In an attempt to facilitate computer-aided kinase similarity studies, we here aim to add another perspective. Binding site comparison methods employed so far can be applied to any binding site regardless of the protein class. Kuhn et al. have applied such a method, Cavbase, to the structurally resolved kinome and could detect expected and unexpected kinase relationships. Since kinases are highly conserved and have been aligned and annotated across the full structurally covered kinome, a binding site comparison method tailored to kinases may provide an extended perspective on kinase similarities. We make use of data in the KLIFS database, a rich resource for kinase research that extracts protein kinasefocused information on structures from the PDB, on inhibitors in clinical trials from the PKIDB, on bioactivities from ChEMBL, and much more. All kinase structures from the PDB are split into single chains and models and aligned with respect to sequence and structure across the full structurally covered kinome. The KLIFS authors defined the kinase pocket as a set of 85 residues that interact with co-crystallized ligands in the initial KLIFS dataset of more than 1200 structures. Thanks to this structural alignment, it is possible to look up all 85 residues in any kinase structure, given the residue is structurally resolved and not in a gap position. This pocket alignment is the basis for the here introduced KiSSim fingerprint.