Editing Epitope (section)

==Epitope mapping==
{{main|Epitope mapping}}

=== T cell epitopes ===
MHC class I and II epitopes can be reliably predicted by computational means alone,<ref>{{cite journal |last1=Koren |first1=E. |last2=Groot |first2=Anne De |last3=Jawa |first3=V. |last4=Beck |first4=K. |last5=Boone |first5=T. |last6=Rivera |first6=D. |last7=Li |first7=L. |last8=Mytych |first8=D. |last9=Koscec |first9=M. |last10=Weeraratne |first10=D. |last11=Swanson |first11=S. |last12=Martin |first12=W. |title=Clinical validation of the 'in silico' prediction of immunogenicity of a human recombinant therapeutic protein |journal=Institute for Immunology and Informatics Faculty Publications |date=1 January 2007 |volume=124 |issue=1 |pages=26–32 |doi=10.1016/j.clim.2007.03.544 |pmid=17490912 |s2cid=12867280 |url=https://digitalcommons.uri.edu/immunology_facpubs/69/ |url-access=subscription }}</ref> although not all in-silico T cell epitope prediction algorithms are equivalent in their accuracy.<ref>{{cite journal |last1=De Groot |first1=Anne S. |last2=Martin |first2=William |title=Reducing risk, improving outcomes: Bioengineering less immunogenic protein therapeutics |journal=Clinical Immunology |date=May 2009 |volume=131 |issue=2 |pages=189–201 |doi=10.1016/j.clim.2009.01.009 |pmid=19269256 }}</ref> There are two main methods of predicting peptide-MHC binding: data-driven and structure-based.<ref name="Sanchez-Trincado et al 2017"/> Structure based methods model the peptide-MHC structure and require great computational power.<ref name="Sanchez-Trincado et al 2017"/> Data-driven methods have higher predictive performance than structure-based methods.<ref name="Sanchez-Trincado et al 2017"/> Data-driven methods predict peptide-MHC binding based on peptide sequences that bind MHC molecules.<ref name="Sanchez-Trincado et al 2017"/> By identifying T-cell epitopes, scientists can track, phenotype, and stimulate T-cells.<ref>{{cite journal |last1=Peters |first1=Bjoern |last2=Nielsen |first2=Morten |last3=Sette |first3=Alessandro |title=T Cell Epitope Predictions |journal=Annual Review of Immunology |date=26 April 2020 |volume=38 |issue=1 |pages=123–145 |doi=10.1146/annurev-immunol-082119-124838 |pmid=32045313 |s2cid=211085860 |pmc=10878398 }}</ref><ref name="Ahmad Eweida El-Sayed 2016">{{cite journal |last1=Ahmad |first1=Tarek A. |last2=Eweida |first2=Amrou E. |last3=El-Sayed |first3=Laila H. |title=T-cell epitope mapping for the design of powerful vaccines |journal=Vaccine Reports |date=December 2016 |volume=6 |pages=13–22 |doi=10.1016/j.vacrep.2016.07.002 }}</ref><ref>{{cite journal |vauthors=Dezfulian MH, Kula T, Pranzatelli T, Kamitaki N, Meng Q, Khatri B, Perez P, Xu Q, Chang A, Kohlgruber AC, Leng Y, Jupudi AA, Joachims ML, Chiorini JA, Lessard CJ, Farris AD, Muthuswamy SK, Warner BM, Elledge SJ |title=TScan-II: A genome-scale platform for the de novo identification of CD4+ T cell epitopes |journal=Cell |volume=186 |issue=25 |pages=5569–86 |date=December 2023 |pmid=38016469 |doi=10.1016/j.cell.2023.10.024 |doi-access=free |pmc=10841602 }}</ref><ref>{{cite journal |vauthors=Kula T, Dezfulian MH, Wang CI, Abdelfattah NS, Hartman ZC, Wucherpfennig KW, Lyerly HK, Elledge SJ |title=T-Scan: A Genome-wide Method for the Systematic Discovery of T Cell Epitopes |journal=Cell |volume=178 |issue=4 |pages=1016–28 |date=August 2019 |pmid=31398327 |pmc=6939866 |doi=10.1016/j.cell.2019.07.009 }}</ref>

=== B cell epitopes ===
There are two main methods of epitope mapping: either structural or functional studies.<ref name="Potocnakova et al 2016">{{cite journal |last1=Potocnakova |first1=Lenka |last2=Bhide |first2=Mangesh |last3=Pulzova |first3=Lucia Borszekova |title=An Introduction to B-Cell Epitope Mapping and In Silico Epitope Prediction |journal=Journal of Immunology Research |date=2016 |volume=2016 |pages=1–11 |doi=10.1155/2016/6760830 |pmid=28127568 |pmc=5227168 |doi-access=free }}</ref> Methods for structurally mapping epitopes include [[X-ray crystallography]], [[nuclear magnetic resonance]], and [[Electron microscope|electron microscopy]].<ref name="Potocnakova et al 2016"/> X-ray crystallography of Ag-Ab complexes is considered an accurate way to structurally map epitopes.<ref name="Potocnakova et al 2016"/> Nuclear magnetic resonance can be used to map epitopes by using data about the Ag-Ab complex.<ref name="Potocnakova et al 2016"/> This method does not require crystal formation but can only work on small peptides and proteins.<ref name="Potocnakova et al 2016"/> Electron microscopy is a low-resolution method that can localize epitopes on larger antigens like virus particles.<ref name="Potocnakova et al 2016"/>

Methods for functionally mapping epitopes often use binding assays such as [[western blot]], [[dot blot]], and/or [[ELISA]] to determine antibody binding.<ref name="Potocnakova et al 2016"/> Competition methods look to determine if two [[Monoclonal antibody|monoclonal antibodies]] (mABs) can bind to an antigen at the same time or compete with each other to bind at the same site.<ref name="Potocnakova et al 2016"/> Another technique involves high-throughput [[mutagenesis]], an epitope mapping strategy developed to improve rapid mapping of conformational epitopes on structurally complex proteins.<ref>{{cite journal |last1=Davidson |first1=Edgar |last2=Doranz |first2=Benjamin J. |title=A high-throughput shotgun mutagenesis approach to mapping B-cell antibody epitopes |journal=Immunology |date=September 2014 |volume=143 |issue=1 |pages=13–20 |doi=10.1111/imm.12323 |pmid=24854488 |pmc=4137951 }}</ref> Mutagenesis uses randomly/site-directed mutations at individual residues to map epitopes.<ref name="Potocnakova et al 2016"/> B-cell epitope mapping can be used for the development of antibody therapeutics, peptide-based vaccines, and immunodiagnostic tools.<ref name="Potocnakova et al 2016"/><ref name="Ahmad Eweida Sheweita 2016">{{cite journal |last1=Ahmad |first1=Tarek A. |last2=Eweida |first2=Amrou E. |last3=Sheweita |first3=Salah A. |title=B-cell epitope mapping for the design of vaccines and effective diagnostics |journal=Trials in Vaccinology |date=2016 |volume=5 |pages=71–83 |doi=10.1016/j.trivac.2016.04.003 |doi-access=free }}</ref>