Grid-enabled Virtual Screening Against Malaria

• Published in: Journal of grid computing Vol. 6; no. 1; pp. 29 - 43
• Main Authors: Jacq, N., Salzemann, J., Jacq, F., Legré, Y., Medernach, E., Montagnat, J., Maaß, A., Reichstadt, M., Schwichtenberg, H., Sridhar, M., Kasam, V., Zimmermann, M., Hofmann, M., Breton, V.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.03.2008; Springer Nature B.V; Springer Verlag
• Subjects: Algorithms; Bioinformatics; Computer Science; Distributed, Parallel, and Cluster Computing; Docking; Experiments; Infrastructure; Malaria; Management of Computing and Information Systems; Monitoring; Processor Architectures; Proteins; Screening; User Interfaces and Human Computer Interaction; Data challenge; Malaria; Virtual screening; Grid computing; In silico docking; Drug discovery; Grid infrastructure; grid infrastructure; in silico docking; drug discovery; virtual screening; grid computing; malaria
• ISSN: 1570-7873; 1572-9184
• DOI: 10.1007/s10723-007-9085-5

WISDOM 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 desktop 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.