Active Learning for Absolute Binding Free Energy Calculations in Drug Discovery

Explore a 23-minute conference talk by Steven Jerome, Director of Hit Discovery at Schrodinger, on active learning techniques for absolute binding free energy calculations in drug discovery. Gain insights into cutting-edge computational methods that enhance the efficiency and accuracy of predicting protein-ligand binding affinities. Learn how active learning approaches can optimize the selection of compounds for free energy calculations, potentially accelerating the drug discovery process. Discover the application of machine learning algorithms in guiding molecular simulations and improving the predictive power of binding free energy models. Understand the implications of these advanced techniques for streamlining lead optimization and reducing the time and cost associated with drug development.