Abstract: Described is a system for automatically identifying chemical properties of a molecule. A chemical representation of a molecular structure is converted into atomic features and an adjacency matrix. The atomic features and the adjacency matrix are processed with a neural network, resulting in neural activations corresponding to each atom in the molecular structure. The system determines a probability for each atom quantifying its relevance for a given chemical characteristic. The probabilities are displayed as a graphical representation on the molecular structure, and groups of atoms are identified for the given chemical characteristic from the graphical representation. The identified groups of atoms for the given chemical characteristic are stored in a database, and a new molecule having the given chemical characteristic is designed based on the stored identified groups of atoms.