Abstract (EN):
Objective. The purpose of this study is to develop a quantitative structure–activity relationship
(QSAR) model that can distinguish mutagenic from non-mutagenic species with
,-unsaturated carbonyl moiety using two endpoints for this activity – Ames test and mammalian
cell genemutation test – and also to gather information about the molecular features
that most contribute to eliminate the mutagenic effects of these chemicals.
Methods. Two data setswere used for modeling the twomutagenicity endpoints: (1) Ames test
and (2) mammalian cellsmutagenesis. The first one comprised 220 molecules, while the second
one 48 substances, ranging from acrylates, methacrylates to ,-unsaturated carbonyl
compounds. The QSAR models were developed by applying linear discriminant analysis
(LDA) along with different sets of descriptors computed using the DRAGON software.
Results. For both endpoints, there was a concordance of 89% in the prediction and 97% confidentiality
by combining the three models for the Ames test mutagenicity. We have also
identified several structural alerts to assist the design of new monomers.
Significance. These individual models and especially their combination are attractive from
the point of view of molecular modeling and could be used for the prediction and design of
new monomers that do not pose a human health risk.
Language:
English
Type (Professor's evaluation):
Scientific
Contact:
Aperez@pdi.ucam.edu (A. Pérez-Garrido)