Computational discovery of vaccine targets

• Main Author: Zhang, Guang Lan
• Other Authors: Kwoh Chee Keong
• Format: Theses and Dissertations
• Language: English
• Published: 2008
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
• Online Access: https://hdl.handle.net/10356/14139
• Institution: Nanyang Technological University

Epitope-based vaccines show great potential in fighting infectious diseases as well as non-communicable diseases. The identification of T-cell epitopes, a crucial step in the design of epitope-based vaccines, is a highly combinatorial problem. Peptide binding to major histocompatibility complex (MHC) molecules is necessary for cellular immune recognition because antigens can only be recognized by T-cells in the form of a peptide complexed by MHC molecules. Experimental approaches for identification of T-cell epitopes are costly, time-consuming, and not applicable to large scale studies. Bioinformatics methods are therefore instrumental for enabling systematic large-scale T-cell epitope mapping. The aim of this work is to aid vaccine targets discovery by combining multiple computational approaches for precise mapping of individual promiscuous T-cell epitopes as well as T-cell epitope hotspots – the regions in protein antigens that have high concentration of these targets.