Development of a Genetic Algorithm to Design and Identify Peptides that can Cross the Blood‐Brain Barrier

The design of peptide drugs to treat central nervous system (CNS) diseases is hampered by our ignorance of the factors that determine whether a given peptide can cross the blood‐brain‐barrier (BBB). We are developing an approach to this problem that combines computer‐aided ligand design, parallel synthesis of peptide libraries, and biological evaluation using in vitro BBB models. We present a genetic algorithm (GA) to search for peptides that can cross the BBB. In the design and optimization of this GA we used a genetic meta‐algorithm to optimize the GA parameters. The GA is validated in silico by virtual screening of a peptide library of more than 1015 molecules. We used a virtual fitness function dervied from statistical analysis of the few experimental data on peptide‐BBB permeability available.