TOPKAT^Ⓡ, Derek^Ⓡ, OECD toolbox를 활용한 화학물질 독성 예측 연구

Toxicity Prediction using Three Quantitative Structure-activity Relationship (QSAR) Programs (OPKAT^Ⓡ, Derek^Ⓡ, OECD toolbox)

Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using TOPKAT^Ⓡ, OECD toolbox, and Derek^Ⓡ, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.