Grid-enabled High-throughput in silico Screening against Influenza A Neuraminidase

• Published in: IEEE Transactions on Nanobioscience
• Main Authors: Lee, H.-C., Salzemann, J., Jacq, N., Chen, H.-Y., Ho, Li-Yung, Merelli, I., Milanesi, L., Breton, Vincent, C. Lin, S., Wu, Y.-T.
• Other Authors: Genomics Research Center (GENOMICS RESEARCH CENTER), Academia Sinica, Laboratoire de Physique Corpusculaire - Clermont-Ferrand (LPC), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institute for Biomedical Technologies (ITB), National Research Council of Italy
• Format: Article in Journal/Newspaper
• Language: English
• Published: CCSD 2006
• Subjects: data challenge; EGEE; BioinfoGRID; grid infrastructure; virtual screening; drug discovery; avian flu; neuraminidase; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; [INFO.INFO-DC]Computer Science [cs]/Distributed; Parallel; and Cluster Computing [cs.DC]; Avian flu
• Online Access: https://in2p3.hal.science/in2p3-00114129; https://in2p3.hal.science/in2p3-00114129v1/document; https://in2p3.hal.science/in2p3-00114129v1/file/IEEE_Transaction.pdf; https://doi.org/10.1109/TNB.2006.887943

8 pages,6 figures, to appear in IEEE Transactions on Nanobioscience. - PCSV, à paraître dans IEEE Transactions on Nanobioscience (2006). This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) [1], the second data challenge battling avian flu kicked off in April 2006 to identify new drugs for the potential variants of the Influenza A virus. Mobilizing thousands of CPUs on the Grid, the 6-weeks long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 Gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a world-wide Grid infrastructure to efficiently deploy large scale virtual screening [2] to speed up the drug design process. Lessons learned through the data challenge activity are also discussed.