Computational Screening and Selection of Cyclic Peptide Hairpin Mimetics by Molecular Simulation and Kinetic Network Models

Designing peptidomimetic compounds to have a preorganized structure in solution is highly nontrivial. To show how simulation-based approaches can help speed this process, we performed an extensive simulation study of designed cyclic peptide mimics of a beta-hairpin from bacterial protein LapD involved in a protein protein interaction (PPI) pertinent to bacterial biofilm formation. We used replica exchange molecular dynamics (REMD) simulation to screen 20 covalently cross-linked designs with varying stereochemistry and selected the most favorable of these for massively parallel simulation on Folding@home in explicit solvent. Markov state models (MSMs) built from the trajectory data reveal how subtle chemical modifications can have a significant effect on conformational populations, leading to the overall stabilization of the target structure. In particular, we identify a key steric interaction between a methyl substituent and a valine side chain that acts to allosterically shift population between native and near-native states, which could be exploited in future designs. Visualization of this mechanism is aided considerably by the tICA method, which identifies degrees of freedom most important in slow conformational transitions. The combination of quantitative detail and human comprehension provided by MSMs suggests such approaches will be increasingly useful for design.