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. 2014 Dec;71(24):4869-80.
doi: 10.1007/s00018-014-1652-x. Epub 2014 Jun 1.

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

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

Regina S Salvat et al. Cell Mol Life Sci. 2014 Dec.

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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Conflict of interest statement

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.

Figures

Fig. 1
Fig. 1
Epitope Map of P99βL. The total number of predicted epitopes (y-axis) that start at a given amino acid is mapped onto the primary sequence of P99βL (x-axis). Using a Propred threshold of 5 %, epitopes were predicted for MHC II alleles DRB1*0101, 0301, 0401, 0701, 0801, 1101, 1301, and 1501 (i.e., max score for any position is 8). Sites of IP2 mutations are indicated with arrows and residue numbers. Inset: Predicted epitopes mapped onto the P99βL peptide backbone (PDB 1XX2 chain A). The density of predicted epitopes is indicated by size and color gradients. Thick tubes indicate a high density of overlapping epitopes, while thin white tubes indicate no epitopes in that protein segment. Residues targeted with mutations are rendered as pink ball and sticks. Rendered with PyMOL [43]
Fig. 2
Fig. 2
Allele-specific epitope predictions for P99βL peptides. Names of synthetic peptides are shown above each plot, the corresponding amino acid sequences are indicated on the x-axis, and the relevant human MHC II alleles are shown on the y-axis. For the wild-type P99βL sequences, predicted epitopes for each allele are indicated as solid black lines spanning the 9mer peptide. Epitopes that remain after the specified mutation are shown as overlaid hatched lines
Fig. 3
Fig. 3
Peptide binding affinities for human MHC II proteins. IC50 values are plotted as cognate wild-type and variant pairs, where lower IC50 values correspond to higher affinity binding with human MHC II. The slope of the connecting lines is a relative measure of deimmunizing efficacy, where larger positive slopes indicate a greater fold decrease in affinity relative to wild type. Lines with negative slopes indicate a mutation that enhanced MHC II binding. Shading indicates binding strength by category (strong = dark gray; moderate = medium gray; weak = light gray; non-binding = white)
Fig. 4
Fig. 4
Aggregated immunoreactivity scores for full-length protein designs. The binding strength of individual peptides for MHC II alleles DRB1*0101, 0401, 0701, and 1501 were binned as strong (IC50 < 1 μM), moderate (1 μM ≤ IC50 < 10 μM), weak (10 μM ≤ IC50 < 100 μM), or non-binding (IC50 ≥ 100 μM, not shown). The counts for each enzyme’s constituent peptides were summed and plotted by semiquantitative category (y-axis). The horizontal hatched lines are visual guides for the strong and moderate counts of wild-type P99βL. Asterisk indicates values from a previously published study [31]. Annotation of binding category for individual peptides is provided in Supplemental Table 1
Fig. 5
Fig. 5
Relative activity and stability of various deimmunized P99βL variants. Relative scores were calculated by dividing a given variant’s parameter by the corresponding wild-type value from the cited study. Hatched horizontal line indicates wild-type values. IP2 variants are shown in blue, DP2 variants in green, and the conventionally deimmunized variant in red. Error bars indicate SEM. The horizontal hatched line is a visual guide to the normalized wild-type value of each parameter. Asterisk indicates values from a previously published study [31]

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