We have developed a novel strategy for rational design of targeted peptide libraries. The goal of this method is to select a subset of natural amino acids that are most likely to be present in active peptides for the synthesis of library. Two different protocols are employed where chemical structures of peptides are described either by topological indices or by a combination of physicochemical descriptors for individual amino acids. The selection of a peptide as a candidate for the targeted library is based either on its chemical similarity to a biologically active probe or on its biological activity predicted from a preconstructed quantitative structure-activity (QSAR) equation. The optimization of the library is achieved by means of genetic algorithms (GA). This method was tested by rational design of the library with bradykinin-potentiating activity. Twenty-eight bradykinin-potentiating pentapeptides were used as a training set for the development of a QSAR equation, and, alternatively, two active pentapeptides, VEWAK and VKWAP, were used as probe molecules. In each case, the frequency distribution of amino acids in the top 100 peptides suggested by the method resembles the frequency distribution of amino acids found in the active peptides. The results obtained after GA optimization also compared favorably with those obtained by the exhaustive analysis of all possible 3.2 million pentapeptides.