Cargando…

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

BACKGROUND: 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 structure...

Descripción completa

Detalles Bibliográficos
Autores principales: Matsuzaki, Yuri, Uchikoga, Nobuyuki, Ohue, Masahito, Shimoda, Takehiro, Sato, Toshiyuki, Ishida, Takashi, Akiyama, Yutaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3847482/
https://www.ncbi.nlm.nih.gov/pubmed/24004986
http://dx.doi.org/10.1186/1751-0473-8-18
_version_ 1782293609980100608
author Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ohue, Masahito
Shimoda, Takehiro
Sato, Toshiyuki
Ishida, Takashi
Akiyama, Yutaka
author_facet Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ohue, Masahito
Shimoda, Takehiro
Sato, Toshiyuki
Ishida, Takashi
Akiyama, Yutaka
author_sort Matsuzaki, Yuri
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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/.
format Online
Article
Text
id pubmed-3847482
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-38474822013-12-07 MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments Matsuzaki, Yuri Uchikoga, Nobuyuki Ohue, Masahito Shimoda, Takehiro Sato, Toshiyuki Ishida, Takashi Akiyama, Yutaka Source Code Biol Med Software Review BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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/. BioMed Central 2013-09-03 /pmc/articles/PMC3847482/ /pubmed/24004986 http://dx.doi.org/10.1186/1751-0473-8-18 Text en Copyright © 2013 Matsuzaki et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Review
Matsuzaki, Yuri
Uchikoga, Nobuyuki
Ohue, Masahito
Shimoda, Takehiro
Sato, Toshiyuki
Ishida, Takashi
Akiyama, Yutaka
MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title_full MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title_fullStr MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title_full_unstemmed MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title_short MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
title_sort megadock 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments
topic Software Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3847482/
https://www.ncbi.nlm.nih.gov/pubmed/24004986
http://dx.doi.org/10.1186/1751-0473-8-18
work_keys_str_mv AT matsuzakiyuri megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT uchikoganobuyuki megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT ohuemasahito megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT shimodatakehiro megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT satotoshiyuki megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT ishidatakashi megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments
AT akiyamayutaka megadock30ahighperformanceproteinproteininteractionpredictionsoftwareusinghybridparallelcomputingforpetascalesupercomputingenvironments