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

Abstract

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.

Publication DOI: https://doi.org/10.1186/1745-7580-6-S2-S4
Divisions: College of Health & Life Sciences > Aston Pharmacy School
College of Health & Life Sciences
College of Health & Life Sciences > Chronic and Communicable Conditions
Additional Information: © 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.
Uncontrolled Keywords: atomistic molecular dynamics ,molecular systems,macromolecular systems,Immunology,Molecular Biology,Computational Theory and Mathematics,Applied Mathematics,Computer Science Applications
Last Modified: 28 Feb 2024 08:10
Date Deposited: 19 Aug 2019 08:52
Full Text Link: http://www.immu ... content/6/S2/S4
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2010-11-03
Authors: Flower, Darren R (ORCID Profile 0000-0002-8542-7067)
Phadwal, Kanchan
Macdonald, Isabel K.
Coveney, Peter V.
Davies, Matthew N.
Wan, Shunzhou

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