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.jmannino.com/best-catch-University-of-Miami-The-U-iPhone-14-Plus-Clear-Case-p36265-quick-deal/