The freely accessible web resource PASS Online is presented. This resource is designed for the prediction of the biological activity spectra of organic compounds based on their structural formulas for more than 4000 types of biological activity with average accuracy above 95% (http://www.way2drug.com/passonline). The prediction is based on an analysis of the structure-activity relationships in the training set containing information on the structure and biological activity of more than 300000 organic compounds. The possibilities and limitations of this approach are described. Recommendations are given for interpreting the prediction results. Examples are given for the practical use of the PASS Online web resource in order to establish priorities for chemical synthesis and biological testing of substances on the basis of prediction results. The further trends are considered for the using PASS Online as an Internet platform for joint projects of academic researchers for the search and development of new pharmaceutical agents.
Chemistry of Heterocyclic Compounds, 2014, 50 (3), 444-457.

The objective of the present work was to synthesize and estimate mechanism of action, pharmacological activity and toxic or side effects of some 1,3,5-trisubstituted-2-pyrazoline derivatives. Substituted chalcones were used as starting material. Chalcones comprising aryl moiety have been prepared by Claisen-Schmidt condensation of aromatic aldehydes with 4-Hydroxy acetophenone. All these pyrazoline derivativatives are characterised by IR, 1H-NMR and MS analysis. Prediction of Activity Spectra for Substances(PASS) is the computer program used in this work.Antifungal and antibacterial activities predicted by PASS was confirmed by experimental evaluation.
Journal of Pharmacy Research, 2011, 4 (2), 558-560.

In the existing QSAR methods any molecule is represented as a single point in many-dimensional space of molecular descriptors. We proposed a new QSAR approach based on Quantitative Neighbourhoods of Atoms (QNA) descriptors, which characterize each atom of a molecule and depend on the whole molecule structure. In “Star Track” methodology any molecule is represented as a set of points in two-dimensional space of QNA descriptors. By our new method the estimate of target property of chemical compound is calculated as the average value of the function of QNA descriptors in the points of the atoms of a molecule in QNA descriptors’ space. Substantially, we have proposed to use only two instead of more than three thousand molecular descriptors applying in QSAR. On the basis of this approach we have developed computer program GUSAR and compared it with the several widely used QSAR methods including CoMFA, CoMSIA, Golpe/GRID, HQSAR and others, using ten data sets representing various chemical series and diverse types of biological activity. It was shown that in the majority of cases the accuracy and predictivity of GUSAR models appeared to be better than for the reference QSAR methods. High predictive ability and robustness of GUSAR were also shown in leave-20%-out cross-validation procedure.
SAR and QSAR in Environmental Research, 2009, 20 (7-8), 679-709.