The proposed research seeks to gain knowledge of protein structure through increased understanding of the microscopic interactions and mechanisms of folding initiation. Peptide folding events will be studied using a novel combination of configurational energy methods, statistical mechanics and statistical clustering techniques. The microscopic mechanisms leading to nascent folding events are generally unknown. Two extremely long molecular dynamics simulations (2.2 nanoseconds each), recently carried out on a pentapeptide that forms stable reverse turns in solutions, will be analyzed by statistically based methods to identify folding pathways. The large number of conformations obtained from the simulations (>30,000) will be clustered into structurally similar groups. Transitions between the conformations in the reduced data set will be analyzed for concerted dihedral angle changes. The mechanisms causing these conformational transitions will be deduced from intra-peptide and peptide-solvent interactions, assessed for each cluster. This research develops new techniques for the analysis of large numbers of conformations resulting from long simulations, and the knowledge of folding pathways gained can lead to the design of more computationally efficient folding simulations. Cluster analysis and other surveys of protein structures have shown that certain N-cap and C-cap conformations dominate helix termini. Free energy simulations will be used to determine the free energy contribution of these capping structures to a- helix initiation and propagation, and their potential to act as helix stop signals. The free energy contributed to helix formation by charge/helix dipole interactions will be calculated, an the role of solvent structure in capping will be examined.
