RIMANDATO

Understanding the interactions between molecular entities and cellular membranes is essential for several biotechnological applications, including targeted drug delivery. However, accurately estimating the free energy landscape associated with membrane translocation events remains a significant computational challenge. This seminar will focus on the use of enhanced sampling techniques to elucidate the internalization mechanisms of small molecules and peptides within membranes, providing atomistic details. The results presented will demonstrate the effectiveness of integrating machine learning techniques with molecular simulations for the optimal selection of Collective Variables (CVs) in enhanced sampling methods. This computational protocol offers a promising approach for estimating the free energy landscape of molecular translocation events, potentially aiding the development of biotechnological tools for drug delivery.