{"title":"Predicting acute toxicity of pesticides towards <i>Daphnia magna</i> with random forest algorithm.","authors":"S Xu","doi":"10.1080/1062936X.2025.2478510","DOIUrl":null,"url":null,"abstract":"<p><p>A large number of pesticides are released into the environment, resulting in serious threat for aquatic organisms. In this work, 15 quantum chemical descriptors were used to develop a quantitative structure-activity/toxicity relationship (QSAR/QSTR) model for toxicity pEC<sub>50</sub> of 745 pesticides towards <i>Daphnia magna</i>, by using random forest algorithm. The optimal QSTR model in this paper yielded a coefficient of determination of 0.828, root-mean-square error of 0.798, and mean absolute error of 0.628 for the test set of 149 pesticides, which are accurate values compared with those of QSTR models published recently. Research has revealed that increasing molecular size (or molar volume), the most positive atomic Mulliken (or APT) charge with hydrogens summed into heavy, and the highest occupied molecular orbital (HOMO) energy, can result in higher toxicity pEC<sub>50</sub>. Increasing the lowest unoccupied molecular orbital (LUMO) energy and the HOMO and LUMO energy gap can lead to lower toxicity pEC<sub>50</sub>.</p>","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"36 3","pages":"189-203"},"PeriodicalIF":2.3000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAR and QSAR in Environmental Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/1062936X.2025.2478510","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/14 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
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Abstract
A large number of pesticides are released into the environment, resulting in serious threat for aquatic organisms. In this work, 15 quantum chemical descriptors were used to develop a quantitative structure-activity/toxicity relationship (QSAR/QSTR) model for toxicity pEC50 of 745 pesticides towards Daphnia magna, by using random forest algorithm. The optimal QSTR model in this paper yielded a coefficient of determination of 0.828, root-mean-square error of 0.798, and mean absolute error of 0.628 for the test set of 149 pesticides, which are accurate values compared with those of QSTR models published recently. Research has revealed that increasing molecular size (or molar volume), the most positive atomic Mulliken (or APT) charge with hydrogens summed into heavy, and the highest occupied molecular orbital (HOMO) energy, can result in higher toxicity pEC50. Increasing the lowest unoccupied molecular orbital (LUMO) energy and the HOMO and LUMO energy gap can lead to lower toxicity pEC50.
期刊介绍：
SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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