Building a Chemical-Protein Interactome on the Open Science Grid. Quick, R., Hayashi, S., Meroueh, S., Rynge, M., Teige, S., Wang, B., Xu, D., Sinica, A., & Taipei, T. In International Symposium on Grids and Clouds (ISGC), pages 15-20, 2015. Website doi abstract bibtex The Structural Protein-Ligand Interactome (SPLINTER) project predicts the interaction of thousands of small molecules with thousands of proteins. These interactions are predicted using the three-dimensional structure of the bound complex between each pair of protein and compound that is predicted by molecular docking. These docking runs consist of millions of individual short jobs each lasting only minutes. However, computing resources to execute these jobs (which cumulatively take tens of millions of CPU hours) are not readily or easily available in a cost effective manner. By looking to National Cyberinfrastructure resources, and specifically the Open Science Grid (OSG), we have been able to harness CPU power for researchers at the Indiana University School of Medicine to provide a quick and efficient solution to their unmet computing needs. Using the job submission infrastructure provided by the OSG, the docking data and simulation executable was sent to more than 100 universities and research centers worldwide. These op-portunistic resources provided millions of CPU hours in a matter of days, greatly reducing time docking simulation time for the research group. The overall impact of this approach allows researchers to identify small molecule candidates for individual proteins, or new protein targets for existing FDA-approved drugs and biologically active compounds.
@inproceedings{
title = {Building a Chemical-Protein Interactome on the Open Science Grid},
type = {inproceedings},
year = {2015},
pages = {15-20},
websites = {https://scitech.isi.edu/wordpress/wp-content/papercite-data/pdf/osg-splinter-2015.pdf},
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abstract = {The Structural Protein-Ligand Interactome (SPLINTER) project predicts the interaction of thousands of small molecules with thousands of proteins. These interactions are predicted using the three-dimensional structure of the bound complex between each pair of protein and compound that is predicted by molecular docking. These docking runs consist of millions of individual short jobs each lasting only minutes. However, computing resources to execute these jobs (which cumulatively take tens of millions of CPU hours) are not readily or easily available in a cost effective manner. By looking to National Cyberinfrastructure resources, and specifically the Open Science Grid (OSG), we have been able to harness CPU power for researchers at the Indiana University School of Medicine to provide a quick and efficient solution to their unmet computing needs. Using the job submission infrastructure provided by the OSG, the docking data and simulation executable was sent to more than 100 universities and research centers worldwide. These op-portunistic resources provided millions of CPU hours in a matter of days, greatly reducing time docking simulation time for the research group. The overall impact of this approach allows researchers to identify small molecule candidates for individual proteins, or new protein targets for existing FDA-approved drugs and biologically active compounds.},
bibtype = {inproceedings},
author = {Quick, Rob and Hayashi, Soichi and Meroueh, Samy and Rynge, Mats and Teige, Scott and Wang, Bo and Xu, David and Sinica, Academia and Taipei, Taiwan},
doi = {https://doi.org/10.22323/1.239.0024},
booktitle = {International Symposium on Grids and Clouds (ISGC)}
}
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