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Ranking the binding of small molecules to protein receptors throughphysics-based computation remains challenging. Though inroads have been madeusing free energy methods, these fail when the underlying classical mechanicalforce fields are insufficient. In principle, a more accurate approach isprovided by quantum mechanical density functional theory (DFT) scoring, buteven with approximations, this has yet to become practical on drugdiscovery-relevant timescales and resources. Here, we describe how to overcomethis barrier using algorithms for DFT calculations that scale on widelyavailable cloud architectures, enabling full density functional theory, withoutapproximations, to be applied to protein-ligand complexes with approximately2500 atoms in tens of minutes. Applying this to a realistic example of 22ligands binding to MCL1 reveals that density functional scoring outperformsclassical free energy perturbation theory for this system. This raises thepossibility of broadly applying fully quantum mechanical scoring to real-worlddrug discovery pipelines.

Novel algorithms and high-performance cloud computing enable efficient fully quantum mechanical protein-ligand scoring