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. 2015 Jul;112(7):1306-18.
doi: 10.1002/bit.25554. Epub 2015 Feb 23.

Protein deimmunization via structure-based design enables efficient epitope deletion at high mutational loads

Regina S Salvat  1 , Yoonjoo Choi  2 , Alexandra Bishop  3 , Chris Bailey-Kellogg  4 , Karl E Griswold  5   6
Affiliations

Protein deimmunization via structure-based design enables efficient epitope deletion at high mutational loads

Regina S Salvat et al. Biotechnol Bioeng. 2015 Jul.

Abstract

Anti-drug immune responses are a unique risk factor for biotherapeutics, and undesired immunogenicity can alter pharmacokinetics, compromise drug efficacy, and in some cases even threaten patient safety. To fully capitalize on the promise of biotherapeutics, more efficient and generally applicable protein deimmunization tools are needed. Mutagenic deletion of a protein's T cell epitopes is one powerful strategy to engineer immunotolerance, but deimmunizing mutations must maintain protein structure and function. Here, EpiSweep, a structure-based protein design and deimmunization algorithm, has been used to produce a panel of seven beta-lactamase drug candidates having 27-47% reductions in predicted epitope content. Despite bearing eight mutations each, all seven engineered enzymes maintained good stability and activity. At the same time, the variants exhibited dramatically reduced interaction with human class II major histocompatibility complex proteins, key regulators of anti-drug immune responses. When compared to 8-mutation designs generated with a sequence-based deimmunization algorithm, the structure-based designs retained greater thermostability and possessed fewer high affinity epitopes, the dominant drivers of anti-biotherapeutic immune responses. These experimental results validate the first structure-based deimmunization algorithm capable of mapping optimal biotherapeutic design space. By designing optimal mutations that reduce immunogenic potential while imparting favorable intramolecular interactions, broadly distributed epitopes may be simultaneously targeted using high mutational loads.

Keywords: T cell epitope deletion; biotherapeutics; computational protein design; deimmunization; immunogenicity.

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Conflict of interest statement

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.

Figures

Figure 1
Figure 1
Epitope map of P99βL. The P99βL sequence was analyzed using ProPred set to a 5% threshold for the alleles DRB1*0101, 0401, 0701, and 1501. The epitope score, or number of alleles that bind each nonamer peptide (left y-axis), is indicated by a black bar at the starting position of the peptide (x-axis). The solvent accessibility (right y-axis) is indicated by the grey trace. Positions within 7Å of the active site (based on Cβ, with Cα for Gly) are bracketed in red along the x-axis. Locations of mutations in the seven structure-based designs are indicated by blue arrows, those in previous sequence-based designs are indicated by green arrows, and those common to both studies are indicated with black arrows.
Figure 2
Figure 2
Pareto frontier of the P99βL design space. The computed Sstr is plotted vs. the computed Sepi for each of the seven unique designs (indicated as blue circles, wild type in red). Sstr, the rigid energy score, is one component of the structure-based design process. Sepi is the total predicted epitope count for each protein. The epitope content of three representative proteins (Str 32, Str 38, and wild-type) is shown mapped onto the P99βL structure (PDB ID 1XX2A). Epitope density is represented with a color gradient, where red indicates dense overlapping epitopes and white indicates sequences free of putative epitopes.
Figure 3
Figure 3
Correlations between computational design parameters and experimentally measured performance metrics. A Sstr vs. Tm. B Sstr vs. kcat. C Sstr vs. kcat /Km. D Sstr vs. MIC. E Sepi vs. Gobal Immunoreactivity Pareto optimal enzymes are shown as solid black diamonds and wild type P99βL is shown as an open black circle. Linear regressions are shown along with R2 values, and an F test was used to determine statistical significance for non-zero slopes (P values are provided).
Figure 4
Figure 4
Peptide binding affinities for human MHC II proteins. The peptide-MHC II binding affinities are represented as IC50 values and are plotted for each pair of wild-type and variant peptides. Shading indicates binding strength by category: strong (IC50<1 μM, dark grey), moderate (1 μM≤IC50<10 μM, medium grey), weak (10 μM≤IC50<100 μM, light grey), or non-binding (IC50 ≥100 μM, white). The slope of the connecting lines are a relative measure of deimmunizing efficacy, where larger positive slopes indicate a greater fold decrease in affinity relative to wild type, and negative slopes indicate a mutation that enhanced binding.
Figure 5
Figure 5
Comparison of sequence-based and structure-based designs A Relative Tm. B Relative Km. C Relative kcat. D Relative kcat /Km. E Relative MIC. F Gobal Immunoreactivity Relative parameters, normalized to wild type from the respective study, are provided for seven sequence-based designs (green) and seven structure-based designs (blue).
Figure 6
Figure 6
Comparison of whole-protein categorical immunoreactivity for sequence- and structure-based designs. The counts for constituent peptides from each enzyme were summed and plotted by semi-quantitative category (y-axis). Each individual peptide’s binding strength for the four MHC II alleles DRB1*0101, 0401, 0701, and 1501 were binned as strong (IC50<1 μM, red), moderate (1 μM≤IC50<10 μM, orange), weak (10 μM≤IC50<100 μM, yellow), or non-binding (IC50 ≥100 μM, not shown). The horizontal hatched lines are visual guides for the wild type binding counts in each category.
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