Before constructing our complex CPLX system (i.e., BOV-receptor-graphene system), we have determined the optimal configuration for the molecular receptor adsorbed on the graphene layer. In this regard, it is known that ππ stacking interaction is the main functionalization mechanism of the mucin-derived receptor. Accordingly, the receptor configuration with the maximal pyrene rings interacting with graphene will be the most stable receptor-graphene system (referred to as the SUB system). Based on this concept, we initially deposited each receptor on graphene in up to four configurations with diverse orientations, which were subsequently optimized using GFN2-xTB methods with D4 correction and tight settings of convergence. Then, the most stable configurations with the lowest adsorption energy were taken as the backbone structures, which were used to further generate the MORE-Q datasets, as shown in Fig. . Note that a more exhaustive evaluation of the conformational space of the molecular receptors may yield different results. However, the main focus of the current work is to define the pathways for understanding and predicting QM-based structure-property and property-property relationships in potential molecular sensors for digital olfaction. Thus, the selection of these configurations represents the most likely configurations and, therefore, ensures the baseline quality of the dataset.