Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions

Predicting the binding affinity of ligand molecules to protein pockets is a key step in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a wide range of attractive and repulsive electronic interactions invoked upon binding. Accurately accounting for all these interactions on equal footing requires robust quantum-mechanical (QM) benchmarks, which are scarce for ligand-pocket systems. In addition, the puzzling disagreement between ``gold standard'' Coupled Cluster (CCSD(T)) and Quantum Monte Carlo (QMC) methods [Nat. Commun. 12, 3927 (2021)] casts doubt on many existing benchmarks for larger non-covalent systems. Here, we introduce the ``Quantum Interacting Dimer'' (QUID) benchmark framework containing 170 non-covalent systems spanning equilibrium and non-equilibrium geometries that model chemically and structurally diverse ligand-pocket motifs. Symmetry-adapted perturbation theory shows that QUID broadly covers non-covalent binding motifs and energetic (exchange-repulsion, electrostatic, induction, and dispersion) contributions. Robust and reproducible binding energies are obtained using two complementary QM methods: LNO-CCSD(T) and QMC, achieving mutual agreement of 0.3 kcal/mol. Analysis of this benchmark data reveals that several dispersion-inclusive density functional approximations provide accurate energy predictions, though they exhibit discrepancies in magnitude and orientation of atomic van der Waals forces, which could influence the dynamics of ligands within the pocket. On the contrary, semiempirical methods and widely used empirical force fields require improvements, particularly in capturing non-covalent interactions (NCIs) for out-of-equilibrium geometries. The wide span of molecular dipole moments and polarizabilities in QUID also demonstrates flexibility in designing pocket structures to achieve desired binding properties. Therefore, QUID sets a new ``platinum standard'' for reliable and reproducible QM benchmarks of NCIs in larger systems and enhances our understanding of biomolecular ligand-pocket interactions.