<div>The prediction of protein-ligand binding affinities using free energy perturbation
(FEP) is becoming increasingly routine in structure-based drug discovery. Most FEP
packages use molecular dynamics (MD) to sample the configurations of proteins and
ligands, as MD is well-suited to capturing coupled motion. However, MD can be prohibitively inefficient at sampling water molecules that are buried within binding sites,
which has severely limited the domain of applicability of FEP and its prospective usage
in drug discovery. In this paper, we present an advancement of FEP that augments
MD with grand canonical Monte Carlo (GCMC), an enhanced sampling method, to
overcome the problem of sampling water. We accomplished this without degrading
computational performance. On both old and newly assembled data sets of proteinligand complexes, we show that the use of GCMC in FEP is essential for accurate and
robust predictions for ligand perturbations that disrupt buried water. <br></div>
Publisher’s Note: “Computation of binding free energy with molecular dynamics and grand canonical Monte Carlo simulations” [J. Chem. Phys. 128, 115103 (2008)]
