Hybrid methods are promising to enhance the performance of the current method without losing interoperability ( ). For example, a conventional molecular docking program, Vina ( ), can be executed to produce ligand poses. Then, an ML model can only order the outputs to improve the overall performance of molecular docking. As a result, such a method improves the performance without losing interpretability.