| Institution: | 1.Graduate School of Information Science and Engineering,Tokyo Institute of Technology,Meguro-ku,Japan;2.Department of Physics,Chuo University,Bunkyo-ku,Japan;3.Grand Challenge Applications Project for Life Sciences, Next-Generation Integrated Simulation of Living Matter, Computational Science Research Program,Riken,Wako,Japan;4.Education Academy of Computational Life Sciences,Tokyo Institute of Technology,Meguro-ku,Japan;5.Research Fellow of the Japan Society for the Promotion of Science,Chiyoda-ku,Japan;6.Mizuho Information & Research Institute,Inc.,Chiyoda-ku,Japan |
| Abstract: | BackgroundProtein-protein interaction (PPI) plays a core role in cellular functions. Massively parallel supercomputing systems have been actively developed over the past few years, which enable large-scale biological problems to be solved, such as PPI network prediction based on tertiary structures.ResultsWe have developed a high throughput and ultra-fast PPI prediction system based on rigid docking, “MEGADOCK”, by employing a hybrid parallelization (MPI/OpenMP) technique assuming usages on massively parallel supercomputing systems. MEGADOCK displays significantly faster processing speed in the rigid-body docking process that leads to full utilization of protein tertiary structural data for large-scale and network-level problems in systems biology. Moreover, the system was scalable as shown by measurements carried out on two supercomputing environments. We then conducted prediction of biological PPI networks using the post-docking analysis.ConclusionsWe present a new protein-protein docking engine aimed at exhaustive docking of mega-order numbers of protein pairs. The system was shown to be scalable by running on thousands of nodes. The software package is available at: http://www.bi.cs.titech.ac.jp/megadock/k/. |
