kasearch 0.0.10

KA-Search: Rapid and exhaustive sequence identity search of known antibodies

---

KA-Search: Rapid and exhaustive sequence identity search of known antibodies

---

by Tobias H. Olsen $^{1,\dagger}$, Brennan A. Kenyon $^{1,\dagger}$, Iain H. Moal $^{2}$ and Charlotte M. Deane $^{1,3}$

$^{1}$ Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
$^{2}$ GSK Medicines Research Centre, GlaxoSmithKline plc, Stevenage, United Kingdom
$^{3}$ Exscientia plc, Oxford, United Kingdom
$^{\dagger}$ These authors contributed equally to this work and share first authorship

Abstract

Antibodies with similar amino acid sequences, especially across their complementary-determining regions, often share properties. Finding that an antibody of interest has a similar sequence to naturally expressed antibodies in healthy or diseased repertoires is a powerful approach for the prediction of antibody properties, such as immunogenicity or antigen specificity. However, as the number of available antibody sequences is now in the billions and continuing to grow, repertoire mining for similar sequences has become increasingly computationally expensive. Existing approaches are limited by either being low-throughput, non-exhaustive, not antibody-specific, or only searching against entire chain sequences. Therefore, there is a need for a specialized tool, optimized for a rapid and exhaustive search of any antibody region against all known antibodies, to better utilize the full breadth of available repertoire sequences.

We introduce Known Antibody Search (KA-Search), a tool that allows for rapid search of billions of antibody sequences by sequence identity across either the whole chain, the CDRs, or a user defined antibody region. We show KA-Search in operation on the ~2.4 billion antibody sequences available in the OAS database. KA-Search can be used to find the most similar sequences from OAS within 30 minutes using 5 CPUs. We give examples of how KA-Search can be used to obtain new insights about an antibody of interest. KA-Search is freely available at https://github.com/oxpig/kasearch.

---

Software implementation

KA-Search is freely available and can be installed with pip.

    pip install kasearch

or directly from github.

    pip install -U git+https://github.com/oxpig/kasearch

NB: You need to manually install a version of ANARCI in the same environment.

---

Download pre-aligned data to search against

This list contains the download links for the paper version of the pre-aligned OAS and any future releases, ready for KA-Search.

NB: The following datasets are large, you should therefore ensure you have enough space before trying to download them.

• (September 2022)(~63GB)(Paper version): pre-aligned version of OAS with 2.4 billion sequences

After downloading, extract the pre-aligned dataset with "tar -xf downloaded_file.tar". Give the extacted dataset path when initiating KA-Search to search against it. See how to do this by following the KA-Search notebook guide below.

---

KA-Search guide

A Jupyter notebook showcasing KA-Search can be found here.

---

Citation

@article{Olsen2022,
  title={KA-Search: Rapid and exhaustive sequence identity search of known antibodies},
  author={Tobias H. Olsen, Brennan A. Kenyon, Iain H. Moal and Charlotte M. Deane},
  journal={bioRxiv},
  doi={},
  year={2022}
}