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MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for

Yuri Matsuzaki¹, Nobuyuki Uchikoga, Masahito Ohue

¹Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan. y_matsuzaki@bi.cs.titech.ac.jp.

Source Code for Biology and Medicine

|September 6, 2013

Summary

MEGADOCK is a novel, high-throughput protein-protein interaction (PPI) prediction system. This ultra-fast engine leverages massively parallel supercomputing for efficient large-scale biological network analysis.

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Area of Science:

Computational Biology
Systems Biology
Bioinformatics

Background:

Protein-protein interactions (PPIs) are fundamental to cellular processes.
Advancements in supercomputing enable tackling large-scale biological challenges like PPI network prediction.

Purpose of the Study:

To develop a high-throughput and ultra-fast protein-protein interaction prediction system.
To utilize massively parallel supercomputing for large-scale biological network analysis.

Main Methods:

Developed MEGADOCK, a protein-protein docking engine.
Employed hybrid parallelization (MPI/OpenMP) for supercomputing environments.
Utilized rigid docking based on tertiary protein structures.

Main Results:

MEGADOCK achieves significantly faster processing speeds for rigid-body docking.
The system effectively utilizes protein tertiary structural data for network-level problems.
Demonstrated scalability on supercomputing environments and conducted PPI network predictions.

Conclusions:

Introduced a new protein-protein docking engine for exhaustive docking of mega-order protein pairs.
The MEGADOCK system is scalable, demonstrated by performance on thousands of nodes.
The MEGADOCK software package is publicly available for research use.