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Correlation of in silico prediction of immunogenicity of therapeutic proteins with immune responses in clinical studies.
Author(s) -
Jawa Vibha,
Mytych Daniel,
Moxness Michael,
Zhong Don,
Swanson Steven,
Chirmule Narendra,
Goletz Theresa
Publication year - 2008
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.22.2_supplement.563
Subject(s) - immunogenicity , epitope , antibody , in silico , neutralizing antibody , immune system , immunology , biology , medicine , genetics , gene
Immune responses elicited by therapeutic proteins can have serious consequences in humans. The immunogenic potential of 5 recombinant proteins (FPX1‐FPX5) was assessed using in silico algorithms (EpiMatrix) to predict MHC class II binding epitopes and the prediction scores were compared with antibody incidence observed in clinical studies. The immunogenicity scores were compared to proteins with known low and high potential immunogenicity. Immunogenicity was assessed by measuring the incidence of anti‐drug antibodies (neutralizing and non‐neutralizing antibodies) in clinical studies. High immunogenicity scores predicted for FPX 1 and FPX 2 were associated with a high incidence of neutralizing antibody response of 40% and 12%, respectively. In contrast, FPX proteins 3, 4 and 5 had negative immunogenicity scores and were supported clinically with a low/non‐detectable incidence of neutralizing antibodies (0 – 0.5%). These observations suggest that in silico prediction of MHC class II binding epitopes can be useful for predicting immunogenicity for therapeutic proteins. This approach can be helpful in selecting the appropriate candidate during early stages of therapeutic protein drug development.