120
Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery Poster Session II
67-POS
Board 20
The MEGADOCK Project: High-Performance Protein-Protein Interaction Prediction
Tools on Supercomputing Environments
Masahito Ohue
1,2
, Takehiro Shimoda
1
, Yuri Matsuzaki
3
, Nobuyuki Uchikoga
4
, Takashi Ishida
1
,
Yutaka Akiyama
1,2
.
1
Tokyo Institute of Technology, Tokyo, Japan,
3
Tokyo Institute of Technology, Tokyo, Japan,
2
Japan Society for the Promotion Science, Tokyo, Japan,
4
Chuo University, Tokyo, Japan.
Background
Protein-protein interaction (PPI) plays a core role in cellular functions. In recent years, PPI
prediction methods based on protein docking have been developed and have been applied for
large-scale PPI network prediction based on tertiary structures. However, such network
prediction requires much computing resources, and a faster PPI prediction method is eagerly
demanded.
Results
We have developed a high throughput PPI prediction system based on rigid-body protein
docking, “MEGADOCK”. MEGADOCK can perform faster docking based on its original
scoring function. Recently, MEGADOCK has been accelerated by using the general purpose
graphics processing unit (GPGPU) technique and it is now released as MEGADOCK-GPU.
MEGADOCK was also parallelized for massively parallel supercomputing environment using
the hybrid parallelization (MPI/OpenMP) technique. The system, named MEGADOCK-K,
achieved an excellent scalability on supercomputing environments, such as K computer, which
has 705,024 Fujitsu SPARC64 VIIIfx CPU cores. We have already applied MEGADOCK
system to a number of interactome analyses such as bacterial chemotaxis pathway, human
apoptosis pathway and human epidermal growth factor receptor related pathway.
Conclusion
We present a new protein-protein docking engine aimed at exhaustive docking of millions of
protein pairs. The system was shown to be scalable when running on thousands of nodes and
multiple GPUs.
