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ZZS similarity tool: The online tool for similarity screening to identify chemicals of potential concern
Author(s) -
Wassenaar Pim N. H.,
Rorije Emiel,
Vijver Martina G.,
Peijnenburg Willie J. G. M.
Publication year - 2022
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26859
Subject(s) - interpretability , similarity (geometry) , prioritization , identification (biology) , computer science , structural similarity , chemical similarity , quantitative structure–activity relationship , data mining , machine learning , artificial intelligence , management science , engineering , biology , botany , image (mathematics)
Screening and prioritization of chemicals is essential to ensure that available evaluation capacity is invested in those substances that are of highest concern. We, therefore, recently developed structural similarity models that evaluate the structural similarity of substances with unknown properties to known Substances of Very High Concern (SVHC), which could be an indication of comparable effects. In the current study the performance of these models is improved by (1) separating known SVHCs in more specific subgroups, (2) (re-)optimizing similarity models for the various SVHC-subgroups, and (3) improving interpretability of the predicted outcomes by providing a confidence score. The improvements are directly incorporated in a freely accessible web-based tool, named the ZZS similarity tool: https://rvszoeksysteem.rivm.nl/ZzsSimilarityTool. Accordingly, this tool can be used by risk assessors, academia and industrial partners to screen and prioritize chemicals for further action and evaluation within varying frameworks, and could support the identification of tomorrow's substances of concern.