With the MMPA, we aim to identify key substructures which are responsible for transformation of a lysosomotropic compound to a non-lysosomotropic compound, and vice-versa. Similarly, by interpreting tree-based Machine learning (ML) models with molecular fingerprints we address the identification of important substructures whose presence a↵ects lysosomotropism. Finally, by interpreting ML models with molecular descriptors as input, the determination of physicochemical parameters which a↵ect lysosomotropism is attempted.