Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU)
- Autores
- Jenik, Michael; Mocskos, Esteban; Roitberg, Adrián E.; Turjanski, Adrián G.
- Año de publicación
- 2010
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Solving the structure of protein-protein complexes is one of the most important tasks in structural biology. Even though there has been great progress in recent years there still a small number of protein complexes structures deposited in the Protein Data Bank in comparison to isolated partners. In this sense, the computational prediction of protein complexes starting from the unbound structures, protein-protein Docking algorithms, has emerged as a reasonable alternative. Many docking programs employ Fast Fourier Transform (FFT) correlations as an efficient search strategy. We describe an implementation of a protein-protein docking program based on FFT surface complementarity that runs entirely on a Graphics Processing Unit (GPU), including grid generation, rotation and scoring. We evaluate its performance, and show that it can be up to 13 times faster than conventional CPU based implementations.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
GPU
Biología estructural - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/152731
Ver los metadatos del registro completo
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Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU)Jenik, MichaelMocskos, EstebanRoitberg, Adrián E.Turjanski, Adrián G.Ciencias InformáticasGPUBiología estructuralSolving the structure of protein-protein complexes is one of the most important tasks in structural biology. Even though there has been great progress in recent years there still a small number of protein complexes structures deposited in the Protein Data Bank in comparison to isolated partners. In this sense, the computational prediction of protein complexes starting from the unbound structures, protein-protein Docking algorithms, has emerged as a reasonable alternative. Many docking programs employ Fast Fourier Transform (FFT) correlations as an efficient search strategy. We describe an implementation of a protein-protein docking program based on FFT surface complementarity that runs entirely on a Graphics Processing Unit (GPU), including grid generation, rotation and scoring. We evaluate its performance, and show that it can be up to 13 times faster than conventional CPU based implementations.Sociedad Argentina de Informática e Investigación Operativa2010info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf3313-3324http://sedici.unlp.edu.ar/handle/10915/152731enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-12.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-9326info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:39:27Zoai:sedici.unlp.edu.ar:10915/152731Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:39:27.261SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
title |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
spellingShingle |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) Jenik, Michael Ciencias Informáticas GPU Biología estructural |
title_short |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
title_full |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
title_fullStr |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
title_full_unstemmed |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
title_sort |
Accelerating Protein-Protein Docking using a Graphics Processing Unit (GPU) |
dc.creator.none.fl_str_mv |
Jenik, Michael Mocskos, Esteban Roitberg, Adrián E. Turjanski, Adrián G. |
author |
Jenik, Michael |
author_facet |
Jenik, Michael Mocskos, Esteban Roitberg, Adrián E. Turjanski, Adrián G. |
author_role |
author |
author2 |
Mocskos, Esteban Roitberg, Adrián E. Turjanski, Adrián G. |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas GPU Biología estructural |
topic |
Ciencias Informáticas GPU Biología estructural |
dc.description.none.fl_txt_mv |
Solving the structure of protein-protein complexes is one of the most important tasks in structural biology. Even though there has been great progress in recent years there still a small number of protein complexes structures deposited in the Protein Data Bank in comparison to isolated partners. In this sense, the computational prediction of protein complexes starting from the unbound structures, protein-protein Docking algorithms, has emerged as a reasonable alternative. Many docking programs employ Fast Fourier Transform (FFT) correlations as an efficient search strategy. We describe an implementation of a protein-protein docking program based on FFT surface complementarity that runs entirely on a Graphics Processing Unit (GPU), including grid generation, rotation and scoring. We evaluate its performance, and show that it can be up to 13 times faster than conventional CPU based implementations. Sociedad Argentina de Informática e Investigación Operativa |
description |
Solving the structure of protein-protein complexes is one of the most important tasks in structural biology. Even though there has been great progress in recent years there still a small number of protein complexes structures deposited in the Protein Data Bank in comparison to isolated partners. In this sense, the computational prediction of protein complexes starting from the unbound structures, protein-protein Docking algorithms, has emerged as a reasonable alternative. Many docking programs employ Fast Fourier Transform (FFT) correlations as an efficient search strategy. We describe an implementation of a protein-protein docking program based on FFT surface complementarity that runs entirely on a Graphics Processing Unit (GPU), including grid generation, rotation and scoring. We evaluate its performance, and show that it can be up to 13 times faster than conventional CPU based implementations. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/152731 |
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dc.language.none.fl_str_mv |
eng |
language |
eng |
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dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 3313-3324 |
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