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A structure-antiarrhythmic activity relationship has been investigated using a chloroform model of arrhythmia in rats. A mathematical model capable of predicting and recognizing antiarrhythmic activity with 84% reliability is formulated. Optimization of the molecular design of lidocaine and procainamide, which have weak antiarrhythmic activity, has resulted in modeling and predicting 51 much more effective antiarrhythmic compounds that can be synthesized for further testing. [ABSTRACT FROM AUTHOR]

A quantitative analysis of the relationship between the structure and inhibitory activity against the herpes simplex virus thymidine kinase (HSV-TK) was performed for the series of 5-ethyluridine, N2-guanine, and 6-oxopurines derivatives with pronounced anti-herpetic activity (IC 50 = 0.09 ÷ 160,000 μmol/L) using the GUSAR 2019 software. On the basis of the MNA and QNA descriptors and whole-molecule descriptors using the self-consistent regression, 12 statistically significant consensus models for predicting numerical pIC 50 values were constructed. These models demonstrated high predictive accuracy for the training and test sets. Molecular fragments of HSV-1 and HSV-2 TK inhibitors that enhance or diminish the anti-herpetic activity are considered. Virtual screening of the ChEMBL database using the developed QSAR models revealed 42 new effective HSV-1 and HSV-2 TK inhibitors. These compounds are promising for further research. The obtained data open up new opportunities for developing novel effective inhibitors of TK.

The present work addresses the quantitative structure−antioxidant activity relationship in a series of 148 sulfur-containing alkylphenols, natural phenols, chromane, betulonic and betulinic acids, and 20-hydroxyecdysone using GUSAR2019 software. Statistically significant valid models were constructed to predict the parameter logk7, where k7 is the rate constant for the oxidation chain termination by the antioxidant molecule. These results can be used to search for new potentially effective antioxidants in virtual libraries and databases and adequately predict logk7 for test samples. A combination of MNA- and QNA-descriptors with three whole molecule descriptors (topological length, topological volume, and lipophilicity) was used to develop six statistically significant valid consensus QSPR models, which have a satisfactory accuracy in predicting logk7 for training and test set structures: R2TR > 0.6; Q2TR > 0.5; R2TS > 0.5. Our theoretical prediction of logk7 for antioxidants AO1 and AO2, based on consensus models agrees well with the experimental value of the measure in this paper. Thus, the descriptor calculation algorithms implemented in the GUSAR2019 software allowed us to model the kinetic parameters of the reactions underlying the liquid-phase oxidation of organic hydrocarbons.

Using the GUSAR 2013 program, the quantitative structure-antioxidant activity relationship has been studied for 74 phenols, aminophenols, aromatic amines and uracils having lgk 7 = 0.01-6.65 (where k 7 is the rate constant for the reaction of antioxidants with peroxyl radicals generated upon oxidation). Based on the atomic descriptors (Quantitative Neighborhood of Atoms (QNA) and Multilevel Neighborhoods of Atoms (MNA)) and molecular (topological length, topological volume and lipophilicity) descriptors, we have developed 9 statistically significant QSAR consensus models that demonstrate high accuracy in predicting the lgk 7 values for the compounds of training sets and appropriately predict lgk 7 for the test samples. Moderate predictive power of these models is demonstrated using metrics of two categories: (1) based on the determination coefficients R 2 (R 2 TSi , R 2 0 , Q 2 ( F1 ), Q 2 ( F2 ), RmTSi2¯) and based on the concordance correlation coefficient (CCC)); or (2) based on the prediction lgk 7 errors (root mean square error (RMSEP), mean absolute error (MAE) and standard deviation (S.D.)) The RBF-SCR method has been used for selecting the descriptors. Our theoretical prognosis of the lgk 7 for 8-PPDA, a known antioxidant, based on the consensus models well agrees with the experimental value measure in the present work. Thus, the algorithms for calculating the descriptors implemented in the GUSAR 2013 program allow simulating kinetic parameters of the reactions underling the liquid-phase oxidation of hydrocarbons.

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.

Structural and electronic factors influencing the inhibition of cyclooxygenase-1 and -2 (COX-1/COX-2) were studied by means of Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking and Density Functional Theory (DFT). A series of structurally diverse compounds containing 209 molecules were classified in accordance with their inhibiting properties, as selectively inhibiting and non-selectively inhibiting COX-2 receptor agents (110 and 99 molecules, correspondingly). The results obtained from the ETM-NN calculations gave us possibility of selecting those pharmacophoric molecular fragments, which allow for the search of new selective inhibitors of COX-2 with high probability of realization. The final selection of pharmacophores and anti-pharmacophores found was taken as a basis for a system designed for the COX-2 inhibitory activity prediction. Analysis of the electron density distribution showed that more effective binding with COX-2 receptor was observed for selective inhibitors. To make an assessment of these interactions, calculations of stabilization energies were carried out for the ligand-receptor complexes. From the results of the docking and from the analysis of electronic structures of active sites of enzymes, some peculiarities of ligand-receptor binding and its influence on the selectivity of the COX-2 relative to COX-1 inhibition were elucidated. 95% of compounds were recognized correctly, as the most active ones, by the system of prediction designed. Thus, the system being the result of the study is capable of predicting the selective inhibitory activity of COX-2 successfully. As a consequence, it can be used both for computer screening and synthesis of potent inhibitors of COX-2 with molecular skeletons that may vary considerably.