Oxime derivatives with larvicidal activity against Aedes aegypti L.

Oximes containing secondary metabolites constitute an important group of bioactive compounds and have been described and frequently updated in the literature due to their pharmacological properties. Thus, the aim of this study was to evaluate the larvicidal activity of a series of fourteen structurally related [1,4]-Benzoquinone mono-oximes on third-instar Aedes aegypti larvae and to investigate structure-activity relationships (SAR) of these compounds. Results of larvicidal assay revealed that all oximes were found to have larvicidal activity. Compound 2,6-dimethyl-[1,4]-benzoquinone oxime tosylate (11) was the most bioactive (LC50 = 9.858 ppm), followed by 2-methyl-[1,4]-benzoquinone oxime tosylate (9) (LC50 = 14.450 ppm). [1,4]-benzoquinone oxime (1) exhibited the lowest potency, with an LC50 = 121.181 ppm. The molecular characteristics which may help to understand the assayed compounds larvicidal activity were identified. SAR indicates that the addition of alkyl groups attached to the ring, number, position in the unsaturated cyclic structure, and size of these groups influence the larvicidal activity. Moreover, the lipophilicity seems to play an important role in increasing the larvicidal effect, because, in general, tosyl-containing products were more potent than products containing free OH.

Chemometric studies on potential larvicidal compounds against Aedes aegypti.

The mosquito Aedes aegypti (Diptera, Culicidae) is the vector of yellow and dengue fever. In this study, chemometric tools, such as, Principal Component Analysis (PCA), Consensus PCA (CPCA), and Partial Least Squares Regression (PLS), were applied to a set of fifty five active compounds against Ae. aegypti larvae, which includes terpenes, cyclic alcohols, phenolic compounds, and their synthetic derivatives. The calculations were performed using the VolSurf+ program. CPCA analysis suggests that the higher weight blocks of descriptors were SIZE/SHAPE, DRY, and H2O. The PCA was generated with 48 descriptors selected from the previous blocks. The scores plot showed good separation between more and less potent compounds. The first two PCs accounted for over 60% of the data variance. The best model obtained in PLS, after validation leave-one-out, exhibited q(2) = 0.679 and r(2) = 0.714. External prediction model was R(2) = 0.623. The independent variables having a hydrophobic profile were strongly correlated to the biological data. The interaction maps generated with the GRID force field showed that the most active compounds exhibit more interaction with the DRY probe.