In summary, the QUID benchmark framework presents a novel approach for accurately analyzing ligand interactions at various protein binding sites, facilitating the development of robust QM datasets for reliable predictions of binding affinities and structural conformations. While the insights gained from this work highlight the importance of an appropriate QM description for inter-and intramolecular properties of ligand-pocket motifs, we acknowledge that further efforts should incorporate more flexible and charged pocket structures, as well as solvation effects . The sampled chemical space should ultimately encompass full pocket-ligand molecular systems, similar to those in MM datasets (e.g. PL-REX and QR50 ), to enhance the reliability of the findings. We expect this work to pave the way for a more informed use and refinement of physical and chemical models for simulating ligand-pocket interactions, offering particular value in fine-tuning MLFFs and ML-augmented semiempirical models, which are increasingly integrated into screening pipelines for drug discovery.