Yu-Shan Lin, Tufts University

Title: Conformational sampling of cyclic peptides

Abstract: Protein–protein interactions (PPIs) play critical roles in cell adhesion, signal transduction, transcription regulation, and many other important and disease-relevant biological processes. Modulating PPIs thus provides a means to control diverse cellular functions for both fundamental research and therapeutic intervention. Unfortunately, protein–protein interfaces are challenging targets for traditional small molecules because the interfaces are relatively large and flat. Cyclic peptides (CPs) offer a promising solution for targeting PPIs, owing to their inherently large surface area and their ability to easily mimic functional groups and structures at protein interfaces. However, the high potential applicability of CPs is currently severely limited by our poor capacity to accurately predict CP structures. In this talk, we describe an efficient enhanced sampling method to simulate CPs. We found that because CPs are highly constrained, they have a limited set of motions they can use to switch conformations (which we term ‘essential transitional motions’). Our approach is to first identify and catalog these essential transitional motions of CPs by observing how flexible CPs switch conformations in standard molecular dynamics simulations. This collection of specific motions can then be leveraged to create enhanced sampling methods that greatly accelerate conformational sampling, allowing rapid simulations of more rigid CPs in explicit solvent. Using our enhanced sampling method, we aim to fill the knowledge gap of CP sequence–structure relationships, and enable rational design of CPs with desired structures.