Combining QM/MM Calculations with Classical Mining Minima to Predict Protein–Ligand Binding Free Energy

We
developed an effective binding free energy prediction protocol
which incorporates quantum mechanical/molecular mechanical (QM/MM)
calculations to substitute the specified atomic charges of force fields
with quantum-mechanically recalculated ones at a proposed pose using
a mining minima approach with the VeraChem mining minima engine. We
tested this protocol using seven well-known targets with 147 different
ligands and compared it with classical mining minima and the most
popular binding free energy (BFE) methods using different metrics.
Our new protocol, dubbed Qcharge-VM2, yielded an overall Pearson correlation
of 0.86, which was better than all the methods examined. Qcharge-VM2
performed significantly better than implicit solvent-based methods,
such as MM-GBSA and MM-PBSA, but not as good as explicit water-based
free energy perturbation methods, such as FEP+, in terms of root-mean-square
error, RMSE (1.75 kcal/mol) and mean unsigned error, MUE (1.39 kcal/mol)
on a limited set of targets. However, our protocol is substantially
less computationally demanding compared with FEP+. The combined accuracy
and efficiency of our method can be valuable in drug discovery campaigns.