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

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 syste...

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Detalles Bibliográficos
Autores principales: Flower, Darren R, Phadwal, Kanchan, Macdonald, Isabel K, Coveney, Peter V, Davies, Matthew N, Wan, Shunzhou
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2981876/
https://www.ncbi.nlm.nih.gov/pubmed/21067546
http://dx.doi.org/10.1186/1745-7580-6-S2-S4
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author Flower, Darren R
Phadwal, Kanchan
Macdonald, Isabel K
Coveney, Peter V
Davies, Matthew N
Wan, Shunzhou
author_facet Flower, Darren R
Phadwal, Kanchan
Macdonald, Isabel K
Coveney, Peter V
Davies, Matthew N
Wan, Shunzhou
author_sort Flower, Darren R
collection PubMed
description 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.
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spelling pubmed-29818762010-11-17 T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges Flower, Darren R Phadwal, Kanchan Macdonald, Isabel K Coveney, Peter V Davies, Matthew N Wan, Shunzhou Immunome Res Review 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. BioMed Central 2010-11-03 /pmc/articles/PMC2981876/ /pubmed/21067546 http://dx.doi.org/10.1186/1745-7580-6-S2-S4 Text en Copyright ©2010 Flower et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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.
spellingShingle Review
Flower, Darren R
Phadwal, Kanchan
Macdonald, Isabel K
Coveney, Peter V
Davies, Matthew N
Wan, Shunzhou
T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title_full T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title_fullStr T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title_full_unstemmed T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title_short T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
title_sort t-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2981876/
https://www.ncbi.nlm.nih.gov/pubmed/21067546
http://dx.doi.org/10.1186/1745-7580-6-S2-S4
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