Accelerare la scoperta di farmaci attraverso la predizione dell’affinità di legame dei ligandi

Predicting ligand binding affinity is a central challenge in drug discovery. This thesis focuses on two molecular dynamics-based approaches for estimating binding strength: Thermal Titration Molecular Dynamics (TTMD) and Free Energy Perturbation (FEP). TTMD, developed and optimized in this work, is a qualitatively-based, but fast and easy to settle method that evaluates complex stability under increasing thermal stress, allowing effective ligand ranking and binding pose validation across proteins, nucleic acids, and fragment-based systems. In parallel, FEP methods were explored in collaboration with Evotec to support membrane protein targets such as GPCRs. This work focused on adapting and benchmarking protocols, with the aim of integrating FEP for membrane proteins into Evotec’s drug discovery pipelines. While quantitative results using Absolute Binding Free Energy (A3FE) are not yet available, the initial adaptation establishes a foundation for future industrial applications. Together, these studies highlight the potential of molecular dynamics-based approaches to predict binding affinities, providing both a fast qualitative tool (TTMD) and a framework for rigorous quantitative calculations in drug discovery.