The Tsetlin Machine: A “Third Way” in QSAR Modeling

lauses) for descriptor-wise contributions to regions of predicted chemical space. These methods show strong alignment of TM-QSAR interpretations to known ligand-protein interactions of the MOR target and gives nonlinear, conditional interpretations for greater predicted bioactivity. Given this combination of accuracy, computational efficiency and interpretability, we provide a basis for TM-QSAR to be explored as a standard methodology in virtual screening toolkits.