All tools
The Ranomics protein-design tool catalog.
Run feasibility scoring, generative binder design, structure prediction, and library planning from a single USD wallet. Every pipeline lands ranked candidates with downloadable PDBs and hands off cleanly into Ranomics' yeast display CRO when a design is worth validating.
Pick Epitope Scout first to identify candidate epitopes and per-dimension feasibility for any target.
Sign in to runPick the Library Planner when you have a binder design shortlist and need to scope library size, diversification scheme, and screening throughput before ordering DNA.
Sign in to runPick BindCraft when you have a target PDB plus known hotspot residues and want de novo 60 to 150 aa protein binders.
Sign in to runPick PXDesign when AF2 confidence against a defined target matters and you want real ipTM, pLDDT, and 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.
Sign in to runPick 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.
Sign in to runPick AF2 when you need the gold-standard structure prediction with calibrated pLDDT and PAE. For faster single-sequence folds use ESMFold (D4); for affinity-aware folds use Boltz-2 (D6).
Sign in to runPick Boltz-2 to validate a designed binder against your antigen. Single-sequence cofold with interface confidence (ipTM), antibody-trained and orthogonal to AF2-multimer. For sequence design, use ProteinMPNN; for de novo backbones, use RFantibody, BindCraft, or BoltzGen first.
Sign in to runPick ColabFold when you need a fast no-MSA fold. 1 to 2 min per run, no MMseqs2 round-trip. Pair with AF2 standalone (D2) when you want full MSA and templates, or with ESMFold (D4) for single-sequence monomers on an even smaller GPU.
Sign in to runPick ESMFold when you need the fastest possible monomer fold. No MSA, no multimer, single-sequence ESM-2 language-model prediction. Pair with ColabFold (D3) for multimers or AF2 standalone (D2) for full MSA-backed accuracy.
Sign in to run| Tool | Best for | Typical runtime | Paper / Repo |
|---|---|---|---|
| AlphaFold2 af2 | Pick AF2 when you need the gold-standard structure prediction with calibrated pLDDT and PAE. For faster single-sequence folds use ESMFold (D4); for affinity-aware folds use Boltz-2 (D6). |
runtime: 5 to 10 min
|
Jumper et al., Nature 2021 (AF2); Mirdita et al., Nature Methods 2022 (ColabFold) Source repo |
| BindCraft bindcraft | Pick BindCraft when you have a target PDB plus known hotspot residues and want de novo 60 to 150 aa protein binders. |
runtime: 45 min
|
Pacesa et al., bioRxiv 2024 Source repo |
| Boltz-2 boltz2 | Pick Boltz-2 to validate a designed binder against your antigen. Single-sequence cofold with interface confidence (ipTM), antibody-trained and orthogonal to AF2-multimer. For sequence design, use ProteinMPNN; for de novo backbones, use RFantibody, BindCraft, or BoltzGen first. |
runtime: <1 min to ~3 min
|
Wohlwend et al., bioRxiv 2025 Source repo |
| BoltzGen boltzgen | 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. |
runtime: 15 to 60 min
|
Wohlwend et al., MIT (2024) Source repo |
| ColabFold colabfold | Pick ColabFold when you need a fast no-MSA fold. 1 to 2 min per run, no MMseqs2 round-trip. Pair with AF2 standalone (D2) when you want full MSA and templates, or with ESMFold (D4) for single-sequence monomers on an even smaller GPU. |
runtime: 1 to 2 min
|
Mirdita et al., Nature Methods 2022 Source repo |
| ESMFold esmfold | Pick ESMFold when you need the fastest possible monomer fold. No MSA, no multimer, single-sequence ESM-2 language-model prediction. Pair with ColabFold (D3) for multimers or AF2 standalone (D2) for full MSA-backed accuracy. |
runtime: 0.5 to 1 min
|
Lin et al., Science 2023 Source repo |
| ProteinMPNN mpnn | Pick ProteinMPNN when you already have a backbone and need candidate sequences. For de novo backbone generation, use RFantibody, BindCraft, or BoltzGen first and feed the output PDB here. |
runtime: 1 min
|
Dauparas et al., Science 2022 Source repo |
| PXDesign pxdesign | Pick PXDesign when AF2 confidence against a defined target matters and you want real ipTM, pLDDT, and 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. |
runtime: 30 to 60 min
|
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. |
| RFantibody rfantibody | Pick RFantibody when you need a VHH (nanobody) scaffold against a target PDB. For de novo non-antibody binders, use BindCraft. For designs involving modified residues or glycans, use BoltzGen. |
runtime: 15 to 60 min
|
Bennett et al., bioRxiv 2024 Source repo |
| RFdiffusion rfdiffusion | 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. |
runtime: 15 to 30 min
|
Watson, J. L., Juergens, D., Bennett, N. R., et al. "De novo design of protein structure and function with RFdiffusion." Nature 620, 1089 to 1100 (2023). Composite pipeline: RFdiffusion backbones, ProteinMPNN sequences, and AF2 multimer validation. Source repo |