Other uses of AI in SBDD include, but are not limited to, potential energy functions that are similar to quantum-chemical descriptions (ANAKIN-ME) . For example, DFT-like interaction potentials at the computational cost of a geometrical optimization with molecular mechanics; force field development ; enhanced sampling by means of collective variables ; Boltzmann generators trained to identify transition states ; protein-ligand interaction fingerprints such as SPLIF or ECIF , and scoring functions like GNINA . Recently, the geometric DL approach was used to learn distance distributions and ligand-target interactions and to predict the binding conformation of bioactive compounds. This potential performs as well as or better than well-established scoring functions .