 DeNovo protein design can be improved by combining energy-based methods with deep learning techniques. Using AlphaFold2 or RoastEtaFold to assess the probability that a design sequence adopts the designed monomastructure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. Additionally, protein MPNN can be used to increase computational efficiency.