Progress towards Automated Kepler Scientific Workflows for Computer-aided Drug Discovery and Molecular Simulations
dc.contributor.author | Ieong, Pek U. | |
dc.contributor.author | Sørensen, Jesper | |
dc.contributor.author | Vemu, Prasantha L. | |
dc.contributor.author | Wong, Celia W. | |
dc.contributor.author | Demir, Özlem | |
dc.contributor.author | Williams, Nadya P. | |
dc.contributor.author | Wang, Jianwu | |
dc.contributor.author | Crawl, Daniel | |
dc.contributor.author | Swift, Robert V. | |
dc.contributor.author | Malmstrom, Robert D. | |
dc.contributor.author | Altintas, Ilkay | |
dc.contributor.author | Amaro, Rommie E. | |
dc.date.accessioned | 2024-02-12T19:46:56Z | |
dc.date.available | 2024-02-12T19:46:56Z | |
dc.date.issued | 2014-06-06 | |
dc.description.abstract | We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computation Resource (NBCR). The main workflow components include: file-management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission, serial and parallel execution, and monitoring on relevant high-performance computing (HPC) resources, receptor structural clustering, virtual screening (VS), and statistical analyses of the VS results. The workflows aim to standardize simulation and analysis and promote best practices within the molecular simulation and CADD communities. Each component is developed as a stand-alone workflow, which should allow for easy integration into larger frameworks built suiting user needs, while remaining intuitive and easy to extend. | |
dc.description.sponsorship | The authors would like to thank Leah Krause for fruitful discussions regarding the development of the workflows. This work is funded in part by a grant from the NVIDIA Foundation, an NIH New Innovator Award to REA OD-007237. Funding and support from the National Biomedical Computation Resource is provided through NIH P41 GM103426. bioKepler is funded by the National Science Foundation (NSF) DBI-1062565 under CI Reuse and Advances in Bioinformatics programs supported some of the IA, DC, and JW. The Alfred Benzon Foundation is thanked for postdoctoral funding to JS. This work used the Extreme Science and Engineering Discovery Environment (XSEDE) at San Diego Supercomputer Center (SDSC) and Texas Advanced Computing Center (TACC) using an allocation to REA with grant number TG-CHE060073N. XSEDE is supported by NSF grant number OCI-1053575. | |
dc.description.uri | https://www.sciencedirect.com/science/article/pii/S1877050914003366 | |
dc.format.extent | 11 pages | |
dc.genre | journal articles | |
dc.identifier.citation | Ieong, Pek U., Jesper Sørensen, Prasantha L. Vemu, Celia W. Wong, Özlem Demir, Nadya P. Williams, Jianwu Wang, et al. “Progress towards Automated Kepler Scientific Workflows for Computer-Aided Drug Discovery and Molecular Simulations.” Procedia Computer Science, 2014 International Conference on Computational Science, 29 (January 1, 2014): 1745–55. https://doi.org/10.1016/j.procs.2014.05.159. | |
dc.identifier.uri | https://doi.org/10.1016/j.procs.2014.05.159 | |
dc.identifier.uri | http://hdl.handle.net/11603/31601 | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Information Systems Department Collection | |
dc.relation.ispartof | UMBC Center for Accelerated Real Time Analysis | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
dc.relation.ispartof | UMBC Data Science | |
dc.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
dc.relation.ispartof | UMBC Center for Real-time Distributed Sensing and Autonomy | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0 DEED) | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | |
dc.subject | UMBC Big Data Analytics Lab | |
dc.title | Progress towards Automated Kepler Scientific Workflows for Computer-aided Drug Discovery and Molecular Simulations | |
dc.type | Text | |
dcterms.creator | https://orcid.org/0000-0002-9933-1170 |