Each pharmaceutical research and development project is aimed at discovering new drugs for the treatment of certain diseases. The investigation of new pharmaceuticals is carried out in a stepwise manner. This is because drug discovery is a time-consuming process involving enormous financial resources and manpower, and with a substantially high risk factor. On average, it requires 12 years and approximately $800 million for introducing a new medicine to the market (1) with a high risk of negative results (1 out of 10,000

substances studied is developed to a safe and potent drug). Drug research starts with identification of a ‘‘lead molecule’’ with required biological activity. Subsequently, the lead molecule is developed to get more potent compounds with appropriate pharmacodynamic and pharmacokinetic properties that can qualify as drug candidates (2). General biological potential of any molecule under study is also evaluated in stages. The emphasis is first laid on testing for specific activity followed by general pharmacology and toxicology study, clinical trials, postmarketing registration of adverse effects, etc. As a result, adverse=toxic actions are often discovered at a stage when a lot of time and money are already expended (3). At the same time, it is practically impossible to test experimentally all compounds against each known kind of biological activity and possible toxic effects. So, a computeraided prediction is the ‘‘method of choice’’ at the early stage of drug research. Relying on predicted results, one may establish the priorities for testing a particular compound and the basis for selecting the most prospective hits=leads=candidates from the set of compounds available for screening. Application of computational methods has significantly decreased the time required for obtaining a compound with the required properties with reduction in financial expenditure. In addition, it helps to obtain more effective and safety medicines.