2 research outputs found
Refine and Strengthen SAR-Based Read-Across by Considering Bioactivation and Modes of Action
Structure–activity relationship (SAR)-based read-across
is an important and effective method to establish the safety of a
data-poor target chemical (structure of interest (SOI)) using hazard
data from structurally similar source chemicals (analogues). Many
methods use quantitative similarity scores to evaluate the structural
similarity for searching and selecting analogues as well as for evaluating
analogue suitability. However, studies suggest that read-across based
purely on structural similarity cannot accurately predict the toxicity
of an SOI. As mechanistic data become available, we gain a greater
understanding of the mode of action (MOA), the relationship between
structures and metabolism/bioactivation pathways, and the existence
of “activity cliffs” in chemical chain length, which
can improve the analogue rating process. For this purpose, the current
work identifies a series of classes of chemicals where a small change
at a key position can result in a significant change in metabolism
and bioactivation pathways and may eventually result in significant
changes in chemical toxicity that have a big impact on the suitability
of analogues for read-across. Additionally, a series of SAR-based
read-across case studies are presented, which cover a variety of chemical
classes that commonly link to different toxic endpoints. The case
study results indicate that SAR-based read-across can be refined and
strengthened by considering MOAs or proposed reactive metabolite formation
pathways, which can improve the overall accuracy, consistency, transparency,
and confidence in evaluating analogue suitability
Refine and Strengthen SAR-Based Read-Across by Considering Bioactivation and Modes of Action
Structure–activity relationship (SAR)-based read-across
is an important and effective method to establish the safety of a
data-poor target chemical (structure of interest (SOI)) using hazard
data from structurally similar source chemicals (analogues). Many
methods use quantitative similarity scores to evaluate the structural
similarity for searching and selecting analogues as well as for evaluating
analogue suitability. However, studies suggest that read-across based
purely on structural similarity cannot accurately predict the toxicity
of an SOI. As mechanistic data become available, we gain a greater
understanding of the mode of action (MOA), the relationship between
structures and metabolism/bioactivation pathways, and the existence
of “activity cliffs” in chemical chain length, which
can improve the analogue rating process. For this purpose, the current
work identifies a series of classes of chemicals where a small change
at a key position can result in a significant change in metabolism
and bioactivation pathways and may eventually result in significant
changes in chemical toxicity that have a big impact on the suitability
of analogues for read-across. Additionally, a series of SAR-based
read-across case studies are presented, which cover a variety of chemical
classes that commonly link to different toxic endpoints. The case
study results indicate that SAR-based read-across can be refined and
strengthened by considering MOAs or proposed reactive metabolite formation
pathways, which can improve the overall accuracy, consistency, transparency,
and confidence in evaluating analogue suitability