Deterministic Global Optimization and Ab Initio Approaches for the Structure Prediction of Polypeptides, Dynamics of Protein Folding, and Protein-Protein Interactions

Summary

The authors first outline the basics of the deterministic global optimization approach, αBB, which has been used extensively to study the protein structure prediction, dynamics of protein-protein folding, and protein docking problems. This is followed by a comprehensive study of ab initio modeling for structure prediction of single-chain polypeptides in Section III. An extensive comparison of energy modeling, including solvation, entropic effects, and free energy calculations, is provided for the oligopeptides. The related problem of restrained structure refinement in the presence of sparse experimen-tally derived restraints is also discussed. Section IV moves beyond the static structure prediction problem toward an understanding of the dynamics of protein folding. An in-depth analysis of the coil-to-helix transition is provided for the alanine tetrapeptide. This analysis includes the elucidation of folding pathways and the identification of plausible reaction coordinates. Section V addresses the peptide docking problem. First, an approach for the determination of binding site structure is introduced. This is followed by a decomposition-based approach for the prediction of relative binding affinities. Both approaches are applied to peptide docking in HLA molecules.