T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

Darren R Flower, Kanchan Phadwal, Isabel K. Macdonald, Peter V. Coveney, Matthew N. Davies, Shunzhou Wan

Research output: Contribution to journalArticle


Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.
Original languageEnglish
Article numberS4
Pages (from-to)S4
JournalImmunome Research
Issue numberSuppl.2
Publication statusPublished - 3 Nov 2010


Bibliographical note

© 2010 Flower et al; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


  • atomistic molecular dynamics
  • molecular systems
  • macromolecular systems

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