where 𝜖 0 is the vacuum permittivity. Since analytic integration of the Coulomb potential at 𝒓 = 0 is not possible, we provide options to either approximate each potential with a sum of three Gaussian functions and integrate the fit function analytically analogous to Good et al. or to perform a Monte-Carlo integration over the space outside of the van-der-Waals radii of each atom, and inside a user-defined margin. Partial charges can either be supplied by the user, calculated via RDKit (Gasteiger or MMFF94 charges), predicted via a recent machine-learning (ML) model, or computed using the open-source quantum chemistry program Psi4, with the option of using Restrained Electrostatic Potential (RESP) charges. There are a range of different methods and basis sets available in Psi4. For example, the oftenrecommended combination of using the B3LYP method and the 6-31G** basis set, although using those can be computational demanding. Within DeepFMPO, Dask, a library for parallel computing in Python, is used to speed up the process. It should be noted that the RESP/Psi4 method is not parametrized for atoms beyond the atomic number of Argon. To allow for larger atoms (e.g., bromine), their van der Waals (vdW) radius needs to be specified separately. In this code version, we set the vdW radii for bromo to 1.8 (file: resp/vdw_surface.py), following the GAMESS scheme 34 derived from the Merz-Kollman-Singh publication. In addition to electrostatic similarities, ESP-Sim can furthermore output the shape Tanimoto similarity of molecules, describing the volume overlap. For DeepFMPO, we used the Tanimoto similarity of electrostatic potentials obtained via fitting to Gaussian functions (ESP-Tanimoto). We furthermore provide an option to add the volumetric shape score resulting in an ESP-TanimotoCombo score.