Peptides have attracted increasing attention over the past decade as a viable alternative to small molecules for developing drug molecules. For this internship, we propose to simulate the association and dissociation of protein – cyclic peptide complexes using advanced molecular dynamics simulations: the metadynamics approach using collective variables to accelerate the process of association and dissociation. The Parrinello group developed recently an improved metadynamics method, named “On-the-fly Probability Enhanced Sampling” (OPES) (Invernizzi and Parrinello, 2022), reducing the convergence times for suboptimal collective variables. Building on that, the Gervasio group combined OPES with REMD into “OneOPES” (https://github.com/valeriorizzi/OneOPES_tutorial/) to further reduce convergence times. They applied OneOPES to predict with a high accuracy the free energy of binding of protein – ligand complexes (Karrenbrock et al., 2024). Recently, we already adapted the OneOPES method to protein – cyclic peptide complexes with promising results. With the current internship project we would like improve our protocol to account better for the conformational flexibility of cyclic peptides. The improved protocol will be applied a set of protein – cyclic peptide complexes for which the experimental free energy of binding is already known. The goal is to explore the association and dissociation mechanisms, as well as to predict the free energy of binding.