QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity

Detalhes bibliográficos
Autor(a) principal: Sousa, Inês J.
Data de Publicação: 2013
Outros Autores: Ferreira, Maria-José U., Molnár, Joseph, Fernandes, Miguel X.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.13/5024
Resumo: Multidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatro phane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure–activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to deter mine which structural modifications can be performed to improve their activity. Using experimental bio logical data at two concentrations (4 and 40 lg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for bio logical activities at compound concentrations of 4 and 40 lg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R2 pred values of 0.765 and 0.534 for biological activities at com pound concentrations of 4 and 40 lg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 lg/ml concentrations, respectively. For the same concentrations, the obtained R2 pred values for jatro phanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability.
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spelling QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activityQuantitative structure–activity relationshipP-glycoproteinMacrocyclic diterpenesMultidrug resistanceMultiple linear regression.Faculdade de Ciências Exatas e da EngenhariaMultidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatro phane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure–activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to deter mine which structural modifications can be performed to improve their activity. Using experimental bio logical data at two concentrations (4 and 40 lg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for bio logical activities at compound concentrations of 4 and 40 lg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R2 pred values of 0.765 and 0.534 for biological activities at com pound concentrations of 4 and 40 lg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 lg/ml concentrations, respectively. For the same concentrations, the obtained R2 pred values for jatro phanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability.ElsevierDigitUMaSousa, Inês J.Ferreira, Maria-José U.Molnár, JosephFernandes, Miguel X.2023-02-10T10:32:51Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.13/5024engSousa, I. J., Ferreira, M. J. U., Molnár, J., & Fernandes, M. X. (2013). QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity. European Journal of Pharmaceutical Sciences, 48(3), 542-553.10.1016/j.ejps.2012.11.012info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-12T05:24:11Zoai:digituma.uma.pt:10400.13/5024Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:46:30.017961Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
title QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
spellingShingle QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
Sousa, Inês J.
Quantitative structure–activity relationship
P-glycoprotein
Macrocyclic diterpenes
Multidrug resistance
Multiple linear regression
.
Faculdade de Ciências Exatas e da Engenharia
title_short QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
title_full QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
title_fullStr QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
title_full_unstemmed QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
title_sort QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity
author Sousa, Inês J.
author_facet Sousa, Inês J.
Ferreira, Maria-José U.
Molnár, Joseph
Fernandes, Miguel X.
author_role author
author2 Ferreira, Maria-José U.
Molnár, Joseph
Fernandes, Miguel X.
author2_role author
author
author
dc.contributor.none.fl_str_mv DigitUMa
dc.contributor.author.fl_str_mv Sousa, Inês J.
Ferreira, Maria-José U.
Molnár, Joseph
Fernandes, Miguel X.
dc.subject.por.fl_str_mv Quantitative structure–activity relationship
P-glycoprotein
Macrocyclic diterpenes
Multidrug resistance
Multiple linear regression
.
Faculdade de Ciências Exatas e da Engenharia
topic Quantitative structure–activity relationship
P-glycoprotein
Macrocyclic diterpenes
Multidrug resistance
Multiple linear regression
.
Faculdade de Ciências Exatas e da Engenharia
description Multidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatro phane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure–activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to deter mine which structural modifications can be performed to improve their activity. Using experimental bio logical data at two concentrations (4 and 40 lg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for bio logical activities at compound concentrations of 4 and 40 lg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R2 pred values of 0.765 and 0.534 for biological activities at com pound concentrations of 4 and 40 lg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 lg/ml concentrations, respectively. For the same concentrations, the obtained R2 pred values for jatro phanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
2023-02-10T10:32:51Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.13/5024
url http://hdl.handle.net/10400.13/5024
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Sousa, I. J., Ferreira, M. J. U., Molnár, J., & Fernandes, M. X. (2013). QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity. European Journal of Pharmaceutical Sciences, 48(3), 542-553.
10.1016/j.ejps.2012.11.012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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