  Ranking the binding of small molecules to protein receptors through
physics-based computation remains challenging. Though inroads have been made
using free energy methods, these fail when the underlying classical mechanical
force fields are insufficient. In principle, a more accurate approach is
provided by quantum mechanical density functional theory (DFT) scoring, but
even with approximations, this has yet to become practical on drug
discovery-relevant timescales and resources. Here, we describe how to overcome
this barrier using algorithms for DFT calculations that scale on widely
available cloud architectures, enabling full density functional theory, without
approximations, to be applied to protein-ligand complexes with approximately
2500 atoms in tens of minutes. Applying this to a realistic example of 22
ligands binding to MCL1 reveals that density functional scoring outperforms
classical free energy perturbation theory for this system. This raises the
possibility of broadly applying fully quantum mechanical scoring to real-world
drug discovery pipelines.
