Do Similar Structures Have Similar No Observed Adverse Effect Level (NOAEL) Values? Exploring Chemoinformatics Approaches for Estimating NOAEL Bounds and Uncertainties

Determination of the no observed
adverse effect level (NOAEL) of
a substance is an important step in safety and regulatory assessments.
Application of conventional in silico strategies,
for example, quantitative structure–activity relationship (QSAR)
models, to predict NOAEL values is inherently problematic. Whereas
QSAR models for well-defined toxicity endpoints such as Ames mutagenicity
or skin sensitization can be developed from mechanistic knowledge
of molecular initiating events and adverse outcome pathways, QSAR
is not appropriate for predicting a NOAEL value, a concentration at
which “no effect” is observed. This paper presents a
chemoinformatics approach and explores how it can be further refined
through the incorporation of toxicity endpoint-specific information
to estimate confidence bounds for the NOAEL of a target substance,
given experimentally determined NOAEL values for one or more suitable
analogues. With a sufficiently large NOAEL database, we analyze how
a difference in NOAEL values for pairs of structures depends on their
pairwise similarity, where similarity takes both structural features
and physicochemical properties into account. The width of the estimate
NOAEL confidence interval is proportional to the uncertainty. Using
the new threshold of toxicological concern (TTC) database enriched
with antimicrobials, examples are presented to illustrate how uncertainty
decreases with increasing analogue quality and also how NOAEL bounds
estimation can be significantly improved by filtering the full database
to include only substances that are in structure categories relevant
to the target and analogue.