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A quantitative analysis of the structure-antioxidant activity relationship was performed for 128 derivatives of phenols, amines, uracil, benzopyrane, and benzofuran using the GUSAR 2013 program. Nine statistically signifi cant QSAR consensus models characterized by a high accuracy of prediction of the chain termination rate constant of oxidation on the antioxidant molecules were constructed. The results of the structural analysis performed in the GUSAR 2013 program are in good agreement with the literature data.

The antioxidant properties of humic substances of low-mineralization sulfidic muds (peloids) were investigated using initiated oxidation of 1,4-dioxane as a model reaction. Four groups of substances including humic, himatomelanic, fulvic, and humus acids were studied. Kinetic characteristics of the oxidation of humic substances were determined in terms of effective inhibition rate constants fk In . It is established that himatomelanic acids of peloids exhibit the maximum antioxidant activity among the studied substances.

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Due to the widespread prevalence, deoxyuridine triphosphatase (UTPase) is considered by modern biochemists and physicians as a promising target for the development of drugs with a wide range of activities. The therapeutic effect of these drugs will be due to suppression of DNA biosynthesis in various viruses, bacteria and protozoa. In order to rationalize the search for new dUTPase inhibitors, domestic and foreign researchers are actively using the QSAR methodology at the selection stage of hit compounds. However, the practical application of this methodology is impossible without existence of valid QSAR models. With the use of the GUSAR 2013 program, a quantitative analysis of the relationship between the structure and efficacy of 135 dUTPase inhibitors based on uracil derivatives was performed in the IC50 range of 30¸185000 nmol/L. Six statistically significant valid consensus models, characterized by high descriptive ability and moderate prognostic ability on the structures of training and test samples, are constructed. To build valid QSAR models for dUTPase inhibitors can use QNA or MNA descriptors and their combinations in a consensus approach.

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