title: Performance studies on distributed virtual screening.
abstract: Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly.
authors.affiliation: Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
authors.forename: Jens
authors.initials: J
authors.lastname: Krüger
authors.affiliation: Technische Universität Dresden, Zellescher Weg 12-14, 01069 Dresden, Germany.
authors.forename: Richard
authors.identifier: 0000-0002-1255-5498
authors.initials: R
authors.lastname: Grunzke
authors.affiliation: Ludwig-Maximilians-Universität München, Butenandtstr aße 5-13, 81377 München, Germany.
authors.forename: Sonja
authors.identifier: 0000-0002-4354-4353
authors.initials: S
authors.lastname: Herres-Pawlis
authors.affiliation: Ludwig-Maximilians-Universität München, Butenandtstr aße 5-13, 81377 München, Germany.
authors.forename: Alexander
authors.identifier: 0000-0002-9647-8839
authors.initials: A
authors.lastname: Hoffmann
authors.affiliation: Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
authors.forename: Luis
authors.initials: L
authors.lastname: de la Garza
authors.affiliation: Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher
authors.affiliation: Technische Universität Dresden, Zellescher Weg 12-14, 01069 Dresden, Germany.
authors.forename: Wolfgang E
authors.initials: WE
authors.lastname: Nagel
authors.affiliation: Center for Research Computing, University of Notre Dame, P.O. Box 539, Notre Dame, IN 46556, USA.
authors.forename: Sandra
authors.identifier: 0000-0002-6051-0673
authors.initials: S
authors.lastname: Gesing
mesh_terms: D030562:Databases, Protein; D055808:Drug Discovery / Q000379:methods*; D062105:Molecular Docking Simulation / Q000379:methods*; D047428:Protein Kinase Inhibitors / Q000737:chemistry*; D011494:Protein Kinases / Q000737:chemistry*
chemical_list: D047428:Protein Kinase Inhibitors; D011494:Protein Kinases