SATYA verifies predicted protein structures for structural coherence using cellular sheaf cohomology. Deterministic. No GPU. No training data. Run any structure below and get a signed receipt.
SATYA Protein is the structural biology application of the Invariant verification stack.
Generated is not verified. Same engine. Different evidence. Same receipt.
Same engine. Same sheaf. Same receipts. From a 10-residue peptide to the largest human protein. Each entry in the ladder adds a structural challenge the previous entries did not have.
| # | Protein | PDB | Residues | Time | RMSD | Verdict |
|---|---|---|---|---|---|---|
| 1 | Chignolin | 1UAO | 10 | 0.0 s | 0.09 A | SAFE |
| 2 | Insulin | 4INS | 51 | 0.2 s | 0.03 A | SAFE |
| 3 | BPTI | 5PTI | 58 | 0.2 s | 0.04 A | SAFE |
| 4 | Aβ42 fibril | 5OQV | 126 | 0.9 s | 0.02 A | SAFE |
| 5 | Spike RBD | 6M0J | 194 | 1.7 s | 0.03 A | SAFE |
| 6 | TIM barrel | 1YPI | 247 | 2.4 s | 0.04 A | SAFE |
| 7 | Titin (300 Ig) | 1WAA x300 | 26,700 | 22.0 s | per-domain | SAFE |
Not a confidence score. A reproducible obstruction map. Every run produces a signed, replayable receipt. Every obstruction signature can become an atlas entry.
This is not a mockup. Each click calls the SATYA verification engine, runs sheaf-cohomology verification, and returns a signed receipt. Sixteen cases range from native structures to catastrophic failures. Try the Corrupted Decoy first.
For each protein in the ladder, we ran the same four-step protocol. The structures are real PDB entries. The decoys are synthetic corruptions designed to test specific failure modes. The refinement is deterministic. Every step produces a signed receipt.
Extract residue-level geometry from the PDB file. Multi-chain, disulfide bonds, backbone dihedrals, SG atom positions. No external dependencies beyond NumPy.
Generate a structurally corrupted decoy. Displace residues, break disulfide bonds, unspring barrels, shear interchain contacts. Each decoy targets the specific structural property that protein tests.
Build a cellular sheaf from the constraint graph. Compute the constant-sheaf connectivity diagnostic (Laplacian kernel), the spectral gap (lambda_2), and Dirichlet energy. Localize obstructions to specific residue regions. Emit verdict: SAFE, REVIEW_REQUIRED, or UNSAFE.
Minimize structural inconsistency over the sheaf constraint graph using analytical gradients. Spatial cell list for O(n) steric detection. Checkpoint verification with SATYA receipts. Track whether refinement improves structural coherence and reduces localized obstruction.
SIGMA maps a protein structure into a cellular sheaf over its residue-level constraint graph. Residues carry local geometric state. Constraints such as backbone bonds, native contacts, disulfide bonds, and steric exclusions define compatibility conditions between neighboring regions.
The sheaf Laplacian's spectrum reveals global structural coherence. The kernel dimension encodes topological invariants. The spectral gap (lambda_2) measures how well-connected the constraint network is. The Dirichlet energy of the deviation section measures total structural inconsistency. Local constraint violations that no local adjustment can reconcile raise the coboundary and concentrate that energy on the affected residue regions.
For a native structure verified against itself: deviation = 0, coboundary = 0, Dirichlet energy = 0, coherence = 1.0. For a corrupted decoy: nonzero deviation, inflated coboundary, and Dirichlet energy that localizes the damage to specific residue regions. The result is deterministic, auditable, and reproducible.
SATYA adds an independent deterministic verification layer to protein-structure pipelines. Small local checks can run in microseconds; full protein receipts complete in seconds on CPU.
You just ran it. The demo above is the real engine, not a mockup. Download SATYA and the same verification runs on any PDB or mmCIF structure on your own machine. Nothing leaves your network.