Ultrafast Shape Recognition 84 (USR) descriptors are characterised by a set of statistical moments of distance distributions created by measuring distances between atoms and reference points. USRCAT and Zernike descriptors are extension on these USR descriptors. USRCAT descriptors incorporate additional information about the presence of hydrophobic, aromatic, hydrogen bond donor, and acceptor atoms while Zernike descriptors replace statistical moments with projections on orthogonal basis functions. Both USRCAT and Zernike descriptors have been shown to outperform traditional USR descriptors in virtual screening benchmarks . In practical terms, we rely on the RDKit implementation of USRCAT and to calculate the Zernike descriptors efficiently, we make use of the just-in-time (JIT) compilation capabilities of the open-source LLVM package Numba .