4.0 Conclusions
In this paper we have reported the use of a quantum chemical-based
approach to assess the skin sensitization potential of chemicals from
the Schiff base domain. We have evaluated the mechanistic profile
associated with 22 SB substrates using a model consisting of two
methylamine and two water molecules. We find that calculating the full
reaction profile for the chemicals is important as the substrates can
often react in more than one position, while also allowing for
mechanistic exceptions to be uncovered. We find that the use of a single
computed descriptor, namely the rate determining barrier to formation of
the SB product can help us to separate sensitizer and non-sensitizer. A
RDS barrier of ~28 kcal/mol indicate that a molecule is
unlikely to act as a sensitizer. We also observed that compounds with
low barriers, but higher logP values show reduced sensitization
prompting us to generate a 2 parameter QMM.
A QMM equation established suggests that SB of lower logP have a greater
propensity to react resulting in r2 of 0.50-0.60. The
predicted RDS and logP establish SAR guidelines to rationalize the skin
sensitization potential. The RDS barriers for aldehydes, ketone, 1,2 and
1,3 diones broadly decrease in that order, in line with their increasing
experimental sensitivity. These findings agree with experimental based
observations in the literature and point to the value computational
methods can play in skin sensitization predictions. We find that the
rate determining barrier and the computed lipophilicity can be used to
estimate the skin-sensitization of unknown compounds. This orthogonal
source of information could prove useful in consensus based predictions
of likely sensitization potential.[21,
26]
The results presented here show that 3D quantum chemical simulation of
SB chemicals, while useful, will lead to the mischaracterization of some
compounds. This is not so different to the variation observed between
the different types of in vivo , in vitro and in
silico methods reported to date which show predictions accuracies of no
more than 70-80%. This is simply a reflection of the complex event
being simulated, a multitude of potential protein targets, and the fact
that the molecules may function in the form of a metabolite rather than
the dosed substrate. The utility of such simulations is that physical
insight and understanding can be garnered which could prove useful,
especially when combined in the so–called weight of evidence approach
with other methods.