{"title":"Discriminating Toxicant Classes by Mode of Action: 2. Physico‐Chemical Descriptors","authors":"M. Nendza, Martin Müller","doi":"10.1002/1521-3838(200012)19:6<581::AID-QSAR581>3.0.CO;2-A","DOIUrl":null,"url":null,"abstract":"Environmental contaminants with common mode of toxic action (MOA) are generally expected to have similar structures and/or physico-chemical properties. Calculated descriptors of lipophilic, electronic and steric properties were used to cluster 115 test chemicals by MOA into nine different toxicant classes (non-polar non-specific toxicants, polar non-specific toxicants, uncouplers of oxidative phosphorylation, inhibitors of photosynthesis, inhibitors of acetylcholinesterase, inhibitors of respiration, thiol-alkylating agents, reactives (irritants), estrogenic compounds). Stepwise discriminant analysis of the test chemicals resulted in 89.6% correct classifications into the MOA classes. The final model uses 10 significant variables (log KOW, eHOMO, V+, QAV, HMAX+, MR, MW, DEFF, SASA, SAVOL). PLS discriminant analysis of the same data set resulted in a three-component model with r=0.89; the variables with the highest discriminatory power are log KOW, HMAX+, DEFF and QAV. Each MOA class reveals a characteristic profile in physico-chemical properties. Deviations relative to non-specific baseline toxicants are specific for each MOA class and reflect the structural dependences of the rate-limiting interactions that are causing the respective toxicities (functional similarity). By combining physiological and chemical knowledge about underlying processes, it is possible to indicate descriptor-based discrimination criteria by MOA as an essential prerequisite for rational selection and application of process-related QSARS for predictive purposes.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":"33 1","pages":"581-598"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Structure-activity Relationships","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/1521-3838(200012)19:6<581::AID-QSAR581>3.0.CO;2-A","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
Abstract
Environmental contaminants with common mode of toxic action (MOA) are generally expected to have similar structures and/or physico-chemical properties. Calculated descriptors of lipophilic, electronic and steric properties were used to cluster 115 test chemicals by MOA into nine different toxicant classes (non-polar non-specific toxicants, polar non-specific toxicants, uncouplers of oxidative phosphorylation, inhibitors of photosynthesis, inhibitors of acetylcholinesterase, inhibitors of respiration, thiol-alkylating agents, reactives (irritants), estrogenic compounds). Stepwise discriminant analysis of the test chemicals resulted in 89.6% correct classifications into the MOA classes. The final model uses 10 significant variables (log KOW, eHOMO, V+, QAV, HMAX+, MR, MW, DEFF, SASA, SAVOL). PLS discriminant analysis of the same data set resulted in a three-component model with r=0.89; the variables with the highest discriminatory power are log KOW, HMAX+, DEFF and QAV. Each MOA class reveals a characteristic profile in physico-chemical properties. Deviations relative to non-specific baseline toxicants are specific for each MOA class and reflect the structural dependences of the rate-limiting interactions that are causing the respective toxicities (functional similarity). By combining physiological and chemical knowledge about underlying processes, it is possible to indicate descriptor-based discrimination criteria by MOA as an essential prerequisite for rational selection and application of process-related QSARS for predictive purposes.