ImmunoGrid is the European Virtual Human Immune System Project which is funded by the EU Sixth Framework Programme. The goal of this project, which began in February 2006, is to model the Human Immune System by computer simulation. Simulations will model different aspects, from the development of the immune system and its recogniton of self, to the immune response to pathogens. The simulations will take place at different levels (organ, cellular and molecular) according to the problem addressed and the information that is available at each level.
The systems biology project involves eight laboratories in France, Italy, Denmark, Australia and the UK. Here in London we will be constructing a database of information about all aspects of the immune system. This database will be interfaced to the simulator. We shall also be developing new techniques for modelling critical intermolecular interactions in the immune system. We shall also be making available software useful at a re-clinical stage.
Currently Dr Mark Halling-Brown
has set up a demonstration of a simpler version of the
simulator and this can be accessed by clicking Projects and then C-ImmSim Online
on the Immunology Grid Website.
2) Immunology Grid
Our goal is to provide easy-to-use computational tools that can be assembled together in work-flow patterns suitable for the study of immunological problems such as histocompatibility, vaccine design, autoimmunity and allergy. The computational and data resources required for the project will generally be found on different hardware and at different sites. In order to integrate these resources we are using Grid technology and observing existing or emerging standards for distributed computing and data access.
In collaboration with the ICENI computing group at the London e-Science Centre we have implemented a workflow that uses the ICENI middleware. Dr Mark Halling-Brown and Dr Barry Smith have constructed a pilot grid with nodes for evaluating proteasomal cleavage, protein-peptide interactions and tissue expression. We are developing a web site to provide workflow and distributed computing support in an antigenic prediction pipeline to support these calculations.
We are also exploring methods of estimating MHC:peptide binding affinities using molecular dynamics. Results obtained from fairly crude calculations compete well with those obtained by matrix methods for MHC Class II complexes (Matthews et al.)(ref(i)). We are now looking at more exact methods that will implemented in APPP. More information can be found by clicking Projects and then APPP on the Immunology Grid Website.
In collaboration with the Anthony Nolan Research Institute, we are trying to enhance the host-versus-leukaemia effect to reduce the relapse rate in patients suffering from chronic leukaemia. To this end, Dr Mark Halling-Brown has constructed a database SiPeP of non-synonymous single nucleotide polymorphisms (SNPs) and their frequencies in the human population. Mark has developed tools to update it regularly as the primary databases evolve.
The database contains all the nonameric peptides that contain a SNP.
For each peptide, data is being included on the probability of
proteasome cleavage being able to produce that peptide
and the likelihood of that peptide binding to certain common class I
MHC alleles.
3) Vaccine design
In collaboration with DSTL and CAMR, Porton Down, we are predicting likely antigenic proteins that would be suitable as candidate vaccines against Mycobacterium tuberculosis and Francisella tularensis. We start with the genome sequence and produce a set of proteins that are likely either to be secreted or be outer membrane proteins. We then predict the proteins from this set that are likely to contain a high density of peptides which can promiscuously bind to MHC molecules. Some of our vaccine candidates are being tested in animal models. Raheel Shaban has constructed a pipeline of tools for in silico vaccine design. This involves modules for protein targeting and secretion and matrix-based methods for MHC:peptide binding. Bacterial proteomes can be scanned for proteins with a high density of antigenic peptides. We are currently using our toolbox to identify possible sub-unit vaccines. To support this, we are developing a vaccine design pipeline.
References
Last updated 17 October 2006
(i)A Novel Predictive Technique for the MHC Class II-peptide binding
interaction, Davies M N, Sansom, C E, Beazley C and Moss D S,
Mol. Medicine, (2003), 9, 220-225.
(ii)Fugu-Human synteny viewer: Web software for automatic annotation
and display of synteny between Fugu genomic sequence and Human,
Halling-Brown, M, Sansom, C, Moss, D S, Elgar, G and Edwards, Y J K,
Nucl. Acid Res., (2004), 32(8), 1-5.
(iii)The Bioinformatics Template Library - Generic Components for Biocomputing.
W. R. Pitt, M. A. Williams, M. Steven, B. Sweeney, A. J. Bleasby, D. S. Moss.
Bioinformatics, (2001), 17(8), 729-737.
3) BioSimGrid (funded by BBSRC)
We are members of BioSimGrid which is a BBSRC Grid pilot project to
establish a distributed database of kitemarked molecular dynamics
simulations of biological molecules. It is developing tools to analyse
the time frames stored in the database. The project is currently based on Web services.
Any questions and bug reports to
David Moss