Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

Affinity and avidity models in autoimmune disease

Department of Mathematical Sciences, Clemson University, Clemson, SC 29634, USA

In this work, we develop a theoretical model of affinity and avidity in the immune system.The model is based on an extension of the Cubic Ternary Complex (CTC) model of receptor - ligandinteractions to the immunological synapse setting. We use the resulting equation to study how lysiscan occur for a cell exhibiting only self proteins. This general affinity model gives a nice quantitativetool which can be used to explore a nonlinear model of how a T Cell can have a productive interactionwith a MHC-I complex even though the encapsulated peptide fragment is a self protein. The modelbuilt will allow the creation of even more general autoimmune models within the framework of B andT Cell differentiation via cytokine signalling families.
  Article Metrics


1. Peterson JK, Kesson AM, King NJC (2017) A model of auto immune response. BMC Immunol 18 (Suppl 1): 48–65.

2. Weiss JM, Morgan PH, Lutz MW, et al. (1996) The cubic ternary complex receptor-occupancy model: I: Model description. J Theor Biol 178: 151–167.    

3. Weiss JM, Morgan PH, Lutz MW, et al. (1996) The cubic ternary complex receptor-occupancy model: II: understanding affinity. J Theor Biol 178: 169–182.    

4. Weiss JM, Morgan PH, Lutz MW, et al.(1996) The cubic ternary complex receptor-occupancy model: III: resurrecting efficacy. J Theor Biol 181: 391–397.

5. Huppa J, Davis M (2013) The Interdisciplinarity Science of T-cell Recognition. Adv Immunol 119: 1–50.    

6. Davis MM, Krogsgaard M, Huse M, et al. (2007) T cells as a self-referential sensory organ. Annu Rev Immunol 25: 681–695.    

7. Kurschus FC,Wörtege S,Waisman A (2011) Modeling a complex disease: Multiple sclerosis. Adv Immunol 110: 111–137.    

8. Dendrou CA, Fugger L (2017) Immunomodulation in multiple sclerosis: promises and pitfalls. Curr Opin Immunol 49: 37–43.    

9. Baranzini SE, Oksenberg JR (2017) The genetics of multiple sclerosis: From 0 to 200 in 50 Years. Trends Genet 33: 960–970.    

10. Mitsikostas DD, Goodin DS (2017) Comparing the efficacy of disease-modifying therapies in multiple sclerosis. Mult Scler Relat Dis 18: 109–116.    

11. Geginat J, Paroni M, Pagani M, et al. (2017) The enigmatic role of viruses in multiple sclerosis: Molecular mimicry or disturbed immune surveillance? Trends Immunol 38: 498–512.    

12. Roybal KT, Lim WA (2017) Synthetic immunology: Hacking immune cells to expand their therapeutic capabilities. Annu Rev Immunol 35: 229–253.    

13. Srivastava S, Riddell SR (2015) Engineering CAR-T cells: Design concepts. Trends Immunol 36: 494–502.    

14. Wekerle H (2017) Brain autoimmunity and intestinal microbiota: 100 trillion game changers. Trends Immunol 38: 483–497.    

© 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline
Copyright © AIMS Press All Rights Reserved