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


Autoria(s): Flower, Darren R; Phadwal, Kanchan; Macdonald, Isabel K.; Coveney, Peter V.; Davies, Matthew N.; Wan, Shunzhou
Data(s)

03/11/2010

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/16069/1/T_cell_epitope_prediction_and_immune_complex.pdf

Flower, Darren R; Phadwal, Kanchan; Macdonald, Isabel K.; Coveney, Peter V.; Davies, Matthew N. and Wan, Shunzhou (2010). T-cell epitope prediction and immune complex simulation using molecular dynamics:state of the art and persisting challenges. Immunome Research, 6 (Suppl.2), S4.

Relação

http://eprints.aston.ac.uk/16069/

Tipo

Article

PeerReviewed