Using Computational Modeling to Understand the Binding Mechanism of Designed Cyclic β-Hairpin to MDM2

Understanding mechanisms of protein folding and binding is crucial to designing their molecular function. Molecular dynamics (MD) simulations have become a powerful tool to understand the atomic details underlying complex processes. Together with Markov State Models (MSMs), these approaches have shown great success in understanding conformational change that occurs over long timescales, which may be important in drug design. The MDM2-p53 protein-peptide interaction is a well-studied model system that is both therapeutically relevant and used frequently in methodology development. Cyclic peptide binders of MDM2 have become attractive as therapeutics due to their high stability and preorganization in solution. In this work, we performed massively parallel explicit-solvent molecular dynamics simulations of designed cyclic β-hairpins on the [email protected] distributed computing platform. MSM analysis of the over 3-ms aggregate trajectory data enabled us to build a detailed mechanistic model of coupled folding and binding of cyclic peptides that can be compared to experimental binding affinities and rates. The MSMs allows us to assess the relative stability of each ligand in solution and capture a number of non-native interactions which lead to misfolded states. Our MSM models imply a conformational selection mechanism of cyclic β-hairpin binding, a result which helps inform future drug design studies targeting MDM2.