You can bin all astounding ml results into one of two categories, convolutional forms or sequential forms. The problem space does not fit into either of those so cleanly.

Yes, you can turn a molecule into a graph, and there are graph ml techniques, but how that interacts with a protein also does not have a lot of source data (real or synthetic) nor is the interaction space obviously reducible into a differentiable form. Either would be sufficient for today's breed of ML to excel at this.