MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

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 investi...

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Main Authors: Ohue, Masahito, Matsuzaki, Yuri, Uchikoga, Nobuyuki, Ishida, Takashi, Akiyama, Yutaka
Format: Online
Language:English
Published: Bentham Science Publishers 2014
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4443796/
id pubmed-4443796
recordtype oai_dc
spelling pubmed-44437962015-05-28 MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data Ohue, Masahito Matsuzaki, Yuri Uchikoga, Nobuyuki Ishida, Takashi Akiyama, Yutaka Article 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. Bentham Science Publishers 2014-08 2014-08 /pmc/articles/PMC4443796/ /pubmed/23855673 http://dx.doi.org/10.2174/09298665113209990050 Text en © 2014 Bentham Science Publishers http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Ohue, Masahito
Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ishida, Takashi
Akiyama, Yutaka
spellingShingle Ohue, Masahito
Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ishida, Takashi
Akiyama, Yutaka
MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
author_facet Ohue, Masahito
Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ishida, Takashi
Akiyama, Yutaka
author_sort Ohue, Masahito
title MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
title_short MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
title_full MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
title_fullStr MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
title_full_unstemmed MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data
title_sort megadock: an all-to-all protein-protein interaction prediction system using tertiary structure data
description 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.
publisher Bentham Science Publishers
publishDate 2014
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4443796/
_version_ 1613227626627858432

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