{"title":"Classification Model of Pesticide Toxicity in Americamysis bahia Based on Quantum Chemical Descriptors","authors":"Limin Dang","doi":"10.1007/s00244-024-01077-7","DOIUrl":null,"url":null,"abstract":"<div><p>A set of quantum chemical descriptors (molecular polarization, heat capacity, entropy, Mulliken net charge of the most positive hydrogen atom, APT charge of the most negative atom and APT charge of the most positive atom with hydrogen summed into heavy atoms) was successfully used to establish the classification models for the toxicity pLC<sub>50</sub> of pesticides in <i>Americamysis bahia</i>. The optimal random forest model (Class Model A) yielded predictive accuracy of 100% (training set of 217 pesticides), 95.8% (test set of 72 pesticides) and 99.0% (total set of 289 pesticides), which were very satisfactory, compared with previous classification models reported for the toxicity of compounds in aquatic organisms. Therefore, it is reasonable to apply the quantum chemical descriptors associated with molecular structural information on molecular bulk, chemical reactivity and weak interactions, to develop classification models for the toxicity pLC<sub>50</sub> of pesticides in <i>A. bahia</i>.</p></div>","PeriodicalId":8377,"journal":{"name":"Archives of Environmental Contamination and Toxicology","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Environmental Contamination and Toxicology","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s00244-024-01077-7","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
A set of quantum chemical descriptors (molecular polarization, heat capacity, entropy, Mulliken net charge of the most positive hydrogen atom, APT charge of the most negative atom and APT charge of the most positive atom with hydrogen summed into heavy atoms) was successfully used to establish the classification models for the toxicity pLC50 of pesticides in Americamysis bahia. The optimal random forest model (Class Model A) yielded predictive accuracy of 100% (training set of 217 pesticides), 95.8% (test set of 72 pesticides) and 99.0% (total set of 289 pesticides), which were very satisfactory, compared with previous classification models reported for the toxicity of compounds in aquatic organisms. Therefore, it is reasonable to apply the quantum chemical descriptors associated with molecular structural information on molecular bulk, chemical reactivity and weak interactions, to develop classification models for the toxicity pLC50 of pesticides in A. bahia.
期刊介绍：
Archives of Environmental Contamination and Toxicology provides a place for the publication of timely, detailed, and definitive scientific studies pertaining to the source, transport, fate and / or effects of contaminants in the environment. The journal will consider submissions dealing with new analytical and toxicological techniques that advance our understanding of the source, transport, fate and / or effects of contaminants in the environment. AECT will now consider mini-reviews (where length including references is less than 5,000 words), which highlight case studies, a geographic topic of interest, or a timely subject of debate. AECT will also consider Special Issues on subjects of broad interest. The journal strongly encourages authors to ensure that their submission places a strong emphasis on ecosystem processes; submissions limited to technical aspects of such areas as toxicity testing for single chemicals, wastewater effluent characterization, human occupation exposure, or agricultural phytotoxicity are unlikely to be considered.
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