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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...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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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. |
format | Text |
id | pubmed-2981876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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