In this work we have explored the potential benefits of using ML models to enhance virtual screening studies for molecules with low reorganization energies λ. We find that this is a challenging setting for molecular ML, both because of the conformational flexibility of the molecules and the intrinsic difficulty of predicting λ from the equilibrium geometry alone. Both aspects can be mitigated by using a semiempirical electronic structure method for conformer searching and as a baseline model.