MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
Masahito Ohue, Yuri Matsuzaki, Nobuyuki Uchikoga, Takashi Ishida and Yutaka Akiyama
Affiliation: Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure
and function and structure-based drug design. However, the development of an effective method to conduct exhaustive
PPI screening represents a computational challenge. We have been investigating a protein docking approach based on
shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking
software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK
reduces the calculation time required for docking by using several techniques such as a novel scoring function
called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive
PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while
maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset
to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231
was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening
problem with accuracy better than random. When our approach is combined with parallel high-performance computing
systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional
structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock.
Keywords: Interactome, MEGADOCK, Parallel computing, Protein-protein docking, Protein-protein interactions.
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