Natural products found a wide use in folk medicine. Presently, when routine development of new drugs faced a considerable challenge, they become an inspiration and valuable source in drugs discovery. Rather complex and diverse chemical structures of natural compounds provide a basis for modulation of different biological targets. Natural compounds exhibit a multitargeted action that may lead to additive/synergistic or antagonistic effects. Rational design of more safe and potent pharmaceuticals requires an estimation of probable multiple actions of natural products. Our software PASS can perform such estimation. It predicts with reasonable accuracy over 3500 pharmacotherapeutic effects, mechanisms of action, interaction with the metabolic system, and specific toxicity for drug-like molecules on the basis of their structural formulae. We analyzed PASS predictions utilizing PharmaExpert, which performs selection of compounds with multiple mechanisms of action, analysis of activity-activity relationships and drug-drug interactions. The paper describes an application of PASS and PharmaExpert to the evaluation of biological activity of natural compounds including marine sponge alkaloids, triterpenoids of lupane group, and their derivatives. Proposed computer-aided methods can generate combinatorial libraries of macrolides. They help to select the most promising pharmaceutical leads with the required properties. Case study, based on the analysis of biological activity spectra predicted for St John’s Wort constituents, clearly demonstrates capabilities of computational methods in the evaluation of multitargeted actions, additive/synergistic and/or antagonistic effects of natural products.
Current Pharmaceutical Design, 2010, 16 (15), 1703-1717.

Computer aided prediction of biological activity spectra has been carried out for 50 new thiazolyl and benzothiazolyl derivatives. Predicted activity spectra for different compounds from the set include 1±8 activities with estimated probability to be found more than 50%, which cover both possible therapeutic and adverseyside effects. Experimental data coincide with the prediction for 25 of 39 compounds tested as NSAIDs (64.1%); for 4 of 6 compounds tested as local anaesthetics (66.7%); for 1 compound tested as antioxidants (100%). The concordance that describes the overall percentage of correct predictions equals to 65.2% that is sufficient to use this approach for optimization of biological testing. In particular, the compounds from studied data set will be further tested according to the additional predicted activities. Description of the current version of computer system PASS and feasibility for free testing is available via Internet on http://www.ibmh.msk.su/ PASS.
Quantitative Structure-Activity Relationships, 18 (1) 16-25.