Protein-ligand binding affinity prediction is a key aspect in computational small molecule drug discovery. Several recent studies have demonstrated that molecular simulations based on alchemical absolute binding free-energy (ABFE) calculations are an accurate and broadly applicable tool for this purpose. However, the use of current ABFE protocols in large scale drug discovery projects occasionally leads to unstable simulations and poor convergence. To address these problems, we have implemented several optimizations of the ABFE protocol. First, a new algorithm to choose the protein-ligand pose restraints was developed to prevent numerical instabilities. By considering protein-ligand hydrogen bonds, the restraint selection now incorporates data on the key interactions to improve the convergence. Second, an optimization of the annihilation protocol was conducted to minimize the resulting error of the free energy. Third, a rearrangement of the order with which interactions (electrostatics, Lennard-Jones, restraints, intramolecular torsions) are scaled resulted in a systematic improvement of the precision. The results from four protein-ligand benchmark systems (TYK2, P38, JNK1, and CDK2) show significantly lower variances of the free energy results and improvements of up to 0.23 kcal/mol for the root-mean-square error, compared to the original protocol.
Wu et al. (Tue,) studied this question.