HYPERDOCK: Improving virtual screening through parallel hyperheuristics

Virtual screening (VS) methods aid clinical research by predicting the interaction of ligands with pharmacological targets. The computational requirements of VS, along with the size of the databases, propitiate the use of high performance computing. METADOCK is a tool for the application of metaheur...

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Detalles Bibliográficos
Autores: Imbernón Tudela, Baldomero, Llanes, Antonio, Cutillas Lozano, José María, Giménez, Domingo
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universidad Católica San Antonio de Murcia (UCAM)
Repositorio:RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murcia
OAI Identifier:oai:repositorio.ucam.edu:10952/8811
Acceso en línea:http://hdl.handle.net/10952/8811
Access Level:acceso abierto
Palabra clave:Virtual screening
Molecular docking
HPC
Metaheuristics
Hyperheuristics
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spelling HYPERDOCK: Improving virtual screening through parallel hyperheuristicsImbernón Tudela, BaldomeroLlanes, AntonioCutillas Lozano, José MaríaGiménez, DomingoVirtual screeningMolecular dockingHPCMetaheuristicsHyperheuristicsVirtual screening (VS) methods aid clinical research by predicting the interaction of ligands with pharmacological targets. The computational requirements of VS, along with the size of the databases, propitiate the use of high performance computing. METADOCK is a tool for the application of metaheuristics to VS in heterogeneous clusters of computers based on central processing unit (CPU) and graphics processing unit (GPU). HYPERDOCK represents a step forward; the exploration for satisfactory metaheuristics is systematically approached by means of hyperheuristics working on top of the metaheuristic schema of METADOCK. Multiple metaheuristics are explored, so the process is computationally demanding. HYPERDOCK exploits the parallelism of METADOCK and includes parallelism at its own level. The different levels of parallelism can be used to exploit the parallelism offered by computational systems composed of multicore CPU þ multi-GPUs. The efficient exploitation of these systems enables HYPERDOCK to improve ligand–receptor binding.Ingeniería, Industria y ConstrucciónEscuela Politécnica2019info:eu-repo/semantics/articlehttp://hdl.handle.net/10952/8811reponame:RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murciainstname:Universidad Católica San Antonio de Murcia (UCAM)Inglésinfo:eu-repo/semantics/openAccessoai:repositorio.ucam.edu:10952/88112026-06-07T18:35:21Z
dc.title.none.fl_str_mv HYPERDOCK: Improving virtual screening through parallel hyperheuristics
title HYPERDOCK: Improving virtual screening through parallel hyperheuristics
spellingShingle HYPERDOCK: Improving virtual screening through parallel hyperheuristics
Imbernón Tudela, Baldomero
Virtual screening
Molecular docking
HPC
Metaheuristics
Hyperheuristics
title_short HYPERDOCK: Improving virtual screening through parallel hyperheuristics
title_full HYPERDOCK: Improving virtual screening through parallel hyperheuristics
title_fullStr HYPERDOCK: Improving virtual screening through parallel hyperheuristics
title_full_unstemmed HYPERDOCK: Improving virtual screening through parallel hyperheuristics
title_sort HYPERDOCK: Improving virtual screening through parallel hyperheuristics
dc.creator.none.fl_str_mv Imbernón Tudela, Baldomero
Llanes, Antonio
Cutillas Lozano, José María
Giménez, Domingo
author Imbernón Tudela, Baldomero
author_facet Imbernón Tudela, Baldomero
Llanes, Antonio
Cutillas Lozano, José María
Giménez, Domingo
author_role author
author2 Llanes, Antonio
Cutillas Lozano, José María
Giménez, Domingo
author2_role author
author
author
dc.subject.none.fl_str_mv Virtual screening
Molecular docking
HPC
Metaheuristics
Hyperheuristics
topic Virtual screening
Molecular docking
HPC
Metaheuristics
Hyperheuristics
description Virtual screening (VS) methods aid clinical research by predicting the interaction of ligands with pharmacological targets. The computational requirements of VS, along with the size of the databases, propitiate the use of high performance computing. METADOCK is a tool for the application of metaheuristics to VS in heterogeneous clusters of computers based on central processing unit (CPU) and graphics processing unit (GPU). HYPERDOCK represents a step forward; the exploration for satisfactory metaheuristics is systematically approached by means of hyperheuristics working on top of the metaheuristic schema of METADOCK. Multiple metaheuristics are explored, so the process is computationally demanding. HYPERDOCK exploits the parallelism of METADOCK and includes parallelism at its own level. The different levels of parallelism can be used to exploit the parallelism offered by computational systems composed of multicore CPU þ multi-GPUs. The efficient exploitation of these systems enables HYPERDOCK to improve ligand–receptor binding.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10952/8811
url http://hdl.handle.net/10952/8811
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murcia
instname:Universidad Católica San Antonio de Murcia (UCAM)
instname_str Universidad Católica San Antonio de Murcia (UCAM)
reponame_str RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murcia
collection RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murcia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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