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...
Autores principales: | , , , , , , |
---|---|
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 |