What is immunoinformatics?
Immunoinformatics applies informatics techniques to the study of molecules of the immune system. Scientists can study immunogenicity at the level of epitopes, subunit vaccines, or weakened or inactive pathogens. One principal goal of this study is the efficient and effective prediction of immunogenicity.
Immunogenicity is the ability of a pathogen or a part or molecule of a pathogen to induce a specific immune response when first exposed to surveillance by the immune system.
Antigenicity is the capacity for recognition by the adaptive immune response molecular machinery in a recall response.
In Silico experiments, using a computer or computer simulation to enable more effective biological experiments, historically also referred to as virtual experimentation in a human's brain, theoretical biology, or "Gedanken experiments = Thought experiments," can help predict immunogenicity. In-Silico Immunogenicity Predictions involve
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T cell epitope predictions from primary sequences
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Peptide binding predictions to MHC class I and MHC class II
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B cell epitope predictions – linear versus conformational epitopes (3D structure)
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Antigen structure prediction via protein homology model
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Others.
Flower DR; Immunoinformatics and the in silico prediction of immunogenicity. An introduction. Methods Mol Biol. 2007;409:1-15. doi: 10.1007/978-1-60327-118-9_1.