EticaHub Labs computational protein-design dataset — Cancer Immunotherapy — run de0c13de-fe6a-464b-b329-4cddf45768d9

Computational dataset / research audit record, not a validated treatment.

This individual run contains 5 archived candidates from 1 reported iterations. The pipeline-selected candidate is #2; its internal automated grade is weak.

Proposed research question (not a demonstrated outcome): Engineer rigid α-helical staples into the flexible hinge region of the MOTS-c/anti-PD-L1 bispecific to lock protease-cleavable conformation while preserving mitochondrial targeting and PD-L1 blockade avidity in humanized tumor models

Evidence and limitations

• Computational predictions only. No experimental or clinical evidence is supplied. Scores, automated checks and resolved identifiers do not establish binding, novelty, efficacy, safety or medical benefit.
• The stored "verified" grade is an internal automated check, not peer review or independent scientific validation.
• Hypothesis, approach and success criteria below are proposed research, not experiments performed.
• Checkpoint versions, random seeds and complete tool inputs are not established by this archive export; exact rerun reproducibility is not claimed.
• Selected candidate #2 has 0 cysteines. Its recorded sequence cannot form an intramolecular cysteine disulfide bridge; the proposed disulfide-stapling objective is not demonstrated. The sequence alone also does not establish a non-canonical crosslink.
• Automated warn: Sequence complexity: 2.38 bits — low diversity
• Automated warn: Composition bias: 43% single-residue share
• Automated warn: Low-complexity regions: 6 window(s) of 12 aa below 1.8 bits
• Internal publication gate: verification grade is weak
• Internal publication gate: no PubMed citation resolved
• Internal publication gate: no named target resolved in UniProt
• Internal publication gate: unresolved target symbols: MOTS, EAAAKL, GPLG, CGVCG

Files: evidence report, original JSON, all candidate sequences, provenance manifest, license and SHA-256 checksums. Available predicted coordinate exports are included and explicitly labelled; missing structures are not reconstructed.

AI-assisted research generated by the EticaHub Labs autopilot. Deaven Mabry is credited as responsible project creator, with EticaHub Labs affiliation. Cited literature remains the work of its original authors; identifier resolution is not claim support.