Proteina-Complexa
De novo binder design against protein or small-molecule targets, run as an inference-time search filtered by an AF2 / RF3 / force-field reward stack. Fans out as a fund-and-drain campaign of independent search shards; the wallet balance is the only ceiling.
What it is for
Pick Proteina-Complexa when you want de novo binders against a protein OR a small-molecule (ligand) target, scored by a full AF2 / RF3 / force-field reward stack, and you want to scale the search across many GPUs with the wallet as the only ceiling.
Proteina-Complexa (Geffner et al., NVIDIA 2025). A flow-matching generator wrapped in an inference-time search that filters designs through an AlphaFold2 / RoseTTAFold3 / force-field reward stack. It designs de novo binders against protein targets, small-molecule (ligand) targets, and enzyme / motif active sites. Runs here as a fund-and-drain campaign of independent seeded search shards, with global cross-shard top-K and post-hoc diversity clustering.
When it fits:
- You want de novo binders against a small-molecule target, not just a protein.
- You want an inference-time search filtered by an AF2 / RF3 / force-field reward, not raw generation.
- You want to scale the search across many GPUs with the prepaid wallet as the only ceiling.
- You want diverse high-reward designs (global top-K + diversity clustering) rather than near-duplicates.
Inputs
You will need:
- A target: a curated benchmark task, or your own target (
.pdbfor protein / motif,.sdffor ligand). - For a protein target, the chain ID.
- 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 small molecule)
- Design de novo binders against a small-molecule target supplied as an SDF. Scored by the RoseTTAFold3 reward (the force field does not support protein-ligand complexes). Pick a curated ligand task or upload your own SDF.
- Motif scaffolding / enzyme (AME)
- Scaffold a functional motif or enzyme active site. Scored by the RoseTTAFold3 reward. Pick a curated AME task or upload your own motif.
- Validate (free dry-run)
- Free CPU-only 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_binderfor a protein target (AF2 reward),ligand_binderfor a small-molecule SDF target (RF3 reward),motif_amefor motif scaffolding / enzyme active sites, orvalidatefor a free config check before spending GPU.- Target task
- A curated benchmark task (target baked in) or your own uploaded target. Protein and motif targets are PDB; ligand targets are SDF.
- Number of designs
- How many designs to search for. This scales the number of independent search shards; each shard runs on its own GPU and returns its survivors, and the hub picks the global top set.
Typical runtime:
- protein_binder
- 30 to 120 min / shard
- ligand_binder
- 30 to 120 min / shard
- motif_ame
- 30 to 120 min / shard
- validate
- 1 to 3 min (free)
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 structural diversity cluster id, 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 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.
References
Geffner et al., NVIDIA (2025)