Peptides fulfill many tasks in controlling and regulating cellular functions and are key molecules in systems biology. There is a great demand in science and industry for a fast search of innovative peptide structures. In this chapter we introduce a combination of a computer-based guided search of novel peptides in sequence space with their biological experimental validation. The computer-based search uses an evolutionary algorithm that includes artificial neural networks as fitness function and a mutation operator, called the PepHarvester. Optimization occurs during 100 iterations. This system, called DARWINIZER, is applied in the de novo design of neutralizing peptides against autoantibodies from DCM (dilatative cardiomyopathy) patients. Another approach is the optimization of peptide sequences by an ant colony optimization process. This biologically-oriented system identified several novel weak binding T-cell epitopes.
Correction: De Novo Peptide Design and Experimental Validation of Histone Methyltransferase Inhibitors