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 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.
Life and Health Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK.
Darren R
DR
Flower
Oxford Biomedical Research Centre, The John Radcliffe Hospital, Room 4503, Corridor 4b, Level 4, Oxford, OX 3 9DU, UK.
Kanchan
K
Phadwal
OncImmune Limited, Clinical Sciences Building, Nottingham City Hospital, Hucknall Rd. Nottingham, NG5 1PB, UK.
Isabel K
IK
Macdonald
Centre for Computational Science, Chemistry Department, University College of London, 20 Gordon Street, WC1H 0AJ, London, UK.
Peter V
PV
Coveney
SGDP, Institute of Psychiatry, King's College London, De Crespigny Park, London, SE5 8AF, UK.
Matthew N
MN
Davies
Centre for Computational Science, Chemistry Department, University College of London, 20 Gordon Street, WC1H 0AJ, London, UK.
Shunzhou
S
Wan