In silicomodelling of hazard endpoints: current problems and perspectives

Abstract

Major scientific hurdles in the acceptance of quantitative structure-activity relationships (QSAR) for regulatory purposes have been identified. First, when quantifying important features of chemical structure complexities of molecular structure have often been ignored. More mechanistic modelling of chemical structure should proceed on two fronts: by developing a more in-depth understanding and representation of the multiple states possible for a single chemical by achieving greater rigor in understanding of conformational flexibility of chemicals; and, by considering families of activated metabolites that are derived in biological systems from an initial chemical substrate. Second, QSAR research is severely limited by the lack of systematic databases for important risk assessment endpoints, and despite many decades of research, the ability to cluster reactive chemicals by common toxicity pathways is in its infancy. Finally, computational tools are lacking for defining where a specific QSAR is applicable within the domain (universe) of chemical structures that are to be regulated. This paper describes some of the approaches being taken to address these needs. Applications of some of these new approaches are demonstrated for the prediction of chemical mutagenicity, where considerations of both molecular flexibility and metabolic activation improved the QSAR predictability and interpretations. Lastly, the applicability domain for a specific QSAR predicting estrogen receptor binding is presented in the context of a mechanistically-defined chemical structure space for large heterogeneous chemical datasets of regulatory concern. A strategic approach is discussed to selecting chemicals for model improvement and validation until regulatory acceptance criteria for risk assessment applications are met.

Toward the Development of “Nano‐QSARs”: Advances and Challenges

“…There are some reviews comprehensively presenting approaches recently used for validating the applicability domains 100–104. However, the Williams graph (Figure 5) seems to be the most commonly applied one.…”

“…There are some reviews comprehensively presenting approaches recently used for validating the applicability domains. [100][101][102][103][104] However, the Williams graph ( Figure 5) seems to be the most commonly applied one. It is a scatter plot presenting the investigated compounds in two dimensions.…”

Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗

“…A full assessment of their possible endocrine-disrupting effects is critical for individual PCBs and their metabolites; unfortunately, traditional toxicological studies are costly and time consuming. To meet the needs of contemporary toxicology, a growing number of in silico tools and quantitative structure-activity relationship (QSAR) models are being developed for surrogate use in evaluation of chemicals for which data are lacking [33][34][35][36][37][38][39][40][41][42]. Through these efforts, meaningful chemical structural features can be identified that will lead to the development of robust predictive models, and specific selection criteria for use of such models [38,39,[41][42][43][44][45][46].…”

“…Recent laws such as European Union's REACH regulation are pushing the acceptance of these methods and their use by the regulatory and public health communities in the mitigation of potential hazardous exposures that could compromise the quality of human and environment health [39,[75][76][77][78][79][80][81][82][83].…”

Metabolism: A Bottleneck in In Vitro Toxicological Test Development

“…Like Meteor, TIMES involves the use of a heuristic algorithm to produce plausible biotransformation pathways from a query molecule, by using rules developed from a comprehensive library of biotransformations (153,157). The generation of metabolites by TIMES can also be limited to the most likely ones or extended to include less likely ones.…”