To address these challenges, we introduce the MORE-Q dataset, which provides an extensive set of QM properties to accurately investigate the BOV-Receptor systems on a graphene surface, see Fig. . We have modeled 18 mucin-derived receptors and their combinations with 102 relevant skin BOV molecules -both systems containing heavy atoms C, N, O, and S. The number of atoms of the receptor molecules ranges from 37 to 102 atoms, while for BOV molecules varies from 7 to 53 atoms. We have followed an exhaustive and systematic procedure to generate the final complex systems (i.e., BOVreceptor-graphene system) and compute the QM properties, resulting in the creation of three MORE-Q subsets: i) MORE-Q-G1 contains the QM data of isolated single BOV and receptor molecules, ii) MORE-Q-G2 contains the QM data of diverse configurations of the BOV-receptor systems, and iii) MORE-Q-G3 contains the QM data of dimers deposited on the graphene surface (see Fig. ). The initial BOV and receptor molecules were optimized using the semi-empirical method GFN2-xTB that considers D4 dispersion correction . Then, the configurations of the 1, 836 BOV-receptor systems were screened by molecular docking using the automated Interaction Site Screening (aISS) submodule of the xTB code, applying the same level of theory as used in the geometry optimizations. Here, the hierarchical clustering method was used to filter similar geometries for each BOV-receptor combination, resulting in 23, 838 dimer configurations. To generate the complex systems, we have considered the most energy-favorable dimer configuration for each unique combination (ranked by the interaction energy