Pharmacophoric and size features are taken from the SiteAlign categories for standard amino acids. They encode the size based on the number of heavy atoms, the number of hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), the charge (negative, neutral, or positive), and aromatic and aliphatic properties (present or not present) of a residue (Table ). The side chain orientation (inward-facing, intermediate, or outward-facing) is based on the vertex angle from the residue's CA atom (vertex) to the pocket center and to the residue's outermost side chain atom, the side chain representative (Table ). The solvent exposure of a residue (high, intermediate, or low) is based on the ratio of CA atoms in the upper half of a sphere that is placed around the residue's CA atom (radius 12 Å) and cut in half by a normal plane spanned by the residue's CA-CB vector, as implemented in BioPython's HSExposure module. Spatial properties are described by discrete values, i.e., distances and moments. Spatial distances are calculated from each residue's CA atom to the pocket's geometric center and to prominent subpocket centers. The pocket center is the centroid of all pocket CA atoms. The selected subpocket centers include functionally well-characterized kinase regions such as the hinge region, DFG region, and front pocket. Each subpocket center is calculated based on the centroid of three anchor residues' CA atoms (Table ), following the idea described in the KinFragLib methodology. We added the code to calculate the subpocket centers to the structural cheminformatics library OpenCADD (module opencadd.structure.pocket) to allow for easy access in other projects. Spatial moments describe each of the four distributions of distances to the pocket center, hinge region, DFG region, and front pocket. In KiSSim, the first three moments are used: the mean, the standard deviation, and the cube root of the skewness. This procedure is inspired and adapted from the ligand-based Ultrafast Shape Recognition (USR) method.