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Computationally driven deletion of broadly distributed T cell epitopes in a biotherapeutic candidate

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Abstract

Biotherapeutics are subject to immune surveillance within the body, and anti-biotherapeutic immune responses can compromise drug efficacy and patient safety. Initial development of targeted antidrug immune memory is coordinated by T cell recognition of immunogenic subsequences, termed “T cell epitopes.” Biotherapeutics may therefore be deimmunized by mutating key residues within cognate epitopes, but there exist complex trade-offs between immunogenicity, mutational load, and protein structure–function. Here, a protein deimmunization algorithm has been applied to P99 beta-lactamase, a component of antibody-directed enzyme prodrug therapies. The algorithm, integer programming for immunogenic proteins, seamlessly integrates computational prediction of T cell epitopes with both 1- and 2-body sequence potentials that assess protein tolerance to epitope-deleting mutations. Compared to previously deimmunized P99 variants, which bore only one or two mutations, the enzymes designed here contain 4–5 widely distributed substitutions. As a result, they exhibit broad reductions in major histocompatibility complex recognition. Despite their high mutational loads and markedly reduced immunoreactivity, all eight engineered variants possessed wild-type or better catalytic activity. Thus, the protein design algorithm is able to disrupt broadly distributed epitopes while maintaining protein function. As a result, this computational tool may prove useful in expanding the repertoire of next-generation biotherapeutics.

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Abbreviations

APCs:

Antigen-presenting cells

MHC II:

Class II major histocompatibility complex proteins

DP2 :

Dynamic programming for deimmunizing proteins

P99βL:

Enterobacter chloacae P99 beta-lactamase

IP2 :

Integer programming for immunogenic proteins

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Acknowledgments

This work was supported by NIH grant R01-GM-098977 to CBK and KEG. RSS was supported in part by a Luce Foundation Fellowship and in part by a Thayer Innovation Program Fellowship from the Thayer School of Engineering. The authors would like to thank Thomas Scanlon, Warren Kett, and Deeptak Verma for their insights and support.

Conflict of interest

Karl E. Griswold and Chris Bailey-Kellogg are Dartmouth faculty and co-members of Stealth Biologics, LLC, a Delaware biotechnology company. They acknowledge that there is a potential conflict of interest related to their association with this company, and they hereby affirm that the data presented in this paper is free of any bias. This work has been reviewed and approved as specified in these faculty members’ Dartmouth conflict of interest management plans. The remaining authors declare no conflict of interest.

Author information

Author notes

  1. Andrew S. Parker

    Present address: Zettics, 150 Baker Ave. Ext., Ste. 201, Concord, MA, USA

  2. Andrew Guilliams

    Present address: Mascoma Corp., 67 Old Etna Road #300, Lebanon, NH, USA

Authors and Affiliations

  1. Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH, 03755, USA

    Regina S. Salvat, Andrew Guilliams & Karl E. Griswold

  2. Department of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH, 03755, USA

    Andrew S. Parker, Yoonjoo Choi & Chris Bailey-Kellogg

  3. Program in Molecular and Cellular Biology, Dartmouth College, Hanover, NH, USA

    Karl E. Griswold

Authors
  1. Regina S. Salvat
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  2. Andrew S. Parker
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  4. Yoonjoo Choi
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  6. Karl E. Griswold
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Corresponding authors

Correspondence to Chris Bailey-Kellogg or Karl E. Griswold.

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Salvat, R.S., Parker, A.S., Guilliams, A. et al. Computationally driven deletion of broadly distributed T cell epitopes in a biotherapeutic candidate. Cell. Mol. Life Sci. 71, 4869–4880 (2014). https://doi.org/10.1007/s00018-014-1652-x

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  • DOI: https://doi.org/10.1007/s00018-014-1652-x

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