Additionally, SpaiNN facilitates communication between SchNetPack 2.0 and SHARC 3.0 through the spainn.calculator.SPaiNNulator class. This functionality allows trained ML models to furnish quantum chemical properties (calculate) or SHARC predictions (get_qm) for molecular structures. A comprehensive description of the data pipeline can be found in the supporting information (section S1) and a code documentation is available as "Read the Docs" page. In the following, we focus on certain properties that are essential for ML but for a comprehensive overview of the other parts of NAMD simulations with SHARC see references 36 and 39.