[show abstract][hide abstract] ABSTRACT: The inclusion complex of sulphathiazole in β-cyclodextrin has been investigated. A 1:2 stoichiometry of the complex was established and formation constants K2 (42.83 ± 3.27 M−1) and K1 (4.98 ± 0.36 M−1) were calculated by using the changes produced on the native fluorescence of the drug, when included on the hydrophobic cyclodextrin cavity. An enhancement in the fluorescence emission of sulphathiazole and protection of the drug against photochemical reactions has been attained upon inclusion. In solutions of β-CD dual emission (458 nm) was noticed in STZ. Formation of the inclusion complex of STZ should result dual emission which is due to a Twisted Intramolecular Charge Transfer band (TICT). A fluorimetric method for the determination of sulphathiazole has been proposed and applied in honey without sample treatment. The optimised fluorimetric method showed detection and quantitation limits of 9.74 ng/g and 32.48 ng/g, respectively. Selectivity is high, showing no cross-reactivity to other chemically related antibiotics. The results obtained for blind honey samples (mean recovery 97%), were in good agreement with those obtained by liquid chromatography separation and mass spectrometry detection (LC–MS) (mean recovery 102%), showing that the proposed method might be used for the determination of sulphathiazole residues without expensive equipment.
[show abstract][hide abstract] ABSTRACT: Genotoxicity is a key toxicity endpoint for current regulatory requirements regarding new and existing chemicals. However, genotoxicity testing is time-consuming and costly, and involves the use of laboratory animals. This has motivated the development of computational approaches, designed to predict genotoxicity without the need to conduct laboratory tests. Currently, many existing computational methods, like quantitative structure-activity relationship (QSAR) models, provide limited information about the possible mechanisms involved in mutagenicity or predictions based on structural alerts (SAs) do not take statistical models into account. This paper describes an attempt to address this problem by using the TOPological Substructural MOlecular Design (TOPS-MODE) approach to develop and validate improved QSAR models for predicting the mutagenicity of a range of halogenated derivatives. Our most predictive model has an accuracy of 94.12%, exhibits excellent cross-validation and external set statistics. A reasonable interpretation of the model in term of SAs was achieved by means of bond contributions to activity. The results obtained led to the following conclusions: primary halogenated derivatives are more mutagenic than secondary ones; and substitution of chlorine by bromine increases mutagenicity while polyhalogenation decreases activity. The paper demonstrates the potential of the TOPS-MODE approach in developing QSAR models for identifying structural alerts for mutagenicity, combining high predictivity with relevant mechanistic interpretation.