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Tokenizing loops of antibodies.

Ada Fang1,2, Robert G Alberstein2, Simon Kelow2

  • 1Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.

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Summary

We developed ImmunoGlobulin LOOp Tokenizer (Igloo), a multimodal antibody loop tokenizer that improves antibody design. Igloo enhances protein foundation models and efficiently prioritizes functional antibody variants.

Keywords:
Antibodycanonical conformationcomplementarity-determining regionsmachine learningstructuretransformer

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Area of Science:

  • Structural biology
  • Immunoinformatics
  • Protein engineering

Background:

  • Antibody complementarity-determining regions (CDRs) are crucial for antigen binding and novel biologic design.
  • Current CDR characterization methods have limited coverage and integration with protein foundation models.

Purpose of the Study:

  • Introduce ImmunoGlobulin LOOp Tokenizer (Igloo), a multimodal antibody loop tokenizer.
  • Enhance protein foundation models for antibody CDR design and analysis.

Main Methods:

  • Igloo encodes antibody loops using backbone dihedral angles and amino acid sequence.
  • Trained with contrastive learning to map similar loop structures in latent space.
  • Incorporated Igloo tokens into protein language models (IglooLM, IglooALM).

Main Results:

  • Igloo retrieves similar loop structures, outperforming existing methods by 6.1% for H3 loops.
  • IglooLM improves binding affinity prediction accuracy compared to base models.
  • IglooALM generates diverse and structurally consistent antibody loops.
  • Igloo achieved 1.9x enrichment of HER2 binders in a zero-shot setting.

Conclusions:

  • Igloo provides a comprehensive and scalable method for encoding antibody loop diversity.
  • Multimodal tokens enhance protein foundation models for antibody CDR design.
  • Igloo facilitates rapid prioritization of functional antibody variants.