{"title":"揭示大鼠和小鼠急性口服抗菌剂毒性的种间相关性和敏感性因子分析:首份 QSTR 和 QTTR 模型报告。","authors":"Purusottam Banjare, Anjali Murmu, Balaji Wamanrao Matore, Jagadish Singh, Ester Papa, Partha Pratim Roy","doi":"10.1093/toxres/tfae191","DOIUrl":null,"url":null,"abstract":"<p><p>This study aims to identify toxic potential and environmental hazardousness of antimicrobials. In this regard, the available experimental toxicity data with rat and mouse acute oral toxicity have been gathered from ChemID Plus database (<i>n</i> = 202) and subjected to data curation. Upon the data curation 51 and 68 compounds were left for the rat and mouse respectively for the modeling. The quantitative structure toxicity relationship (QSTR) and interspecies correlation analysis by quantitative toxicity-toxicity relationship (QTTR) modeling was approached in this study. The models were developed from 2D descriptors under OECD guidelines by using multiple linear regressions (MLR) with genetic algorithm (GA) for feature selection as a chemometric tool. The developed models were robust (Q <sup><b>2</b></sup> <sub><b>LOO</b></sub> = 0.600-0.679) and predictive enough (Q <sup><b>2</b></sup> F <sub><b>n</b></sub> = 0.626-0.958, CCC <sub><b>Ext</b></sub> = 0.840-0.893). The leverage approach of applicability domain (ad) analysis assures the model's reliability. The antimicrobials without experimental toxicity values were classified as high, moderate and low toxic based on prediction and ad. The occurrence of the same classification from QSTR and QTTR models revealed the reliability of QTTR models.Finally, the applied <i>\"sensitivity factor analysis\"</i> typifies the sensitivity of chemicals toward each species. Overall, the first report will be helpful in the toxicity assessment of upcoming antimicrobials in rodents.</p>","PeriodicalId":105,"journal":{"name":"Toxicology Research","volume":"13 6","pages":"tfae191"},"PeriodicalIF":2.2000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11569388/pdf/","citationCount":"0","resultStr":"{\"title\":\"Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report.\",\"authors\":\"Purusottam Banjare, Anjali Murmu, Balaji Wamanrao Matore, Jagadish Singh, Ester Papa, Partha Pratim Roy\",\"doi\":\"10.1093/toxres/tfae191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study aims to identify toxic potential and environmental hazardousness of antimicrobials. In this regard, the available experimental toxicity data with rat and mouse acute oral toxicity have been gathered from ChemID Plus database (<i>n</i> = 202) and subjected to data curation. Upon the data curation 51 and 68 compounds were left for the rat and mouse respectively for the modeling. The quantitative structure toxicity relationship (QSTR) and interspecies correlation analysis by quantitative toxicity-toxicity relationship (QTTR) modeling was approached in this study. The models were developed from 2D descriptors under OECD guidelines by using multiple linear regressions (MLR) with genetic algorithm (GA) for feature selection as a chemometric tool. The developed models were robust (Q <sup><b>2</b></sup> <sub><b>LOO</b></sub> = 0.600-0.679) and predictive enough (Q <sup><b>2</b></sup> F <sub><b>n</b></sub> = 0.626-0.958, CCC <sub><b>Ext</b></sub> = 0.840-0.893). The leverage approach of applicability domain (ad) analysis assures the model's reliability. The antimicrobials without experimental toxicity values were classified as high, moderate and low toxic based on prediction and ad. The occurrence of the same classification from QSTR and QTTR models revealed the reliability of QTTR models.Finally, the applied <i>\\\"sensitivity factor analysis\\\"</i> typifies the sensitivity of chemicals toward each species. Overall, the first report will be helpful in the toxicity assessment of upcoming antimicrobials in rodents.</p>\",\"PeriodicalId\":105,\"journal\":{\"name\":\"Toxicology Research\",\"volume\":\"13 6\",\"pages\":\"tfae191\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11569388/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Toxicology Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/toxres/tfae191\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicology Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/toxres/tfae191","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
本研究旨在确定抗菌素的毒性潜力和环境危害。为此,我们从 ChemID Plus 数据库(n = 202)中收集了现有的大鼠和小鼠急性口服毒性实验数据,并进行了数据整理。经数据整理后,大鼠和小鼠分别留下了 51 和 68 个化合物用于建模。本研究采用定量毒性-毒性关系(QTTR)模型进行定量结构毒性关系(QSTR)和种间相关性分析。模型是根据 OECD 准则,利用多重线性回归(MLR)和遗传算法(GA)作为化学计量学工具进行特征选择,从二维描述符中建立的。所开发的模型具有很强的鲁棒性(Q 2 LOO = 0.600-0.679)和足够的预测性(Q 2 F n = 0.626-0.958,CCC Ext = 0.840-0.893)。适用域(ad)分析的杠杆方法确保了模型的可靠性。根据预测值和 ad 值,将没有实验毒性值的抗菌素分为高毒、中毒和低毒。最后,应用 "敏感性因子分析 "对化学品对每个物种的敏感性进行了典型分析。总之,第一份报告将有助于对即将上市的抗菌药物进行啮齿动物毒性评估。
Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report.
This study aims to identify toxic potential and environmental hazardousness of antimicrobials. In this regard, the available experimental toxicity data with rat and mouse acute oral toxicity have been gathered from ChemID Plus database (n = 202) and subjected to data curation. Upon the data curation 51 and 68 compounds were left for the rat and mouse respectively for the modeling. The quantitative structure toxicity relationship (QSTR) and interspecies correlation analysis by quantitative toxicity-toxicity relationship (QTTR) modeling was approached in this study. The models were developed from 2D descriptors under OECD guidelines by using multiple linear regressions (MLR) with genetic algorithm (GA) for feature selection as a chemometric tool. The developed models were robust (Q 2LOO = 0.600-0.679) and predictive enough (Q 2 F n = 0.626-0.958, CCC Ext = 0.840-0.893). The leverage approach of applicability domain (ad) analysis assures the model's reliability. The antimicrobials without experimental toxicity values were classified as high, moderate and low toxic based on prediction and ad. The occurrence of the same classification from QSTR and QTTR models revealed the reliability of QTTR models.Finally, the applied "sensitivity factor analysis" typifies the sensitivity of chemicals toward each species. Overall, the first report will be helpful in the toxicity assessment of upcoming antimicrobials in rodents.