Antibodies, checked before synthesis

ProteinIQ connects those complementary analyses without separating the evidence from the candidate. Researchers can annotate heavy and light chains, assess humanness and sequence liabilities, generate or inspect structures, and compare docking or design outputs alongside the original inputs. Begin with an antigen, antibody sequence, framework, or candidate set and choose a focused tool or workflow. Each run preserves the resulting tables, residue annotations, structures, confidence values, logs, and downloadable files for a traceable synthesis shortlist.

The computational stages that come before synthesis: prepare the antigen, generate or collect antibody and nanobody candidates, model their structures, then number the sequences and review humanness and developability. The workflow ends with a ranked shortlist and its provenance. ProteinIQ does not cover expression, purification, or assay work, which happen in the lab afterwards.

ProteinIQ hosts RFantibody, BoltzGen, IgGM, and mBER for generating antibodies, Fabs, and nanobodies against an antigen structure, plus AntiFold, DiffAb, and IgDesign for redesigning an existing antibody. No single method suits every project, so the starting point decides: a target alone, a framework, or an existing complex. Running several generators from the same antigen and applying the same checks to each makes their outputs comparable.

Yes. ABodyBuilder3 and ImmuneBuilder run in the browser from heavy and light chain sequences, and ImmuneBuilder also models nanobodies. Each returns a PDB structure with confidence values, and no local installation or GPU is needed.

ProteinIQ supports antibody engineering workflows for numbering, germline context, humanness review, humanization triage, developability screening, antibody structure prediction, nanobody modeling, antibody-antigen docking, and design review. Each workflow keeps upstream scores, files, and tool conventions visible for scientific inspection.

ProteinIQ antibody tools can accept FASTA sequences, paired heavy and light chains, single-domain or nanobody sequences, PDB structures, and antigen structures depending on the upstream model. The platform keeps each accepted input format tied to the tool that produced the downstream annotation, model, or score.

Yes. ProteinIQ can run antibody humanization and humanness review workflows using tools such as BioPhi, AbLang-style language model review, and humanization comparison steps. The answers are presented as sequence-level evidence for review, not as a hidden replacement for expert antibody engineering judgment.

Yes. ProteinIQ includes antibody and nanobody structure workflows that can turn variable-region sequences into modeled structures when the selected upstream tool supports that input. The generated PDB or related structure files, confidence values, and logs remain available for inspection and export.

Yes. ProteinIQ supports antibody-antigen docking and exploratory complex modeling workflows that can combine antibody chains or modeled antibody structures with an antigen structure. Docking outputs are useful for hypothesis generation and triage, while binding, specificity, and epitope claims still need experimental evidence.

ProteinIQ keeps antibody numbering, germline calls, humanness scores, developability tables, modeled structures, docking files, and logs associated with the input sequence or structure that produced them. This helps reviewers avoid separating heavy chains, light chains, residue annotations, and downstream models during triage.

Yes. ProteinIQ workflows are useful when you want connected antibody annotation, humanization, structure, and docking steps, but individual tools such as ANARCI, BioPhi, ImmuneBuilder, RFantibody, ParaSurf, and LightDock can also be opened directly for focused analysis.

ProteinIQ antibody workflows can export numbered sequence tables, humanness and developability CSV files, predicted structures, designed sequences, docking models, logs, and upstream result files depending on the tool. Exported outputs preserve the upstream labels and formats needed for review outside the platform.

No. ProteinIQ organizes computational antibody engineering evidence for prioritization and review. Expression, binding, specificity, immunogenicity, developability, and manufacturability experiments are still required before making biological, therapeutic, or clinical claims.