Matsuzaki Yuri, Uchikoga Nobuyuki, Ohue Masahito, Shimoda Takehiro, Sato Toshiyuki, Ishida Takashi, Akiyama Yutaka
Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
Source Code Biol Med. 2013 Sep 3;8(1):18. doi: 10.1186/1751-0473-8-18.
Protein-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.
We 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.
We 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/.
蛋白质-蛋白质相互作用(PPI)在细胞功能中起着核心作用。在过去几年中,大规模并行超级计算系统得到了积极发展,这使得大规模生物学问题得以解决,例如基于三级结构的PPI网络预测。
我们通过采用混合并行化(MPI/OpenMP)技术,开发了一种基于刚性对接的高通量超快速PPI预测系统“MEGADOCK”,该技术适用于大规模并行超级计算系统。MEGADOCK在刚体对接过程中显示出显著更快的处理速度,这使得蛋白质三级结构数据能够充分用于系统生物学中的大规模和网络级问题。此外,如在两个超级计算环境中进行的测量所示,该系统具有可扩展性。然后,我们使用对接后分析对生物PPI网络进行了预测。
我们提出了一种新的蛋白质-蛋白质对接引擎,旨在对数百万对蛋白质进行详尽对接。该系统通过在数千个节点上运行显示出可扩展性。软件包可在以下网址获取:http://www.bi.cs.titech.ac.jp/megadock/k/ 。