I am trying to understand how accurate the docking predictions are. Looking at the PoseBusters paper [1] they mention, they say they are 50% more accurate than

I am trying to understand how accurate the docking predictions are. Looking at the PoseBusters paper [1] they mention, they say they are 50% more accurate than traditional methods. DiffDock, which is the best DL based systems gets 30-70% depending on the dataset, and traditional gets 50-70%. The paper highlighted some issues with the DL-based methods and given that DeepMind would have had time to incorporate this into their work and develop with the PoseBusters paper in mind, I'd hope it's significantly better than 50-70%. They say 50% better than traditional so I expected something like 70-85% across all datasets. I hope a paper will appear soon to illuminate these and other details. [1] https://pubs.rsc.org/en/content/articlehtml/2024/sc/d3sc04185a https://pubs.rsc.org/en/content/articlehtml/2024/sc/d3sc0418...