Run PXDesign online

Pick PXDesign when AF2 confidence against a defined target matters and you want real ipTM / pLDDT / pAE on every candidate. For hallucination-driven binder design without AF2 filtering use BindCraft, for antibody and nanobody CDRs use RFantibody, and for target structure generation without binder design use BoltzGen.

PXDesign — Ranomics in-house binder-design pipeline. An RFdiffusion-style backbone generator paired with JAX AF2 in Initial Guess mode for fast, accurate scoring (Bennett et al., Nature Communications 2023). Every candidate carries real ipTM, pLDDT, and pAE from the AF2-IG stage.

When it fits:

• AF2 confidence against a defined target matters and you want real ipTM / pLDDT / pAE on every candidate.
• You want faster scoring than full AF2 multimer (Initial Guess shortcut).
• You want the same scoring pipeline that drives Ranomics' wet-lab campaigns.

Use the score legend below to read results. Each tool reports a subset of these depending on whether it does design, sequence recovery, or structure prediction.

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.

ProteinMPNN recovery

Fraction of native residues recovered when ProteinMPNN redesigns a known sequence on its native backbone. Higher is better; well calibrated above roughly 0.4 on diverse folds.

30–60 min per run on a dedicated GPU. Billing is by the second of compute, so a faster preset costs less.

We keep a plain-English overview of PXDesign on the main Ranomics site — what the model does under the hood, the kinds of targets it works on, and where it fits inside a full design-to-wet-lab campaign.

If you are picking between PXDesign and a sibling algorithm, these run on the same hub against the same target.

Run RFdiffusion online

Pick RFdiffusion when you want general de novo binder design scored by AF2 multimer (ipTM / pLDDT / i_pAE). For antibody and nanobody scaffolds use RFantibody, for AF2-IG initial-guess scoring use PXDesign, and for hallucination-driven binders without AF2 filtering use BindCraft.

Run BindCraft online

Pick BindCraft when you have a target PDB plus known hotspot residues and want de novo 60-150 aa protein binders.

Run BoltzGen online

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.

Bennett, N. R., Coventry, B., Goreshnik, I., et al. "Improving de novo protein binder design with deep learning." Nature Communications 14, 2625 (2023). Ranomics in-house pipeline; scoring stage uses AF2 Initial Guess.