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Directed evolution of trypsin inhibiting peptides using a genetic algorithm
Abstract
A new strategy which employs a process of directed evolution in the search for molecules exhibiting certain desirable properties is reported. By repeating a cycle of peptide synthesis, evaluation of the trypsin inhibitory activities of these peptides and subsequent selection and transformation based on a genetic algorithm, it is possible artificially to induce the evolution of a family of peptides and improve their biological activities. Commencing with a set of 24 randomly generated hexapeptides, a progressive improvement from 16 to 50% average inhibitory activity over six generations, with maximum activities of 80–90% is observed. The emergence of consensus sequences which concur with those previously generated using peptide libraries is also observed.
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