Large scale deployment of molecular docking application on computational grid infrastructures for combating malaria

PCSVInternational audienceComputational grids are solutions for several biological applications like virtual screening or molecular dynamics where large amounts of computing power and storage are required. The WISDOM project successfully deployed virtual screening at large scale on EGEE grid infrastructures in the summer 2005 and achieved 46 million dockings in 45 days, which is equivalent to 80 CPU years. WISDOM is one good example of a successful deployment of an embarrassingly parallel application. In this paper, we describe the improvements in our deployment. We screened ZINC database against four targets implicated in malaria. During more than 2 months and a half, we have achieved 140 million dockings, representing an average throughput of almost 80,000 dockings per hour. This was made possible by the availability of thousands of CPUs through different infrastructures worldwide. Through the acquired experience, the WISDOM production environment is evolving to enable an easy and fault-tolerant deployment of biological tool

Grid enabled high throughput virtual screening against four different targets implicated in malaria

PCSVInternational audienceAfter having deployed a first data challenge on malaria and a second one on avian flu, respectively in summer 2005 and spring 2006, we are demonstrating here again how efficiently the computational grids can be used to produce massive docking data at a high-throughput. During more than 2 months and a half, we have achieved at least 140 million dockings, representing an average throughput of almost 80,000 dockings per hour. This was made possible by the availability of thousands of CPUs through different infrastructures worldwide. Through the acquired experience, the WISDOM production environment is evolving to enable an easy and fault-tolerant deployment of biological tools; in this case it is the FlexX commercial docking software which is used to dock the whole ZINC database against 4 different targets

Les grilles pour le développement médical

PCSV, présenté par V. Breton, à paraître dans les Comptes-Rendu de la ConférenceLe développement récent des sciences et technologies de l'information et de la communication permet aujourd'hui la création de véritables infrastructures pour le calcul et le stockage de données hétérogènes à l'échelle régionale, nationale et internationale. Ces infrastructures, appelées grilles informatiques, permettront bientôt d'utiliser les ressources informatiques mutualisées avec autant de facilité que nous utilisons aujourd'hui l'électricité. L'utilisation des grilles afin d'accélérer la découverte de médicaments est une voie très prometteuse pour l'avenir. Par cette approche in silico, le nombre de molécules ainsi que la vitesse de test peuvent être grandement augmentés induisant un coût moindre de développement de médicaments. Du 11 Juillet au 31 Août 2005, l'expérience WISDOM (Wide In Silico Docking On Malaria) a permis de tester rien moins qu'un million de ligands (médicaments potentiels) pour le traitement du paludisme: 1700 ordinateurs à travers le monde ont ainsi été associés à cette démarche permettant de réaliser en un mois ce qui aurait nécessité 80 ans sur un ordinateur classique. L'analyse des résultats est en cours. Par cette approche, on peut souhaiter également que les maladies orphelines puissent bénéficier d'un intérêt nouveau de la part des industries pharmaceutiques, à travers notamment la baisse du coût de développement d'un médicament, principal obstacle actuellement à leur mobilisation

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

Demonstration of In Silico docking at a large scale on grid infrastructure

présenté par N. Jac

Grid enabled virtual screening against malaria

34 pages, 5 figures, 3 tables, to appear in Journal of Grid Computing - PCSV, à paraître dans Journal of Grid ComputingWISDOM is an international initiative to enable a virtual screening pipeline on a grid infrastructure. Its first attempt was to deploy large scale in silico docking on a public grid infrastructure. Protein-ligand docking is about computing the binding energy of a protein target to a library of potential drugs using a scoring algorithm. Previous deployments were either limited to one cluster, to grids of clusters in the tightly protected environment of a pharmaceutical laboratory or to pervasive grids. The first large scale docking experiment ran on the EGEE grid production service from 11 July 2005 to 19 August 2005 against targets relevant to research on malaria and saw over 41 million compounds docked for the equivalent of 80 years of CPU time. Up to 1,700 computers were simultaneously used in 15 countries around the world. Issues related to the deployment and the monitoring of the in silico docking experiment as well as experience with grid operation and services are reported in the paper. The main problem encountered for such a large scale deployment was the grid infrastructure stability. Although the overall success rate was above 80%, a lot of monitoring and supervision was still required at the application level to resubmit the jobs that failed. But the experiment demonstrated how grid infrastructures have a tremendous capacity to mobilize very large CPU resources for well targeted goals during a significant period of time. This success leads to a second computing challenge targeting Avian Flu neuraminidase N1

HOPE, an open platform for medical data management on the grid

International audienc

Virtual Screening on Large Scale Grids

PCSV, article in press in Parallel ComputingLarge scale grids 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 virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids 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

Trends in life science grid: from computing grid to knowledge grid

BACKGROUND: Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. RESULTS: This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. CONCLUSION: Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community