Abstract Graph Neural Networks (GNNs) excel in compound property and activity prediction. but the choice of molecular graph representations significantly influences model learning and interpretation. While atom-level molecular graphs resemble natural topology. they overlook key substructures or functional groups and their interpretation partially aligns with chemical intuition. https://www.roneverhart.com/HP-Pavilion-15-eg1053cl-15-6-FHD-Touch-Intel-Core-i5-1235U-3-30-GHz-Intel-Iris-Xe-Graphics-12-GB-DDR4-RAM-512-GB-SSD-/