Abstract
Predicting the binding affinity of ligands to protein pockets is key in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a range of attractive and repulsive electronic interactions during binding. Accurately accounting for all interactions requires robust quantum-mechanical (QM) benchmarks, which are scarce for ligand-pocket systems. Additionally, disagreement between “gold standard” Coupled Cluster (CC) and Quantum Monte Carlo (QMC) methods casts doubt on many benchmarks for larger non-covalent systems. We introduce the “QUantum Interacting Dimer” (QUID) benchmark framework containing 170 non-covalent (non-)equilibrium systems modeling chemically and structurally diverse ligand-pocket motifs. Symmetry-adapted perturbation theory shows that QUID broadly covers non-covalent binding motifs and energetic contributions. Robust binding energies are obtained using complementary CC and QMC methods, achieving agreement of 0.5 kcal/mol. The benchmark data analysis reveals that several dispersion-inclusive density functional approximations provide accurate energy predictions, though their atomic van der Waals forces differ in magnitude and orientation. Contrarily, semiempirical methods and empirical force fields require improvements in capturing non-covalent interactions (NCIs) for out-of-equilibrium geometries. The wide span of NCIs, highly accurate interaction energies, and analysis of molecular properties take QUID beyond the “gold standard” for QM benchmarks of ligand-protein systems.
| Original language | English |
|---|---|
| Article number | 8583 |
| Journal | Nature Communications |
| Volume | 16 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
Funding
M.P. acknowledges with gratitude financial support from the Institute for Advanced Studies (IAS) Luxembourg for the PhD “Young Academics” program. A.T. was funded by the Luxembourg Research Fund (FNR Core Grant MBD-in-BMD/18093472). The authors thank Matteo Barborini and Matteo Gori for their support and discussions, Sergio Suárez Dou for his support in biomolecular force fields, and Gregory Cordeiro Fonseca for the support in the use of his FFAST software. The financial support from the ERC Starting Grant No. 101076972, “aCCuracy”, the ERC Advanced Grant No. 101054629 “FITMOL”, the National Research, Development, and Innovation Office (NKFIH, Grant No. FK142489), the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, and the computing time granted by the Hungarian Governmental Information-Technology Development Agency on the Komondor and the LEONARDO supercomputers are gratefully acknowledged. Some of the calculations presented in this paper were carried out using the HPC facilities of the University of Luxembourg120 (see hpc.uni.lu). The QMC simulations were performed on the Luxembourg national supercomputer MeluXina. The authors gratefully acknowledge the LuxProvide teams for their expert support. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. M.P. acknowledges with gratitude financial support from the Institute for Advanced Studies (IAS) Luxembourg for the PhD “Young Academics” program. A.T. was funded by the Luxembourg Research Fund (FNR Core Grant MBD-in-BMD/18093472). The authors thank Matteo Barborini and Matteo Gori for their support and discussions, Sergio Suárez Dou for his support in biomolecular force fields, and Gregory Cordeiro Fonseca for the support in the use of his FFAST software. The financial support from the ERC Starting Grant No. 101076972, “aCCuracy”, the ERC Advanced Grant No. 101054629 “FITMOL”, the National Research, Development, and Innovation Office (NKFIH, Grant No. FK142489), the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, and the computing time granted by the Hungarian Governmental Information-Technology Development Agency on the Komondor and the LEONARDO supercomputers are gratefully acknowledged. Some of the calculations presented in this paper were carried out using the HPC facilities of the University of Luxembourg (see hpc.uni.lu ). The QMC simulations were performed on the Luxembourg national supercomputer MeluXina. The authors gratefully acknowledge the LuxProvide teams for their expert support. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.