EticaHub Labs computational protein-design dataset — Type 2 Diabetes — run 90fc729e-55ce-4a26-a2c0-19ec844f31ed

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

This individual run contains 4 archived candidates from 1 reported iterations. The pipeline-selected candidate is #1; its internal automated grade is weak.

Proposed research question (not a demonstrated outcome): Design a GLP-1 receptor agonist with a de novo albumin-binding domain fused via a protease-resistant linker to extend half-life while maintaining high receptor affinity

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.
• Automated warn: Low-complexity regions: 12 window(s) of 12 aa below 1.8 bits
• Automated warn: Fold confidence: mean pLDDT 68
• 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: GLP, EAAAK

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.