Parallel algorithm for discovering and comparing three-dimensional proteins patterns

Identifying conserved (similar) three-dimensional patterns among a set of proteins can be helpful for the rational design of polypharmacological drugs. Some available tools allow this identification from a limited perspective, only considering the available information, such as known binding sites o...

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Autores: Valdés Jiménez, Alejandro Mauricio, Reyes Parada, Miguel, Núñez Vivanco, Gabriel, Jiménez González, Daniel|||0000-0001-6064-7883
Formato: artículo
Fecha de publicación:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/407741
Acesso em linha:https://hdl.handle.net/2117/407741
https://dx.doi.org/10.1109/TCBB.2024.3367789
Access Level:acceso abierto
Palavra-chave:Proteins -- Structure
Three-dimensional display systems
Three-dimensional patterns discovering
Parallel and distributed programming
OpenMP
MPI
CUDA
Proteïnes -- Estructura
Visualització tridimensional (Informàtica)
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
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spelling Parallel algorithm for discovering and comparing three-dimensional proteins patternsValdés Jiménez, Alejandro MauricioReyes Parada, MiguelNúñez Vivanco, GabrielJiménez González, Daniel|||0000-0001-6064-7883Proteins -- StructureThree-dimensional display systemsThree-dimensional patterns discoveringParallel and distributed programmingOpenMPMPICUDAProteïnes -- EstructuraVisualització tridimensional (Informàtica)Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::BioinformàticaIdentifying conserved (similar) three-dimensional patterns among a set of proteins can be helpful for the rational design of polypharmacological drugs. Some available tools allow this identification from a limited perspective, only considering the available information, such as known binding sites or previously annotated structural motifs. Thus, these approaches do not look for similarities among all putative orthosteric and or allosteric bindings sites between protein structures. To overcome this tech-weakness Geomfinder was developed, an algorithm for the estimation of similarities between all pairs of three-dimensional amino acids patterns detected in any two given protein structures, which works without information about their known patterns. Even though Geomfinder is a functional alternative to compare small structural proteins, it is computationally unfeasible for the case of large protein processing and the algorithm needs to improve its performance. This work presents several parallel versions of the Geomfinder to exploit SMPs, distributed memory systems, hybrid version of SMP and distributed memory systems, and GPU based systems. Results show significant improvements in performance as compared to the original version and achieve up to 24.5x speedup when analyzing proteins of average size and up to 95.4x in larger proteinsThis research was funded by DICYT-USACH grant 5392102RP-AC and the Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) grants 1191133 and 1170662 and from Spanish Government (projects SEV2015-0493 and TIN2015-65316-P, grant BES-2016-078046), and from Generalitat de Catalunya (contracts 2017-SGR1414 and 2017-SGR-1328). The web-server is hosted in the cluster obtained with the grant CONICYT-FONDEQUIPEQM160063.Peer ReviewedInstitute of Electrical and Electronics Engineers (IEEE)20242024-05-0120242024-05-09journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/407741https://dx.doi.org/10.1109/TCBB.2024.3367789reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 TIN2015-65316-P COMPUTACION DE ALTAS PRESTACIONES VIIopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4077412026-05-27T15:37:01Z
dc.title.none.fl_str_mv Parallel algorithm for discovering and comparing three-dimensional proteins patterns
title Parallel algorithm for discovering and comparing three-dimensional proteins patterns
spellingShingle Parallel algorithm for discovering and comparing three-dimensional proteins patterns
Valdés Jiménez, Alejandro Mauricio
Proteins -- Structure
Three-dimensional display systems
Three-dimensional patterns discovering
Parallel and distributed programming
OpenMP
MPI
CUDA
Proteïnes -- Estructura
Visualització tridimensional (Informàtica)
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
title_short Parallel algorithm for discovering and comparing three-dimensional proteins patterns
title_full Parallel algorithm for discovering and comparing three-dimensional proteins patterns
title_fullStr Parallel algorithm for discovering and comparing three-dimensional proteins patterns
title_full_unstemmed Parallel algorithm for discovering and comparing three-dimensional proteins patterns
title_sort Parallel algorithm for discovering and comparing three-dimensional proteins patterns
dc.creator.none.fl_str_mv Valdés Jiménez, Alejandro Mauricio
Reyes Parada, Miguel
Núñez Vivanco, Gabriel
Jiménez González, Daniel|||0000-0001-6064-7883
author Valdés Jiménez, Alejandro Mauricio
author_facet Valdés Jiménez, Alejandro Mauricio
Reyes Parada, Miguel
Núñez Vivanco, Gabriel
Jiménez González, Daniel|||0000-0001-6064-7883
author_role author
author2 Reyes Parada, Miguel
Núñez Vivanco, Gabriel
Jiménez González, Daniel|||0000-0001-6064-7883
author2_role author
author
author
dc.subject.none.fl_str_mv Proteins -- Structure
Three-dimensional display systems
Three-dimensional patterns discovering
Parallel and distributed programming
OpenMP
MPI
CUDA
Proteïnes -- Estructura
Visualització tridimensional (Informàtica)
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
topic Proteins -- Structure
Three-dimensional display systems
Three-dimensional patterns discovering
Parallel and distributed programming
OpenMP
MPI
CUDA
Proteïnes -- Estructura
Visualització tridimensional (Informàtica)
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
description Identifying conserved (similar) three-dimensional patterns among a set of proteins can be helpful for the rational design of polypharmacological drugs. Some available tools allow this identification from a limited perspective, only considering the available information, such as known binding sites or previously annotated structural motifs. Thus, these approaches do not look for similarities among all putative orthosteric and or allosteric bindings sites between protein structures. To overcome this tech-weakness Geomfinder was developed, an algorithm for the estimation of similarities between all pairs of three-dimensional amino acids patterns detected in any two given protein structures, which works without information about their known patterns. Even though Geomfinder is a functional alternative to compare small structural proteins, it is computationally unfeasible for the case of large protein processing and the algorithm needs to improve its performance. This work presents several parallel versions of the Geomfinder to exploit SMPs, distributed memory systems, hybrid version of SMP and distributed memory systems, and GPU based systems. Results show significant improvements in performance as compared to the original version and achieve up to 24.5x speedup when analyzing proteins of average size and up to 95.4x in larger proteins
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-05-01
2024
2024-05-09
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/407741
https://dx.doi.org/10.1109/TCBB.2024.3367789
url https://hdl.handle.net/2117/407741
https://dx.doi.org/10.1109/TCBB.2024.3367789
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 TIN2015-65316-P COMPUTACION DE ALTAS PRESTACIONES VII
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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