{"title":"有机化合物对四膜虫急性毒性的全球分类模型","authors":"Xinliang Yu , Zekai Zhang , Hanlu Wang","doi":"10.1016/j.psep.2024.10.108","DOIUrl":null,"url":null,"abstract":"<div><div>Predicting the toxic categories for organics towards <em>Tetrahymena pyriformis</em> is a challenging task. A subset of molecular descriptors reflecting structural characteristics such as molecular size, hydrophilicity, polarity, hydrogen bonds, activated multiple halogen substituents and activated carbon–carbon double bonds, were used for developing global quantitative structure–toxicity relationship models for 1792 toxic chemicals (pIGC<sub>50</sub>) in <em>Tetrahymena pyriformis.</em> By utilizing the random forest algorithm, a nine–descriptor classification model was established, which yielded accuracy, sensitivity and specificity higher than 91 % for chemicals with low toxicity classified as Class 0 (pIGC<sub>50</sub> < 3.4) and with high toxicity classified as Class 1 (pIGC<sub>50</sub> ≥ 3.4) in the test set. This classification model based on a larger applicability domain provides a potential tool for predicting the toxic categories for organic compounds towards <em>Tetrahymena pyriformis</em>.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"192 ","pages":"Pages 1221-1227"},"PeriodicalIF":6.9000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global classification model for acute toxicity of organic compounds towards Tetrahymena pyriformis\",\"authors\":\"Xinliang Yu , Zekai Zhang , Hanlu Wang\",\"doi\":\"10.1016/j.psep.2024.10.108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Predicting the toxic categories for organics towards <em>Tetrahymena pyriformis</em> is a challenging task. A subset of molecular descriptors reflecting structural characteristics such as molecular size, hydrophilicity, polarity, hydrogen bonds, activated multiple halogen substituents and activated carbon–carbon double bonds, were used for developing global quantitative structure–toxicity relationship models for 1792 toxic chemicals (pIGC<sub>50</sub>) in <em>Tetrahymena pyriformis.</em> By utilizing the random forest algorithm, a nine–descriptor classification model was established, which yielded accuracy, sensitivity and specificity higher than 91 % for chemicals with low toxicity classified as Class 0 (pIGC<sub>50</sub> < 3.4) and with high toxicity classified as Class 1 (pIGC<sub>50</sub> ≥ 3.4) in the test set. This classification model based on a larger applicability domain provides a potential tool for predicting the toxic categories for organic compounds towards <em>Tetrahymena pyriformis</em>.</div></div>\",\"PeriodicalId\":20743,\"journal\":{\"name\":\"Process Safety and Environmental Protection\",\"volume\":\"192 \",\"pages\":\"Pages 1221-1227\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Process Safety and Environmental Protection\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S095758202401396X\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Process Safety and Environmental Protection","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S095758202401396X","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Global classification model for acute toxicity of organic compounds towards Tetrahymena pyriformis
Predicting the toxic categories for organics towards Tetrahymena pyriformis is a challenging task. A subset of molecular descriptors reflecting structural characteristics such as molecular size, hydrophilicity, polarity, hydrogen bonds, activated multiple halogen substituents and activated carbon–carbon double bonds, were used for developing global quantitative structure–toxicity relationship models for 1792 toxic chemicals (pIGC50) in Tetrahymena pyriformis. By utilizing the random forest algorithm, a nine–descriptor classification model was established, which yielded accuracy, sensitivity and specificity higher than 91 % for chemicals with low toxicity classified as Class 0 (pIGC50 < 3.4) and with high toxicity classified as Class 1 (pIGC50 ≥ 3.4) in the test set. This classification model based on a larger applicability domain provides a potential tool for predicting the toxic categories for organic compounds towards Tetrahymena pyriformis.
期刊介绍:
The Process Safety and Environmental Protection (PSEP) journal is a leading international publication that focuses on the publication of high-quality, original research papers in the field of engineering, specifically those related to the safety of industrial processes and environmental protection. The journal encourages submissions that present new developments in safety and environmental aspects, particularly those that show how research findings can be applied in process engineering design and practice.
PSEP is particularly interested in research that brings fresh perspectives to established engineering principles, identifies unsolved problems, or suggests directions for future research. The journal also values contributions that push the boundaries of traditional engineering and welcomes multidisciplinary papers.
PSEP's articles are abstracted and indexed by a range of databases and services, which helps to ensure that the journal's research is accessible and recognized in the academic and professional communities. These databases include ANTE, Chemical Abstracts, Chemical Hazards in Industry, Current Contents, Elsevier Engineering Information database, Pascal Francis, Web of Science, Scopus, Engineering Information Database EnCompass LIT (Elsevier), and INSPEC. This wide coverage facilitates the dissemination of the journal's content to a global audience interested in process safety and environmental engineering.