Predicting PBT and CMR properties of substances of very high concern (SVHCs) using QSAR models, and application for K-REACH

Joonsik Moon; Byongcheun Lee; Jin-Sung Ra; Ki-Tae Kim

doi:10.1016/j.toxrep.2020.08.014

Predicting PBT and CMR properties of substances of very high concern (SVHCs) using QSAR models, and application for K-REACH

Toxicol Rep. 2020 Aug 15:7:995-1000. doi: 10.1016/j.toxrep.2020.08.014. eCollection 2020.

Authors

Joonsik Moon¹, Byongcheun Lee², Jin-Sung Ra³, Ki-Tae Kim¹

Affiliations

¹ Department of Environmental Energy Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea.
² Risk Assessment Division, National Institute of Environmental Research, Incheon, 22689, Republic of Korea.
³ Eco-testing and Risk Assessment Center, Korea Institute of Industrial Technology (KITECH), Ansan, 15588, Republic of Korea.

Abstract

Quantitative structure-activity relationship (QSAR) models have been applied to predict a variety of toxicity endpoints. Their performance needs to be validated, in a variety of cases, to increase their applicability to chemical regulation. Using the data set of substances of very high concern (SVHCs), the performance of QSAR models were evaluated to predict the persistence and bioaccumulation of PBT, and the carcinogenicity and mutagenicity of CMR. BIOWIN and Toxtree showed higher sensitivity than other QSAR models - the former for persistence and bioaccumulation, the latter for carcinogenicity. In terms of mutagenicity, the sensitivities of QSAR models were underestimated, Toxtree was more accurate and specific than lazy structure-activity relationships (LAZARs) and Computer Assisted Evaluation of industrial chemical Substances According to Regulations (CAESAR). Using the weight of evidence (WoE) approach, which integrates results of individual QSAR models, enhanced the sensitivity of each toxicity endpoint. On the basis of obtained results, in particular the prediction of persistence and bioaccumulation by KOWWIN, a conservative criterion is recommended of log Kow greater than 4.5 in K-REACH, without an upper limit. This study suggests that reliable production of toxicity data by QSAR models is facilitated by a better understanding of the performance of these models.

Keywords: AD, applicability domain; AFC, atom/fragment contribution; BCF, bioconcentration factor; CAESAR, Computer Assisted Evaluation of industrial chemical Substances According to Regulations; CAS, chemicals abstracts service; CMR; CMR, carcinogenic, mutagenic or toxic for reproduction; DSSTox, distributed structure-searchable toxicity; ECHA, European Chemical Agency; EDC, endocrine disrupting chemicals; EPI, estimation programs interface; FN, false negative; FP, false positive; GHS, globally harmonized system of classification and labelling of chemicals; K-REACH; Kow, octanol-water coefficient; LAZAR, lazy structure–activity relationships; PBT; PBT, persistent, bioaccumulative and toxic; PFCAs, perfluorinated carboxylic acids; PFDA, nonadecafluorodecanoic acid; QMRF, QSAR model reporting format; QPRF, QSAR prediction reporting format; QSAR; QSAR, quantitative structure-activity relationship; REACH, registration, evaluation, authorization and restriction of chemicals; SA, structure alters; SMILES, simplified molecular-input line-entry system; SVHCs; SVHCs, substances of very high concern; TN, ture negative; TP, ture positive; US EPA, United States Environmental Protection Agency; UVCBs, complex reaction products or biological materials; WoE, weight of evidence.