Convergence-Adaptive Roundtrip Method Enables Rapid and Accurate FEP Calculations

The free energy perturbation (FEP) method is a powerful
technique
for accurate binding free energy calculations, which is crucial for
identifying potent ligands with a high affinity in drug discovery.
However, the widespread application of FEP is limited by the high
computational cost required to achieve equilibrium sampling and the
challenges in obtaining converged predictions. In this study, we present
the convergence-adaptive roundtrip (CAR) method, which is an enhanced
adaptive sampling approach, to address the key challenges in FEP calculations,
including the precision-efficiency tradeoff, sampling efficiency,
and convergence assessment. By employing on-the-fly convergence analysis
to automatically adjust simulation times, enabling efficient traversal
of the important phase space through rapid propagation of conformations
between different states and eliminating the need for multiple parallel
simulations, the CAR method increases convergence and minimizes computational
overhead while maintaining calculation accuracy. The performance of
the CAR method was evaluated through relative binding free energy
(RBFE) calculations on benchmarks comprising four diverse protein–ligand
systems. The results demonstrated a significant speedup of over 8-fold
compared to conventional FEP methods while maintaining high accuracy.
The overall R2 values
of 0.65 and 0.56 were obtained using the combined-structure FEP approach
and the single-step FEP approach, respectively, in conjunction with
the CAR method. In-depth case studies further highlighted the superior
performance of the CAR method in terms of convergence acceleration,
improved predicted correlations, and reduced computational costs.
The advancement of the CAR method makes it a highly effective approach,
enhancing the applicability of FEP in drug discovery.