Enhancing Vaccine Development Through SVM-Based Epitope Prediction

The primary role of our immune system is to discover and identify foreign contaminants . This process involves the interaction of various components, including the immunogen (foreign entity), the humoral immune system (producing antibodies), and the cellular immune system (generating sensitized lymphocytes). Immunogens have surface structures called epitopes, which allow the immune system to distinguish between self and foreign entities. Macrophages, specific immune cells, recognize epitopes and create short peptides called immunodominant peptides (IDPs). These IDPs bind to MHC proteins on the macrophage surface and are presented to T cells, initiating an immune response cascade to eliminate the immunogen. For the development of vaccines, accurate prediction is very crucial . A new approach, the bio support vector machine, integrates a bio-basis function into traditional support vector machines to directly analyze protein sequences without the need for feature extraction. This method achieved a prediction accuracy of 90.31% in 10-fold cross-validation, outperforming previous algorithms, including support vector machines, which achieved 87.86% accuracy.