Accurate density functional theory for noncovalent interactions in charged systems

Accurately modeling noncovalent interactions (NCIs) involving charged systems remains an outstanding challenge in density functional theory (DFT), with implications across natural and life sciences, engineering, e.g., in biochemistry, catalysis, and materials science. For these interactions, the interplay between electrostatics, polarization, and dispersion leads to systematic errors of up to tens of kilocalories per mole in standard dispersion-enhanced DFT methods. We solve this problem by introducing (r²SCAN+MBD)@HF, a DFT method without empirically fitted parameters that combines the r²SCAN functional and many-body dispersion, both evaluated on Hartree-Fock densities. We show that the unique synergy of these three components enables balanced treatment of short- and long-range correlation, which is crucial for accurate description of NCIs involving charged systems. Evaluations on standard benchmarks show that (r²SCAN+MBD)@HF significantly improves accuracy for NCIs involving charged systems while maintaining robust performance for neutral systems. Further tests on the Metal Ion Protein Clusters dataset introduced here demonstrate its improved accuracy for metal-protein interactions, including cases where the metal ion is surrounded by negatively charged ligands for which standard DFT can completely break down. Given the ubiquity of such interactions, (r²SCAN+MBD)@HF is broadly applicable from biochemistry and materials science, including for generating high-quality data to train machine-learning force fields.