BoltzGen — structure + affinity design
Boltz-2 binder design. Generates mini-protein, nanobody, antibody, or peptide backbones against a target, refolds each candidate, and scores affinity via ipTM and pLDDT.
What it is for
Pick BoltzGen when you want one model that can design mini-proteins, nanobodies, antibodies, or peptides against the same target, or when your target involves glycans, post-translational modifications, or non-canonical residues.
BoltzGen (Wohlwend et al., MIT 2024). Boltz-2 binder design — jointly generates a binder backbone against a target, refolds each candidate end-to-end, and scores affinity via ipTM and pLDDT. Ships four design protocols (mini-protein, nanobody, antibody, peptide) and handles glycans, post-translational modifications, and non-canonical residues natively.
When it fits:
- You want one model that can target the same epitope with mini-proteins, nanobodies, antibodies, or peptides.
- Your target has glycans, PTMs, modified residues, or non-canonical chemistry.
- You want refolding RMSD as a self-consistency signal alongside ipTM and pLDDT.
- You need ~5 to 60 min per run and a budget-tunable number of candidates.
Inputs
You will need:
- Target structure (
.pdb/.cif). - Chain ID of the target.
- At least one hotspot residue.
Each run uses a preset that sets the scale and scope:
- Pilot — your target, ~30 min
- Real BoltzGen run against your uploaded target. Up to 24 final candidates with refolding RMSD + ipTM scores; results emailed when complete (~15-60 min on A100-40GB).
Parameters you set on the form:
- Protocol
- Boltz-2 design protocol.
protein-anythingfor general mini-protein binders,nanobody-anythingfor VHH scaffolds,antibody-anythingfor antibody scaffolds,peptide-anythingfor short cyclic or linear peptides. - Hotspot residues
- Comma-separated target-chain residue indices the binder should contact. Click residues in the 3D viewer to toggle.
- Binder length (min/max)
- Residue-count window for the generated binder. Typical starting ranges: mini-protein 50–100, nanobody 110–130, antibody 110–200, peptide 5–30.
- Budget (designs)
- Number of designs Boltz-2 generates and ranks. Higher budgets cost more and run longer.
Typical runtime:
- pilot
- 15–60 min
How to read the results
Ranked candidate binders with ipTM, pLDDT, refolding RMSD, and downloadable PDBs. Refolding RMSD < 2 Å on the top design typically signals self-consistent binding.
Where a tool reports them, the scores mean:
- ipTM
- Predicted confidence in the binder to target interface. Higher is better. Aim above roughly 0.7 on a tractable target.
- pLDDT
- Per-residue confidence in the predicted fold. Higher means the model is more sure of that part of the structure.
- i_pAE and pAE
- Predicted alignment error, at the interface (i_pAE) or across the whole structure (pAE). Lower is better.
Try these examples
One-click sample inputs that load straight into the run form. Edit any field before submitting.
- SARS-CoV-2 RBD (6m0j chain E)
- Boltz-2 binder design against the spike RBD. Same hotspots as the BindCraft / RFdiffusion examples for easy comparison.
References
Wohlwend et al., MIT (2024)