A Cohesive and Integrated Platform for Immunogenicity Prediction
In silico methods for immunogenicity prediction mine the enormous quantity of data arising from deciphered genomes and proteomes to identify immunogenic proteins. While high and productive immunogenicity is essential for vaccines, therapeutic proteins and
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Introduction In silico methods developed during the last decade, as implemented in pharmaceutical research, have accelerated and optimized the process of drug discovery and development, reducing the cost of in vitro and in vivo experiments and the number of animal experiments and shortening the time from bench to bedside. As biological therapeutics have grown in importance, the need to develop in silico methods for immunogenicity prediction—which aims to mine the enormous amount of data arising from deciphered genomes and proteomes and to identify immunogenic proteins—has likewise grown in importance. While high but productive immunogenicity is essential for vaccines, therapeutic proteins and monoclonal antibodies should be minimally immunogenic. The immunogenicity of both foreign and self-proteins is largely determined by the peptide epitopes they contain. The epitope is that part of the antigen that can be recognized by the host immune system, particularly by antibodies, B cells, or T cells. The epitopes can be categorized as conformational or linear, depending on their structure and integration with the paratope [1]. T-cell epitopes are presented on the surface of an antigen-presenting cell (APC), where they are bound to major histocompatibility complex (MHC) molecules in order to induce a T-cell-driven immune response [2]. MHCs are among the most polymorphic protein in higher vertebrates, with more than 12,000 class I and class II MHC molecules listed in IMGT/HLA [3]. Class II MHCs are expressed on specialized cell types, including professional APCs such as B cells, macrophages, and dendritic cells, whereas class I MHCs are found on every nucleated cell [4]. MHC class I molecules usually present
Sunil Thomas (ed.), Vaccine Design: Methods and Protocols, Volume 2: Vaccines for Veterinary Diseases, Methods in Molecular Biology, vol. 1404, DOI 10.1007/978-1-4939-3389-1_50, © Springer Science+Business Media New York 2016
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peptides between 8 and 11 amino acids in length, although much longer class I epitopes are now known, whereas peptides binding to MHC class II have lengths varying from 12 to 25 amino acids [5]. If appropriate quantities of the epitope are presented, a T cell may trigger an adaptive immune response specific for the pathogen. The recognition of epitopes by T cells, and the concomitant induction of immune responses, has a key role to play within an individual’s immune system. Even the slightest deviation from normal functioning may significantly impact an organism. In the case of autoimmune disease, T cells recognize the cell’s native peptides as foreign, attacking, and eventually destroying the organism’s own tissues. Certain viruses, such as human immunodeficiency virus (HIV), hepatitis C, avian, and swine influenza, manage to avoid recognition by the T cell by relying on mutations that alter the amino acid sequences of the proteins encoded by the virus that allows them to evade or “escape” T-cell surveillance [6, 7]. Knowledge about epitopes is vital if protei
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