# Antibodies, checked before synthesis

An antibody engineering platform to design antibodies and nanobodies, model their structures, and review humanness and developability before synthesis.

[Try it free](https://proteiniq.io/app/workflows/templates?template=antibody-candidate-triage)[Book a demo](https://proteiniq.io/contact/sales)

![ProteinIQ workflow preparing one antigen, generating antibody candidates with RFantibody, BoltzGen, and IgGM, and applying shared sequence and structure triage while preserving method-specific scores](https://proteiniq.io/images/solutions/workflows/antibody-candidate-triage-light.webp?dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9)![ProteinIQ workflow preparing one antigen, generating antibody candidates with RFantibody, BoltzGen, and IgGM, and applying shared sequence and structure triage while preserving method-specific scores](https://proteiniq.io/images/solutions/workflows/antibody-candidate-triage-dark.webp?dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9)

1. ## Antigen and epitope preparation

   Repair the antigen structure, identify likely epitope regions, and review protonation before design.

   [![PDBFixer](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fpdb-fixer-featured.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### PDBFixer Fix PDB and mmCIF structures by adding missing atoms, residues, hydrogens, and solvent. structure-analysisquality-validation+3](https://proteiniq.io/app/pdb-fixer)[![ScanNet](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fscannet.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### ScanNet Predict protein binding sites using geometric deep learning on 3D structures. interaction-predictiondeep-learning+3](https://proteiniq.io/app/scannet)[![PROPKA 3](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fpropka-3.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### PROPKA 3 Predict pKa values of ionizable groups in proteins based on 3D structure. protein-analysisproperty-prediction+3](https://proteiniq.io/app/propka)
2. ## Antibody design software

   Design antibody, Fab, and nanobody candidates with RFantibody, BoltzGen, IgGM, and mBER while preserving each method’s native ranking.

   [![BoltzGen](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fboltzgen-featured.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### BoltzGen Design protein, peptide, and nanobody binders against protein or small-molecule targets. binder-designai-powered+5](https://proteiniq.io/app/boltzgen)[![RFantibody](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Frfantibody.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### RFantibody Design antibody and nanobody binders with an end-to-end RosettaCommons pipeline binder-designai-powered+5](https://proteiniq.io/app/rfantibody)[![IgGM](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Figgm.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### IgGM Design antibodies using a generative foundation model. protein-designantibody-design+5](https://proteiniq.io/app/iggm)[![BoltzProt-1](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fboltzprot-1.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### BoltzProt-1 Protein, peptide, nanobody and antibody binder design. protein-designbinder-design+3](https://proteiniq.io/app/boltzprot-1)[![ESMFold2 Binder Design](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fesmfold2-binder-design.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### ESMFold2 Binder Design Design minibinders and antibody scFvs against a protein target. binder-designai-powered+2](https://proteiniq.io/app/esmfold2-binder-design)[![mBER](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmber.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### mBER Design VHH nanobody binders using structure-guided modeling. binder-designai-powered+5](https://proteiniq.io/app/mber)
3. ## Antibody modeling and binding review

   Model candidate structures, check their geometry, and score antibody–antigen interfaces before choosing what to make.

   [![ABodyBuilder3](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fabodybuilder3.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### ABodyBuilder3 Predict paired antibody variable-domain structures from heavy and light chain sequences. protein-foldingstructure-prediction+3](https://proteiniq.io/app/abodybuilder3)[![MolProbity](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmolprobity.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### MolProbity Validate protein structures with clashscore, Ramachandran, rotamer, and geometry checks. structure-analysisquality-validation+4](https://proteiniq.io/app/molprobity)[![DeepRank-Ab](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fdeeprank-ab.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### DeepRank-Ab Score antibody and nanobody complexes with predicted DockQ. protein-analysisai-powered+4](https://proteiniq.io/app/deeprank-ab)
4. ## Antibody sequence analysis and developability

   Number variable regions and review humanness, solubility, viscosity, and developability risk before synthesis.

   [![ANARCII](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fanarci.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### ANARCII Language-model numbering for antibodies, T cell receptors, and VNAR/VHH domains sequence-analysisai-powered+4](https://proteiniq.io/app/anarcii)[![BioPhi](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fbiophi.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### BioPhi Humanize antibody sequences and evaluate humanness scores for therapeutic development. sequence-designai-powered+3](https://proteiniq.io/app/biophi)[![TAP2](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fimmunebuilder.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### TAP2 Contextualize antibody developability risks across hydrophobicity, charge patches, CDR length, and Fv charge symmetry. antibodytherapeutics+2](https://proteiniq.io/app/tap2)[![DeepViscosity](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fdeep-viscosity.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### DeepViscosity Screen paired antibody Fv sequences for high-concentration viscosity risk. protein-analysisdeep-learning+2](https://proteiniq.io/app/deepviscosity)[![NetSolP-1.0](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fnetsolp.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### NetSolP-1.0 Predict protein solubility and purification usability for E. coli expression systems protein-analysisproperty-prediction+3](https://proteiniq.io/app/netsolp-1-0)[![AbLang-2](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fablang-2.webp&w=1920&q=75&dpl=dpl_FAgf5acUWMGh21MEL7khBNAj8AH9) ### AbLang-2 Predict non-germline residues and generate embeddings for paired or unpaired antibody sequences. sequence-analysisai-powered+5](https://proteiniq.io/app/ablang-2)

## Antibody engineering guides

Background on the sequences, structures, and checks behind each step, written for scientists new to a method.

## Ready to engineer antibodies?

### Free

$0

The perfect starting place for your first project.

- All tools
- 200 credits, then 100/mo
- 3 jobs per day
- Up to 1,000 residues per job
- Academic license

[Get Free](https://proteiniq.io/sign-up)

### Plus

$23 per user/month

Everything an academic lab needs to scale.

- Everything in Free
- 24,000 credits/user/year
- No daily job limit
- Batches & workflows
- API access

### Pro

Popular

$79 per user/month

More compute and a commercial license for industry.

- Everything in Plus
- 96,000 credits/user/year
- Commercial license

### Enterprise

Contact us Custom annual terms

Custom credits, seats, and security review.

- Everything in Pro
- Custom credit allocation
- Shared seats and admin controls
- Invoice billing and security review

[Contact sales](https://proteiniq.io/contact)

[View all plans and compare features](https://proteiniq.io/pricing)

## Frequently asked questions

AI answers from our docs. No sign-in needed.