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v0.3.1

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@github-actions github-actions released this 19 Jul 12:03

[0.3.1] - 2026-07-19

Adds SaProt structure-aware protein embeddings (tt-bio saprot, an ESM-2 encoder over a
fused amino-acid + Foldseek-3Di vocabulary) and ProteinMPNN fixed-backbone sequence design
(tt-bio design, inverse folding — the step run after a backbone generator like BoltzGen, or
any bring-your-own-backbone PDB). Both are purely additive: no existing model file changed.

Release gate (scripts/release_gate.py, examples/prot.yaml, 200 steps / 5 samples, seed 0, Blackhole P150a):

model CA-RMSD TM floor result
Boltz-2 1.541 Å 0.939 ≤3.0 Å / ≥0.75 PASS
ESMFold2 1.774 Å 0.915 ≤4.0 Å / ≥0.65 PASS
ESMFold2-fast 1.725 Å 0.909 ≤4.5 Å / ≥0.60 PASS
Protenix-v2 1.417 Å 0.936 ≤6.0 Å / ≥0.50 PASS
OpenDDE 1.367 Å 0.952 ≤6.0 Å / ≥0.50 PASS

BoltzGen designability — n=4, examples/binder.yaml: scRMSD median 0.892 Å, 4/4 designs (100%) ≤2 Å (floor ≤2.0 Å / ≥50%) — PASS.

ESMC embedding parity (fused-RoPE shipped path vs reference esm, 76-residue sequence, PCC floor 0.99):

model per-res PCC pooled logits argmax result
esmc-300m 0.99961 0.99993 0.99990 1.0000 PASS
esmc-600m 0.99964 0.99989 0.99996 1.0000 PASS

SaProt embedding parity (vs reference HF EsmForMaskedLM golden, PCC floor 0.99):

model embedding PCC logits PCC result
saprot-35m 0.999138 0.999772 PASS
saprot-650m 0.999638 0.999927 PASS

ProteinMPNN parity (pytest tests/test_proteinmpnn.py vs official v_48_020.pt): 4/4 passing —
forward log-prob PCC ≥0.999 on 5L33 and 6MRR, exact greedy-recovery match, checkpoint param count
1,660,485 (matches published 1.66M).

UX gate (scripts/ux_regression.py, examples/trpcage.yaml): every shipped surface (Boltz-2,
ESMFold2, ESMFold2-fast, Protenix-v2, OpenDDE, ESMC-600m embed, BoltzGen) cleared live-progress
advancement, strict mmCIF/npz parse, and results/manifest shape — PASS.

Perf gate (scripts/perf_regression.py, Blackhole P150a, trpcage 20 aa single-sequence, warm 2+5, ±15% threshold):

model metric baseline current delta result
boltz2 structures/s 1.190 1.176 -1.2% PASS
esmfold2 structures/s 1.705 1.692 -0.7% PASS
esmfold2-fast structures/s 2.290 2.304 +0.6% PASS
protenix-v2 structures/s 2.383 2.329 -2.3% PASS
opendde structures/s 1.922 1.939 +0.9% PASS
esmc-600m seq/s 20.92 21.03 +0.5% PASS
boltzgen designs/s 0.01723 0.01745 +1.3% PASS

No perf regression. No OOM observed through the gate targets. ProteinMPNN runs on CPU
(data-parallel fanout, not an on-device port — see docs/proteinmpnn-port.md).

Added

  • SaProt structure-aware protein embeddings (tt-bio saprot, saprot-35m/saprot-650m/saprot-1.3b).
  • ProteinMPNN fixed-backbone sequence design (tt-bio design, inverse folding).
  • esmc-300m and esmc-6b legs in the perf-regression gate.