structure-activity/property (QSAR / The values of the statistical parameters obtained from the multiple linear regression analysis (R²=95.5%, Q²=95.01%, S=0.157, F=604.34, P=0, SDEC=0.153, SDEP=0.161, Q²ext=95.96%, SDEPext=0.153) testify to the good fit of the model.","PeriodicalId":8550,"journal":{"name":"Asian Journal of Research in Chemistry","volume":"113 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive QSAR models for the toxicity of Phenols\",\"authors\":\"Auteur Hamada Hakim\",\"doi\":\"10.52711/0974-4150.2022.00076\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Toxicity data for the 50% growth inhibitory concentration against Tetrahymena pyriformis pCIC50 = -logCIC50 for 85 phenols substituted were obtained experimentally. Log (CIC50)-1 along with the hydrophobicity, the logarithm of the 1-octanol/water partition coefficient (log Kow), and R2u (GETAWAY descriptors). The entire data set was randomly split into a training set (60chemicals) used to establish the QSAR model, and a test set (25 chemicals) for statistical external validation The descriptors models were selected from an extensive set of several descriptors (topological, geometrical and quantum). Quantitative structure-activity/property (QSAR / The values of the statistical parameters obtained from the multiple linear regression analysis (R²=95.5%, Q²=95.01%, S=0.157, F=604.34, P=0, SDEC=0.153, SDEP=0.161, Q²ext=95.96%, SDEPext=0.153) testify to the good fit of the model.\",\"PeriodicalId\":8550,\"journal\":{\"name\":\"Asian Journal of Research in Chemistry\",\"volume\":\"113 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Research in Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52711/0974-4150.2022.00076\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Research in Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52711/0974-4150.2022.00076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive QSAR models for the toxicity of Phenols
Toxicity data for the 50% growth inhibitory concentration against Tetrahymena pyriformis pCIC50 = -logCIC50 for 85 phenols substituted were obtained experimentally. Log (CIC50)-1 along with the hydrophobicity, the logarithm of the 1-octanol/water partition coefficient (log Kow), and R2u (GETAWAY descriptors). The entire data set was randomly split into a training set (60chemicals) used to establish the QSAR model, and a test set (25 chemicals) for statistical external validation The descriptors models were selected from an extensive set of several descriptors (topological, geometrical and quantum). Quantitative structure-activity/property (QSAR / The values of the statistical parameters obtained from the multiple linear regression analysis (R²=95.5%, Q²=95.01%, S=0.157, F=604.34, P=0, SDEC=0.153, SDEP=0.161, Q²ext=95.96%, SDEPext=0.153) testify to the good fit of the model.