Evaluating the Immunogenicity of Protein Drugs by ApplyingIn VitroMHC Binding Data and the Immune Epitope Database and Analysis Resource

Sinu Paul,Ravi V Kolla,Daniela Weiskopf,Yohan Kim,Alessandro Sette,Bjoern Peters,Ward Fleri,John Sidney

doi:10.1155/2013/467852

Sinu Paul, Ravi V Kolla + Show 6 more

Open Access

https://doi.org/10.1155/2013/467852

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Abstract

The immune system has evolved to become highly specialized in recognizing and responding to pathogens and foreign molecules. Specifically, the function of HLA class II is to ensure that a sufficient sample of peptides derived from foreign molecules is presented to T cells. This leads to an important concern in human drug development as the possible immunogenicity of biopharmaceuticals, especially those intended for chronic administration, can lead to reduced efficacy and an undesired safety profile for biological therapeutics. As part of this review, we will highlight the molecular basis of antigen presentation as a key step in the induction of T cell responses, emphasizing the events associated with peptide binding to polymorphic and polygenic HLA class II molecules. We will further review methodologies that predict HLA class II binding peptides and candidate epitopes. We will focus on tools provided by the Immune Epitope Database and Analysis Resource, discussing the basic features of different prediction methods, the objective evaluation of prediction quality, and general guidelines for practical use of these tools. Finally the use, advantages, and limitations of the methodology will be demonstrated in a review of two previous studies investigating the immunogenicity of erythropoietin and timothy grass pollen.

Highlights

Immunogenicity of drug candidates is a significant concern that requires exhaustive evaluation during drug development to ensure maximum efficacy and optimal safety of administered therapeutics [1,2,3,4]
We will discuss different HLA class II epitope prediction methodologies provided by the Immune Epitope Database and Analysis Resource (IEDB—http://tools .iedb.org/main/) and how they can be utilized to modify the immunogenicity of protein therapeutics to mitigate possible safety risks while maximizing efficacy
The MHC class II binding prediction tool in the IEDB makes available a variety of methods, including NN-align and NetMHCIIpan [35, 36], SMMalign [11], matrices based on positional scanning combinatorial libraries [38], Sturniolo et al [39] and average relative binding method (ARB) methods [30], and a consensus method [33, 38] based on a combination of NN-align, SMM-align, and CombLib methods (Table 1)

Summary

Introduction

Immunogenicity of drug candidates is a significant concern that requires exhaustive evaluation during drug development to ensure maximum efficacy and optimal safety of administered therapeutics [1,2,3,4]. When the threedimensional structure of MHC molecules was described [8], it was demonstrated that these hypervariable regions correspond to specific pockets within the molecule that engage peptide side chains, and that each pocket was associated with a relatively narrow chemical specificity This feature results in the different allelic variants having somewhat unique binding repertoires. The polygenic and polymorphic nature of HLA binding and T cell recognition leads to a broad and low threshold of selectivity for activation of the immune response These features reflect the biological function of HLA molecules in host immunity that ensures that for each pathogen protein, at least some peptides are bound and presented to T cells. We will discuss different HLA class II epitope prediction methodologies provided by the Immune Epitope Database and Analysis Resource (IEDB—http://tools .iedb.org/main/) and how they can be utilized to modify the immunogenicity of protein therapeutics to mitigate possible safety risks while maximizing efficacy

Different Methodologies Used to Predict HLA Class II Binding

Methods

Test Case Scenario 1

Test Case Scenario 2

Findings

Conclusions