Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations

TL;DR

Dual-LAO is a novel method that dramatically accelerates relative binding free energy calculations, enabling routine use in drug discovery with high accuracy even for complex molecular transformations.

Contribution

It introduces dual-LAO, a highly efficient RBFE calculation method that combines dual-topology setup and restraints, significantly improving speed and reliability over existing approaches.

Findings

Achieves 15 to 30 times acceleration compared to state-of-the-art methods.

Successfully handles complex transformations like scaffold-hopping and charge changes.

Maintains high accuracy in predicting binding free energies.

Abstract

Relative Binding Free Energy (RBFE) calculations are a cornerstone of rational hit-to-lead and lead optimization in modern drug discovery. However, the high computational cost and limited reliability in tackling large or complex molecular transformations often prevent their routine, high-throughput use. Here we introduce dual-LAO, a novel, highly efficient method for calculating RBFE. Building on the Lambda-ABF-OPES framework, this method combines a dual-topology setup and suitable restraints to dramatically accelerate free energy convergence. We demonstrate that dual-LAO, in combination with the AMOEBA polarizable force field, achieves an unprecedented acceleration factor of 15 to 30 times compared to current state-of-the-art methods on standard drug targets. Crucially, the approach maintains high accuracy and successfully tackles previously prohibitive molecular changes, including scaffold-hopping, buried water displacement, charge changes, ring-opening, and binding pose perturbations. This significant leap in efficiency allows for the widespread, routine integration of predictive molecular simulations into the rapid optimization cycles of drug discovery, enabling chemists to confidently model historically challenging systems in timescales compatible with real-world project deadlines.