A genetic algorithm for the ligand-protein docking problem
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Genetics and Molecular Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400022 |
Resumo: | We analyzed the performance of a real coded "steady-state" genetic algorithm (SSGA) using a grid-based methodology in docking five HIV-1 protease-ligand complexes having known three-dimensional structures. All ligands tested are highly flexible, having more than 10 conformational degrees of freedom. The SSGA was tested for the rigid and flexible ligand docking cases. The implemented genetic algorithm was able to dock successfully rigid and flexible ligand molecules, but with a decreasing performance when the number of ligand conformational degrees of freedom increased. The docked lowest-energy structures have root mean square deviation (RMSD) with respect to the corresponding experimental crystallographic structure ranging from 0.037 Å to 0.090 Å in the rigid docking, and 0.420 Å to 1.943 Å in the flexible docking. We found that not only the number of ligand conformational degrees of freedom is an important aspect to the algorithm performance, but also that the more internal dihedral angles are critical. Furthermore, our results showed that the initial population distribution can be relevant for the algorithm performance. |
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Genetics and Molecular Biology |
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A genetic algorithm for the ligand-protein docking problemligand-protein dockingflexible dockinggenetic algorithmsWe analyzed the performance of a real coded "steady-state" genetic algorithm (SSGA) using a grid-based methodology in docking five HIV-1 protease-ligand complexes having known three-dimensional structures. All ligands tested are highly flexible, having more than 10 conformational degrees of freedom. The SSGA was tested for the rigid and flexible ligand docking cases. The implemented genetic algorithm was able to dock successfully rigid and flexible ligand molecules, but with a decreasing performance when the number of ligand conformational degrees of freedom increased. The docked lowest-energy structures have root mean square deviation (RMSD) with respect to the corresponding experimental crystallographic structure ranging from 0.037 Å to 0.090 Å in the rigid docking, and 0.420 Å to 1.943 Å in the flexible docking. We found that not only the number of ligand conformational degrees of freedom is an important aspect to the algorithm performance, but also that the more internal dihedral angles are critical. Furthermore, our results showed that the initial population distribution can be relevant for the algorithm performance.Sociedade Brasileira de Genética2004-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400022Genetics and Molecular Biology v.27 n.4 2004reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572004000400022info:eu-repo/semantics/openAccessMagalhães,Camila S. deBarbosa,Hélio J.C.Dardenne,Laurent E.eng2005-01-14T00:00:00Zoai:scielo:S1415-47572004000400022Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2005-01-14T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false |
dc.title.none.fl_str_mv |
A genetic algorithm for the ligand-protein docking problem |
title |
A genetic algorithm for the ligand-protein docking problem |
spellingShingle |
A genetic algorithm for the ligand-protein docking problem Magalhães,Camila S. de ligand-protein docking flexible docking genetic algorithms |
title_short |
A genetic algorithm for the ligand-protein docking problem |
title_full |
A genetic algorithm for the ligand-protein docking problem |
title_fullStr |
A genetic algorithm for the ligand-protein docking problem |
title_full_unstemmed |
A genetic algorithm for the ligand-protein docking problem |
title_sort |
A genetic algorithm for the ligand-protein docking problem |
author |
Magalhães,Camila S. de |
author_facet |
Magalhães,Camila S. de Barbosa,Hélio J.C. Dardenne,Laurent E. |
author_role |
author |
author2 |
Barbosa,Hélio J.C. Dardenne,Laurent E. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Magalhães,Camila S. de Barbosa,Hélio J.C. Dardenne,Laurent E. |
dc.subject.por.fl_str_mv |
ligand-protein docking flexible docking genetic algorithms |
topic |
ligand-protein docking flexible docking genetic algorithms |
description |
We analyzed the performance of a real coded "steady-state" genetic algorithm (SSGA) using a grid-based methodology in docking five HIV-1 protease-ligand complexes having known three-dimensional structures. All ligands tested are highly flexible, having more than 10 conformational degrees of freedom. The SSGA was tested for the rigid and flexible ligand docking cases. The implemented genetic algorithm was able to dock successfully rigid and flexible ligand molecules, but with a decreasing performance when the number of ligand conformational degrees of freedom increased. The docked lowest-energy structures have root mean square deviation (RMSD) with respect to the corresponding experimental crystallographic structure ranging from 0.037 Å to 0.090 Å in the rigid docking, and 0.420 Å to 1.943 Å in the flexible docking. We found that not only the number of ligand conformational degrees of freedom is an important aspect to the algorithm performance, but also that the more internal dihedral angles are critical. Furthermore, our results showed that the initial population distribution can be relevant for the algorithm performance. |
publishDate |
2004 |
dc.date.none.fl_str_mv |
2004-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400022 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400022 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1415-47572004000400022 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
dc.source.none.fl_str_mv |
Genetics and Molecular Biology v.27 n.4 2004 reponame:Genetics and Molecular Biology instname:Sociedade Brasileira de Genética (SBG) instacron:SBG |
instname_str |
Sociedade Brasileira de Genética (SBG) |
instacron_str |
SBG |
institution |
SBG |
reponame_str |
Genetics and Molecular Biology |
collection |
Genetics and Molecular Biology |
repository.name.fl_str_mv |
Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG) |
repository.mail.fl_str_mv |
||editor@gmb.org.br |
_version_ |
1752122379400642560 |