Biotechnology Journal International

Aims: Several studies have reported the existence for T helper cell epitopes with the persistence of unwanted immune reactions for several protein drugs. T-cell epitope is an amino acid or set of amino acids that are capable of being recognized form one or more T-cell receptors. There is also an indication that T helper cells are involved in the anti-drug antibodies development to therapeutic interferon beta-1a. Protein drugs containing Major histocompatibility complex class II T cell epitopes are likely to elicit anti-drug antibodies. Binding specificity between T-cell epitopes and major histocompatibility molecules are the most important determinant step in finding the T-cellular immune responses. The data obtained from the present study provides new insights into prediction of therapeutic Interferon beta T helper cells epitopes using T cell epitope prediction tools, mapping of clusters of predicted epitopes.

Study Design: Insilico analysis by bioinformatics tools was to predict T-cell epitopes of Interferon beta-1a.

Methodology: Several Insilico prediction tools (immunoinformatics tools) including Proped, NetMHCIIpan3.0 and Immune Epitope Database Analysis Resource (IEDB-AR) are available to map the potential major histocompatibility class II T cell epitopes. After predicting potential T-cell epitopes, epitopes were mapped on interferon beta-1a using MIMOX2 server.

Results: The potential MHC class II immunogenic sequence of 50 amino acids “TRGKLMSSLHLKRYYGRILHYLKAKEYSHCAWTIVRVEILRNFYFINRLTG” With IFN-β-1a (position 111-161) were identified. This study can provide the understanding the relevance to T-cell activation for prediction and assessment of unwanted immune responses.

Conclusions: Insilico prediction by using the available tools helps in reducing the time and cost for the immunologists during the vaccine design. By predicting them we will come to know, which peptides play major role and synthesize them using invitro technologies.