It has been shown that calculating atomic charges using quantum mechanical level theory greatly improves the accuracy of docking. A protocol was developed and shown to be effective. That this protocol works is just a manifestation of the fact that electrostatic interactions are important in protein-ligand binding. In order to investigate how the same protocol helps in prediction of binding affinities, we took a series of known cocrystal structures of influenza neuraminidase inhibitors with the receptor and performed docking with Glide SP, Glide XP, and QPLD, the last being a workflow that incorporates QM/MM calculations to replace the fixed atomic charges of force fields with quantum mechanically recalculated ones at a given docking pose, and predicted the binding affinities of each cocrystal. The correlation with experimental binding affinities considerably improved with QPLD compared to Glide SP/XP yielding $r^2$ = 0.83. The results suggest that for binding sites, such as that of neuraminidase, which are laden with hydrophilic residues, protocols such as QPLD which utilizes QM-based atomic charges can better predict the binding affinities.