25,485 research outputs found
Large Scale In Silico Screening on Grid Infrastructures
Large-scale grid infrastructures for in silico drug discovery open
opportunities of particular interest to neglected and emerging diseases. In
2005 and 2006, we have been able to deploy large scale in silico docking within
the framework of the WISDOM initiative against Malaria and Avian Flu requiring
about 105 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These
achievements demonstrated the relevance of large-scale grid infrastructures for
the virtual screening by molecular docking. This also allowed evaluating the
performances of the grid infrastructures and to identify specific issues raised
by large-scale deployment.Comment: 14 pages, 2 figures, 2 tables, The Third International Life Science
Grid Workshop, LSGrid 2006, Yokohama, Japan, 13-14 october 2006, to appear in
the proceeding
A perspective on the Healthgrid initiative
This paper presents a perspective on the Healthgrid initiative which involves
European projects deploying pioneering applications of grid technology in the
health sector. In the last couple of years, several grid projects have been
funded on health related issues at national and European levels. A crucial
issue is to maximize their cross fertilization in the context of an environment
where data of medical interest can be stored and made easily available to the
different actors in healthcare, physicians, healthcare centres and
administrations, and of course the citizens. The Healthgrid initiative,
represented by the Healthgrid association (http://www.healthgrid.org), was
initiated to bring the necessary long term continuity, to reinforce and promote
awareness of the possibilities and advantages linked to the deployment of GRID
technologies in health. Technologies to address the specific requirements for
medical applications are under development. Results from the DataGrid and other
projects are given as examples of early applications.Comment: 6 pages, 1 figure. Accepted by the Second International Workshop on
Biomedical Computations on the Grid, at the 4th IEEE/ACM International
Symposium on Cluster Computing and the Grid (CCGrid 2004). Chicago USA, April
200
A Novel Scoring Based Distributed Protein Docking Application to Improve Enrichment
Molecular docking is a computational technique which predicts the binding energy and the preferred binding mode of a ligand to a protein target. Virtual screening is a tool which uses docking to investigate large chemical libraries to identify ligands that bind favorably to a protein target. We have developed a novel scoring based distributed protein docking application to improve enrichment in virtual screening. The application addresses the issue of time and cost of screening in contrast to conventional systematic parallel virtual screening methods in two ways. Firstly, it automates the process of creating and launching multiple independent dockings on a high performance computing cluster. Secondly, it uses a NË™ aive Bayes scoring function to calculate binding energy of un-docked ligands to identify and preferentially dock (Autodock predicted) better binders. The application was tested on four proteins using a library of 10,573 ligands. In all the experiments, (i). 200 of the 1000 best binders are identified after docking only 14% of the chemical library, (ii). 9 or 10 best-binders are identified after docking only 19% of the chemical library, and (iii). no significant enrichment is observed after docking 70% of the chemical library. The results show significant increase in enrichment of potential drug leads in early rounds of virtual screening
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
The organization and mining of malaria genomic and post-genomic data is
highly motivated by the necessity to predict and characterize new biological
targets and new drugs. Biological targets are sought in a biological space
designed from the genomic data from Plasmodium falciparum, but using also the
millions of genomic data from other species. Drug candidates are sought in a
chemical space containing the millions of small molecules stored in public and
private chemolibraries. Data management should therefore be as reliable and
versatile as possible. In this context, we examined five aspects of the
organization and mining of malaria genomic and post-genomic data: 1) the
comparison of protein sequences including compositionally atypical malaria
sequences, 2) the high throughput reconstruction of molecular phylogenies, 3)
the representation of biological processes particularly metabolic pathways, 4)
the versatile methods to integrate genomic data, biological representations and
functional profiling obtained from X-omic experiments after drug treatments and
5) the determination and prediction of protein structures and their molecular
docking with drug candidate structures. Progresses toward a grid-enabled
chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa
Innovative in silico approaches to address avian flu using grid technology
The recent years have seen the emergence of diseases which have spread very
quickly all around the world either through human travels like SARS or animal
migration like avian flu. Among the biggest challenges raised by infectious
emerging diseases, one is related to the constant mutation of the viruses which
turns them into continuously moving targets for drug and vaccine discovery.
Another challenge is related to the early detection and surveillance of the
diseases as new cases can appear just anywhere due to the globalization of
exchanges and the circulation of people and animals around the earth, as
recently demonstrated by the avian flu epidemics. For 3 years now, a
collaboration of teams in Europe and Asia has been exploring some innovative in
silico approaches to better tackle avian flu taking advantage of the very large
computing resources available on international grid infrastructures. Grids were
used to study the impact of mutations on the effectiveness of existing drugs
against H5N1 and to find potentially new leads active on mutated strains. Grids
allow also the integration of distributed data in a completely secured way. The
paper presents how we are currently exploring how to integrate the existing
data sources towards a global surveillance network for molecular epidemiology.Comment: 7 pages, submitted to Infectious Disorders - Drug Target
- …