In silico tools for predicting novel epitopes

BARRA, CAROLINA; NILSSON, JONAS BIRKELUND; SAKSAGER, ASTRID; CARRI, IBEL; DELEURAN, SEBASTIAN; GARCIA ALVAREZ, HELI MAGALÍ; HØIE, MAGNUS HARALDSON; LI, YUCHEN; CLIFFORD, JOAKIM NØDDESKOV; RICHIE WAN, YAT-TSAI; SANZ MORETA, LYS; NIELSEN, MORTEN

Intracellular Pathogens

Springer Science

Lugar: New York; Año: 2024;

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically,antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for the irrational use.p { line-height: 115%; text-align: left; orphans: 2; widows: 2; margin-bottom: 0.1in; direction: ltr; background: transparent }a:link { color: #0000ff; text-decoration: underline }