Large Scale In Silico Screening on Grid Infrastructures
N. Jacq (LPC-Clermont), V. Breton (LPC-Clermont), H.-Y. Chen, L.-Y., Ho, M. Hofmann, H.-C. Lee, Y. Legr\'e (LPC-Clermont), S.-C. Lin, A. Maass, E., Medernach, I. Merelli, L. Milanesi, G. Rastelli, M. Reichstadt, (LPC-Clermont), J. Salzemann (LPC-Clermont), H. Schwichtenberg

TL;DR
This paper demonstrates the successful deployment of large-scale in silico drug screening on grid infrastructures, highlighting their effectiveness and performance in virtual screening for neglected diseases like Malaria and Avian Flu.
Contribution
It showcases the first large-scale in silico docking campaigns on grid infrastructures, evaluating their performance and addressing deployment challenges.
Findings
Achieved about 105 years of CPU time on grid infrastructures.
Validated the feasibility of large-scale virtual screening on distributed systems.
Identified specific issues in deploying large-scale docking on grids.
Abstract
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.
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Taxonomy
TopicsGenetics, Bioinformatics, and Biomedical Research · Bioinformatics and Genomic Networks · Genomics and Phylogenetic Studies
