Really interesting point about the non-correlation of affinity and PPI probabilities. Disappointing, honestly. Mechanistic systems bio models would really benefit from large scale affinity information, and it would be pretty cool if ML methods trained on binary PPI data learned a kind of latent affinity model. Maybe PPI models could be fine tuned to do that? Or maybe there’s specific neurons in the PPI models that correlate better with affinity, similar to the mechanistic interpretability stuff that people are doing on LLM’s? I only follow this area tangentially so I imagine I’m not the first person to have those ideas…

Anyways I look forward to seeing what you publish!