Antibody & Biologics · Ruffolo et al., Johns Hopkins
IgFold
Predicts antibody 3D structures from heavy and light chains in sub-second runtimes.
What IgFold is
IgFold is an antibody structure prediction model developed by Ruffolo et al. at Johns Hopkins. It takes heavy and light chain sequences to produce all-atom coordinate structures in PDB format alongside per-residue confidence metrics.
Antibodies typically share a conserved framework structure. IgFold relies on this conservation to focus its prediction on the variable complementarity-determining region (CDR) loops, generating predictions roughly 1000 times faster than AlphaFold2 in sub-second runtimes. The resulting models provide accuracy suitable for downstream molecular docking and developability workflows.
How it works
The model exploits the structurally conserved framework shared across antibodies, which restricts the prediction task primarily to the variable CDR loops.
Key facts
- Version
- 0.4
- Task
- Structure prediction
- Input modalities
- Heavy chain and light chain protein sequences
- Output modalities
- All-atom PDB structure and per-residue pLDDT vector
- GPU memory
- 8 GB
What you can use it for
- Rapid antibody structure modelling
- Generates all-atom coordinate files in standard PDB format from paired heavy and light chain amino acid sequences in under a second.
- Preparation for molecular docking
- Produces accurate antibody structures that can be fed into downstream computational docking studies.
- Developability screening
- Supplies structural models to assist with the evaluation of antibody developability characteristics.
Run it here
No installation and no GPU of your own: fill in the inputs and it runs on our servers. Results stay in your browser unless you sign in.
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IgFold
Strengths and limits
Good at
- Completes antibody structure prediction in under a second, running approximately 1000 times faster than AlphaFold2.
- Provides per-residue pLDDT confidence scores to indicate local model reliability.
- Outputs complete all-atom coordinates in PDB format suitable for immediate visualization and downstream workflows.
Watch out for
- Specialised for antibodies and dependent on the presence of conserved antibody framework regions.
- Requires paired heavy and light chain sequence inputs rather than single-chain or non-antibody targets.
Inputs and outputs
You provide
Heavy chain
Single-letter amino acid code. Whitespace and FASTA headers are stripped automatically.
Light chainoptional
Single-letter amino acid code. Whitespace and FASTA headers are stripped automatically.
You get back
All-atom coordinates in PDB format, viewable and downloadable.
pLDDT score per residue (0–100). Above 70 is generally reliable.
Licence
Academic and non-commercial use only · JHU Academic License
The JHU Academic License licence does not permit commercial use of this model.
Questions
Can I use IgFold commercially?
Academic and non-commercial use only. The JHU Academic License licence does not permit commercial use of this model.
How do I run IgFold without installing anything?
Use the form under “Run it here” on this page: fill in the inputs and press Run model. It runs on our servers on 1× A100 16GB, typically in 2.0s, and a run costs about 14 credits. Visitors without an account get 1,000 credits a month.
What inputs are required to run IgFold?
IgFold requires two sequence inputs: the antibody heavy chain sequence and the antibody light chain sequence.
What structural outputs does the model generate?
It provides all-atom coordinates in standard PDB format as well as a per-residue pLDDT confidence vector scored from 0 to 100.
How are the pLDDT confidence scores interpreted?
Scores range from 0 to 100, with values above 70 generally considered reliable.
How fast is IgFold compared to general-purpose structure prediction models?
IgFold achieves sub-second prediction times, which is approximately 1000 times faster than AlphaFold2.
Written from IgFold's own documentation. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.