The kinase-focused and subpocket-enhanced KiSSim (Kinase Structural Similarity) fingerprint builds on the KLIFS 14 pocket, whose alignment allows a computationally inexpensive residue-by-residue comparison. The residues' physicochemical and spatial properties are encoded within their structural context including important kinase subpockets -the hinge region, DFG region, and front pocket -building on features from previously published methods such as SiteAlign, KinFragLib, and Ultrafast Shape Recognition (USR). We used the fingerprint to calculate all-against-all similarities within the structurally covered kinome and to generate a KiSSim-based kinome tree. Detected similarities can be used to predict off-targets or guide polypharmacology studies and to rationalize profiling observations on a structural level. We distribute the method as an open source Python package at and as conda package, alongside the data and analyses notebooks at to support FAIR science.