Abstract
Recent increases in the availability of computational power have improved the accessibility of ligand–protein relative binding free energy (RBFE) calculations; however, these calculations remain resource-intensive, which can limit their practical application. RBFE calculations typically use a set of thermodynamic intermediates mediated by the transformation coordinate λ. Optimizing λ offers a way to tune the computational efforts required for a given RBFE calculation. Here, we present Adaptive Lambda Scheduling (ALS), a streamlined approach for on-the-fly bespoke λ scheduling. We show it can achieve substantial reductions in computational cost while retaining predictive performance.
