Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) [1], the second data challenge battling avian flu was 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 six-week-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 worldwide 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.
Grid-enabled high-throughput in silico screening against influenza a neuraminidase
Merelli Ivan;Milanesi Luciano;
2006
Abstract
Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) [1], the second data challenge battling avian flu was 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 six-week-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 worldwide 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
