Ab initio structure prediction for small polypeptides and protein fragments using genetic algorithms.

Abstract

Ab initio folding simulations have been performed on three peptides, using a genetic algorithm-based search method which operates on a full atom representation. Conformations are evaluated with an empirical force field parameterized by a potential of mean force analysis of experimental structures. The dominant terms in the force field are local and nonlocal main chain electrostatics and the hydrophobic effect. Two of the simulated structures were for fragments of complete proteins (eosinophil-derived neurotoxin (EDN) and the subtilisin propeptide) that were identified as being likely initiation sites for folding. The experimental structure of one of these (EDN) was subsequently found to be consistent with that prediction (using local hydrophobic burial as the determinant for independent folding). The simulations of the structures of these two peptides were only partly successful. The most successful folding simulation was that of a 22-residue peptide corresponding to the membrane binding domain of blood coagulation factor VIII (Membind). Three simulations were performed on this peptide and the lowest energy conformation was found to be the most similar to the experimental structure. The conformation of this peptide was determined with a C alpha rms deviation of 4.4 A. Although these simulations were partly successful there are still many unresolved problems, which we expect to be able to address in the next structure prediction experiment.