Skip to main content

Lightweight antibody structure prediction tool (arXiv:2507.09054)

Project description

DOI

Ibex 🐐

Ibex is a lightweight antibody and TCR structure prediction model.

Installation

Ibex can be installed through pip with

pip install prescient-ibex

Alternatively, you can use uv and create a new virtual environment

uv venv --python 3.10
source .venv/bin/activate
uv pip install -e .

Usage

The simplest way to run inference is through the ibex command, e.g.

ibex --fv-heavy EVQLVESGGGLVQPGGSLRLSCAASGFNIKDTYIHWVRQAPGKGLEWVARIYPTNGYTRYADSVKGRFTISADTSKNTAYLQMNSLRAEDTAVYYCSRWGGDGFYAMDYWGQGTLVTVSS --fv-light DIQMTQSPSSLSASVGDRVTITCRASQDVNTAVAWYQQKPGKAPKLLIYSASFLYSGVPSRFSGSRSGTDFTLTISSLQPEDFATYYCQQHYTTPPTFGQGTKVEIK --output prediction.pdb

You can provide a csv (with the --csv argument) or a parquet file (with the --parquet argument) and run a batched inference writing the output into a specified directory with

ibex --csv sequences.csv --output predictions

where sequences.csv should contain a fv_heavy and fv_light column with heavy and light chain sequences, and optionally an id column with a string that will be used as part of the output PDB filenames.

By default, structures are predicted in the holo conformation. To predict the apo state, use the --apo flag.

To run a refinement step on the predicted structures, use the --refine option. Additional checks to fix cis-isomers and D-stereoisomers during refinement can be activated with --refine-checks.

Instead of running Ibex, you can use --abodybuilder3 to run inference with the ABodyBuilder3 model. Below is a summary of all available options:

--abodybuilder3    Use the AbodyBuilder3 model instead of Ibex for inference. [default: no-abodybuilder3]                                           
--fv-heavy         Sequence of the heavy chain.                                                                                                     
--fv-light         Sequence of the light chain.                                                                                                     
--csv              CSV file containing sequences of heavy and light chains. Columns should be named 'fv_heavy' and 'fv_light'. Output file names can
                   be provided in a 'id' column.                                                                                                    
--parquet          Parquet file containing sequences of heavy and light chains. Columns should be named 'fv_heavy' and 'fv_light'. Output file names
                   can be provided in a 'id' column.                                                                                                
--output           Output file for the PDB structure, or path to the output folder when a parquet or csv file is provided. [default: prediction.pdb]
--batch-size       Batch size for inference if a parquet or csv file is provided. [default: 32]                                                     
--save-all         Save all structures of the ensemble as output files. [default: no-save-all]                                                      
--refine           Refine the output structures with openMM. [default: no-refine]                                                                   
--refine-checks    Additional checks to fix cis-isomers and D-stereoisomers during refinement. [default: no-refine-checks]                          
--apo              Predict structures in the apo conformation. [default: no-apo]                                                                    

To run Ibex programmatically, you can use

from ibex import Ibex, checkpoint_path, inference
ckpt = checkpoint_path("ibex")
ibex_model = Ibex.load_from_ensemble_checkpoint(ckpt)
inference(ibex_model, fv_heavy, fv_light, "prediction.pdb")

to predict structures for multiple sequence pairs, batch_inference is recommended instead of inference.

Predictions on nanobodies and TCRs

To predict nanobody structures, leave out the fv_light argument, or set it as "" or None in the csv column.

For inference on TCRs, you should provide the variable beta chain sequence as fv_heavy and the alpha chain as fv_light. Ibex has not been trained on gamma and delta chains.

License

The Ibex codebase is available under an Apache 2.0 license, and the ABodyBuilder3 model weights under a Creative Commons Attribution 4.0 International license, both of which allow for commercial use.

The Ibex model weights are available under a Genentech Apache 2.0 Non-Commercial license, which allows its use for non-commercial academic research purposes.

Ibex uses as input representation embeddings from ESMC 300M, which is licensed under the EvolutionaryScale Cambrian Open License Agreement.

Citation

When using Ibex in your work, please cite the following paper

@misc{ibex,
      title={Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins},
      author={Frédéric A. Dreyer and Jan Ludwiczak and Karolis Martinkus and Brennan Abanades and Robert G. Alberstein and Pan Kessel and Pranav Rao and Jae Hyeon Lee and Richard Bonneau and Andrew M. Watkins and Franziska Seeger},
      year={2025},
      eprint={2507.09054},
      archivePrefix={arXiv},
      primaryClass={q-bio.BM},
      url={https://arxiv.org/abs/2507.09054},
}

If you use the ABodyBuilder3 model weights, you should also cite

@article{abodybuilder3,
    author = {Kenlay, Henry and Dreyer, Frédéric A and Cutting, Daniel and Nissley, Daniel and Deane, Charlotte M},
    title = "{ABodyBuilder3: improved and scalable antibody structure predictions}",
    journal = {Bioinformatics},
    volume = {40},
    number = {10},
    pages = {btae576},
    year = {2024},
    month = {10},
    issn = {1367-4811},
    doi = {10.1093/bioinformatics/btae576}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

prescient_ibex-0.2.0.tar.gz (424.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

prescient_ibex-0.2.0-py3-none-any.whl (87.7 kB view details)

Uploaded Python 3

File details

Details for the file prescient_ibex-0.2.0.tar.gz.

File metadata

  • Download URL: prescient_ibex-0.2.0.tar.gz
  • Upload date:
  • Size: 424.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.14

File hashes

Hashes for prescient_ibex-0.2.0.tar.gz
Algorithm Hash digest
SHA256 6e07acb10e2763002766ec5a91181b7e2ee6f90548665081e2f4178e55154991
MD5 3a4e43a37d318ef58beb4daa44ea94ec
BLAKE2b-256 164f67920573137ee292e0b2b80254dcad2dd3a230a824391212f558ab2c9ae0

See more details on using hashes here.

File details

Details for the file prescient_ibex-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: prescient_ibex-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 87.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.14

File hashes

Hashes for prescient_ibex-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b6d2bfb70249405ae50d8fe56ebb4771ec4fd123bd5d6aaa0d6741994e0cc6cc
MD5 b385c2d4693cd5eddba131b43e316c90
BLAKE2b-256 c51c93e8da956b57863684da3e155ceed2d1d887dde4b84d92da580406825c45

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page