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

• Published in: Cellular and molecular life sciences : CMLS 2014-12, Vol.71 (24), p.4869-4880
• Main Authors: Salvat, Regina S, Parker, Andrew S, Guilliams, Andrew, Choi, Yoonjoo, Bailey-Kellogg, Chris, Griswold, Karl E
• Format: Article
• Language: English
• Subjects: Algorithms; beta-lactamase; beta-Lactamases - genetics; beta-Lactamases - immunology; beta-Lactamases - therapeutic use; Biochemistry; Biomedical and Life Sciences; Biomedicine; catalytic activity; Cell Biology; Computational Biology - methods; Drug Stability; Drug therapy; Drug Therapy - methods; drugs; Epitope Mapping; epitopes; Epitopes, T-Lymphocyte - genetics; Epitopes, T-Lymphocyte - immunology; Humans; immune response; Immune system; Immunogenicity; immunologic memory; Life Sciences; major histocompatibility complex; monitoring; Mutation; patients; prediction; Prodrugs - therapeutic use; Protein Engineering - methods; Proteins; Research Article; Sequence Deletion; T cell receptors; T-lymphocytes; Temperature
• ISSN: 1420-682X; 1420-9071
• DOI: 10.1007/s00018-014-1652-x

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.