What it is for

You have a hard protein target — a recessed pocket, or a site spanning two chains — and you want to throw as much search at it as your balance allows. Every candidate is re-folded and scored against your target as it is generated, and the run fans out across as many GPUs as you fund.

Designs binders for the targets the standard tools find hard: a recessed pocket, or a site spanning two chains. Rather than generating candidates and hoping, it searches — it generates, re-folds every candidate and scores how well it grips your target, keeps what scores well and generates again from there. Which model does that scoring follows the target: a protein target is scored by an AlphaFold2 refold, a benchmark ligand or motif task by RoseTTAFold3, with a physics force field added where it applies. The run splits into independent shards across as many GPUs as your balance funds — each shard is a separately seeded search — and the designs are ranked globally across all of them into one pooled table. Proteina-Complexa, Didi et al., ICLR 2026.

When it fits:

You want to aim a binder at one specific patch, including a recessed or partly shielded one, by naming residues on it.
The site you care about spans more than one chain of your target.
You would rather pay for a search that filters as it goes than for raw generation you have to filter afterwards.
You want to scale the search across many GPUs, with your prepaid balance as the only ceiling.

Inputs

You will need:

A target: your own structure (.pdb/.cif) for the protein-binder variant, or a curated benchmark task for any variant.
For your own target, the chain ID — or a chain/residue range such as A1-150, or A12-157,B12-157,C12-157 for a multi-chain target.
Optionally, hotspot residues to aim the binder at a specific epitope.
A funded wallet that covers at least the first wave of shards.

Each run uses a preset that sets the scale and scope:

Protein binder (de novo, vs a protein target): Design de novo binders against a protein target. Search is scored by AlphaFold2 confidence plus a force-field reward. Pick a curated target task or upload your own target PDB.
Ligand binder (de novo, vs a bundled benchmark ligand): Design de novo binders against one of the small-molecule targets bundled with the model. Scored by the RoseTTAFold3 reward (the force field does not support protein-ligand complexes). Your own molecule cannot be used: the task resolves from a separate upstream registry, so this variant is limited to the curated ligand tasks.
Motif scaffolding / enzyme (AME): Scaffold a functional motif or enzyme active site. Scored by the RoseTTAFold3 reward. Limited to the curated AME tasks — their records key on a motif atom spec the hub cannot emit, so your own motif cannot be registered.
Validate (free dry-run): Free pre-flight that checks your target + config load before you commit GPU to a paid search. No wallet charge.

Parameters you set on the form:

Design variant: protein_binder for a protein target (AF2 reward) and the only variant that can take a target of yours, ligand_binder for a bundled benchmark ligand task (RF3 reward), motif_ame for motif scaffolding / enzyme active sites, or validate for a free config check before spending GPU.
Target: Your own structure, or a curated benchmark task whose target is baked in — the two are mutually exclusive. Uploading your own is available on the protein-binder variant; the ligand and motif variants run curated tasks (their tasks resolve from separate upstream registries).
Target region: Which chains and residues to design against, e.g. A1-150, or A12-157,B12-157,C12-157 for a multi-chain target. Blank uses the whole target chain.
Hotspot residues: Optional. Residues the binder should contact, in original PDB numbering — plain numbers use the target chain, or prefix the chain (A113 C73) for a multi-chain region. Every hotspot is checked against your structure before any GPU runs, so a residue that is not there is refused rather than quietly ignored.
Binder length: The range each design's length is drawn from. Defaults to 60-120 residues.
Number of designs: How many designs to search for. This scales the number of independent search shards rather than the width of one: each shard is a fixed 8-design search on its own GPU and returns up to 8, and the hub picks the global top set across every shard.

How to read the results

Ranked designs with reward scores (AF2 pLDDT / ipTM for protein, RF3 score for ligand / motif, force-field energy where applicable), a self-consistency re-fold RMSD, and downloadable structures. The ligand and motif variants score on RF3 only.

Where a tool reports them, the scores mean:

ipTM: Predicted confidence in the contact between two chains, on a 0 to 1 scale. Higher is better: 0.65 to 0.75 depending on the tool. Individual tools set their own pass bar a little either side of that. On a multi-chain target the number may cover the target's own chain–chain interface as well as the binder's, so read the per-tool note on the results table before comparing designs on it.
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.

References

Didi et al., ICLR 2026

Read the paper Source code on GitHub

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