Genetic algorithms as a tool for helix design--computational and experimental studies on prion protein helix 1.

Evolutionary computing is a general optimization mechanism successfully implemented for a variety of numeric problems in a variety of fields, including structural biology. We here present an evolutionary approach to optimize helix stability in peptides and proteins employing the AGADIR energy function for helix stability as scoring function. With the ability to apply masks determining positions, which are to remain constant or fixed to a certain class of amino acids, our algorithm is capable of developing stable helical scaffolds containing a wide variety of structural and functional amino acid patterns. The algorithm showed good convergence behaviour in all tested cases and can be parameterized in a wide variety of ways. We have applied our algorithm for the optimization of the stability of prion protein helix 1, a structural element of the prion protein which is thought to play a crucial role in the conformational transition from the cellular to the pathogenic form of the prion protein, and which therefore poses an interesting target for pharmacological as well as genetic engineering approaches to counter the as of yet uncurable prion diseases. NMR spectroscopic investigations of selected stabilizing and destabilizing mutations found by our algorithm could demonstrate its ability to create stabilized variants of secondary structure elements.