Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report.

Abstract

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 ² _LOO  = 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.