Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.

Prediction of human Cytochrome P450 (CYP) binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory ac...

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Autores: Capoferri, Luigi, Verkade-Vreeker, Marlies C. A., Buitenhuis, Danny, Commandeu, Jan N.M., Pastor Maeso, Manuel, Vermeulen, Nico P. E., Geerke, Daan P.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/25588
Acesso em linha:http://hdl.handle.net/10230/25588
http://dx.doi.org/10.1371/journal.pone.0142232
Access Level:acceso abierto
Palavra-chave:Citocrom P-450 -- Metabolisme
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spelling Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.Capoferri, LuigiVerkade-Vreeker, Marlies C. A.Buitenhuis, DannyCommandeu, Jan N.M.Pastor Maeso, ManuelVermeulen, Nico P. E.Geerke, Daan P.Citocrom P-450 -- MetabolismePrediction of human Cytochrome P450 (CYP) binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD) simulations and Linear Interaction Energy (LIE) theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE) of 4.1 kJ mol-1 and a standard error in prediction (SDEP) in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units).The work was supported by Innovative Medicines Initiative Joint Undertaking (IMI-JU) under grant agreement no. 115002 (eTOX), resources of which are composed of financial contribution from the European Union Seventh Framework Programme/n(FP7/20072013) and EFPIA companies in kind contribution; www.etoxproject.eu. The work was also supported by The Netherlands Organisation for Scientific Research (NWO, VIDI grant 723.012.105); www.nwo.nl.Public Library of Science201620162015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/25588http://dx.doi.org/10.1371/journal.pone.0142232reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésPLoS ONE. 2015 Nov 9;10(11):e0142232info:eu-repo/grantAgreement/EC/FP7/115002© 2015 Capoferri et al. This is an open access article distributed under the terms of the http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/255882026-05-29T05:05:01Z
dc.title.none.fl_str_mv Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
title Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
spellingShingle Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
Capoferri, Luigi
Citocrom P-450 -- Metabolisme
title_short Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
title_full Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
title_fullStr Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
title_full_unstemmed Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
title_sort Linear interaction energy based prediction of cytochrome P450 1A2 binding affinities with reliability estimation.
dc.creator.none.fl_str_mv Capoferri, Luigi
Verkade-Vreeker, Marlies C. A.
Buitenhuis, Danny
Commandeu, Jan N.M.
Pastor Maeso, Manuel
Vermeulen, Nico P. E.
Geerke, Daan P.
author Capoferri, Luigi
author_facet Capoferri, Luigi
Verkade-Vreeker, Marlies C. A.
Buitenhuis, Danny
Commandeu, Jan N.M.
Pastor Maeso, Manuel
Vermeulen, Nico P. E.
Geerke, Daan P.
author_role author
author2 Verkade-Vreeker, Marlies C. A.
Buitenhuis, Danny
Commandeu, Jan N.M.
Pastor Maeso, Manuel
Vermeulen, Nico P. E.
Geerke, Daan P.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Citocrom P-450 -- Metabolisme
topic Citocrom P-450 -- Metabolisme
description Prediction of human Cytochrome P450 (CYP) binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD) simulations and Linear Interaction Energy (LIE) theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE) of 4.1 kJ mol-1 and a standard error in prediction (SDEP) in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units).
publishDate 2015
dc.date.none.fl_str_mv 2015
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/25588
http://dx.doi.org/10.1371/journal.pone.0142232
url http://hdl.handle.net/10230/25588
http://dx.doi.org/10.1371/journal.pone.0142232
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv PLoS ONE. 2015 Nov 9;10(11):e0142232
info:eu-repo/grantAgreement/EC/FP7/115002
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,228081

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