Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations

Detalhes bibliográficos
Autor(a) principal: Mendes, Maria
Data de Publicação: 2020
Outros Autores: Cova, Tânia, Basso, João, Ramos, M. Luísa, Vitorino, Rui, Sousa, João, Pais, Alberto, Vitorino, Carla
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
DOI: 10.1016/j.molliq.2020.113774
Texto Completo: http://hdl.handle.net/10316/90813
https://doi.org/10.1016/j.molliq.2020.113774
Resumo: The main bottleneck of glioblastoma still relies on the existence of the blood brain-blood brain tumor dual barrier, along with the lack of therapy specificity. The present work deals with the question of whether (and how) different targeting hyaluronic acid (HA)-peptide [c(RGDfK) and/or H7K(R2)2] moieties hierarchically interact with each other, to ensure a unique entity with specificity to glioblastoma. A dual experimental-computational approach, encompassing nuclear magnetic resonance and molecular dynamics simulations is enclosed. Relevant contact patterns based on the identification of the stabilizing/destabilizing noncovalent interactions within the constructs are detailed. The synthesis pathway requires the HA-c(RGDfK)-H7k(R2)2 association hierarchy, stemming from the size and amino acid residue rearrangement, in the 1:1 M ratio, to obtain a stable conjugate ultimately able to interact with the tumor cell membrane. To our knowledge, the structural and mechanistic rationale for the formation of hybrid polymer-peptide constructs, including HA-c(RGDfK)-H7k(R2)2, for glioblastoma has not been addressed so far.
id RCAP_9211bbe89fa55a4b45eae70851e6bd58
oai_identifier_str oai:estudogeral.uc.pt:10316/90813
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulationsHyaluronic acidc(RGDfK)H7k(R2)2Polymer-peptide conjugatesGlioblastomaThe main bottleneck of glioblastoma still relies on the existence of the blood brain-blood brain tumor dual barrier, along with the lack of therapy specificity. The present work deals with the question of whether (and how) different targeting hyaluronic acid (HA)-peptide [c(RGDfK) and/or H7K(R2)2] moieties hierarchically interact with each other, to ensure a unique entity with specificity to glioblastoma. A dual experimental-computational approach, encompassing nuclear magnetic resonance and molecular dynamics simulations is enclosed. Relevant contact patterns based on the identification of the stabilizing/destabilizing noncovalent interactions within the constructs are detailed. The synthesis pathway requires the HA-c(RGDfK)-H7k(R2)2 association hierarchy, stemming from the size and amino acid residue rearrangement, in the 1:1 M ratio, to obtain a stable conjugate ultimately able to interact with the tumor cell membrane. To our knowledge, the structural and mechanistic rationale for the formation of hybrid polymer-peptide constructs, including HA-c(RGDfK)-H7k(R2)2, for glioblastoma has not been addressed so far.Elsevier2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/90813http://hdl.handle.net/10316/90813https://doi.org/10.1016/j.molliq.2020.113774eng01677322https://www.sciencedirect.com/science/article/pii/S016773222032331XMendes, MariaCova, TâniaBasso, JoãoRamos, M. LuísaVitorino, RuiSousa, JoãoPais, AlbertoVitorino, Carlainfo: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:RCAAP2022-10-20T11:33:47Zoai:estudogeral.uc.pt:10316/90813Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:10:50.333561Repositório 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 Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
title Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
spellingShingle Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
Mendes, Maria
Hyaluronic acid
c(RGDfK)
H7k(R2)2
Polymer-peptide conjugates
Glioblastoma
Mendes, Maria
Hyaluronic acid
c(RGDfK)
H7k(R2)2
Polymer-peptide conjugates
Glioblastoma
title_short Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
title_full Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
title_fullStr Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
title_full_unstemmed Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
title_sort Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations
author Mendes, Maria
author_facet Mendes, Maria
Mendes, Maria
Cova, Tânia
Basso, João
Ramos, M. Luísa
Vitorino, Rui
Sousa, João
Pais, Alberto
Vitorino, Carla
Cova, Tânia
Basso, João
Ramos, M. Luísa
Vitorino, Rui
Sousa, João
Pais, Alberto
Vitorino, Carla
author_role author
author2 Cova, Tânia
Basso, João
Ramos, M. Luísa
Vitorino, Rui
Sousa, João
Pais, Alberto
Vitorino, Carla
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Mendes, Maria
Cova, Tânia
Basso, João
Ramos, M. Luísa
Vitorino, Rui
Sousa, João
Pais, Alberto
Vitorino, Carla
dc.subject.por.fl_str_mv Hyaluronic acid
c(RGDfK)
H7k(R2)2
Polymer-peptide conjugates
Glioblastoma
topic Hyaluronic acid
c(RGDfK)
H7k(R2)2
Polymer-peptide conjugates
Glioblastoma
description The main bottleneck of glioblastoma still relies on the existence of the blood brain-blood brain tumor dual barrier, along with the lack of therapy specificity. The present work deals with the question of whether (and how) different targeting hyaluronic acid (HA)-peptide [c(RGDfK) and/or H7K(R2)2] moieties hierarchically interact with each other, to ensure a unique entity with specificity to glioblastoma. A dual experimental-computational approach, encompassing nuclear magnetic resonance and molecular dynamics simulations is enclosed. Relevant contact patterns based on the identification of the stabilizing/destabilizing noncovalent interactions within the constructs are detailed. The synthesis pathway requires the HA-c(RGDfK)-H7k(R2)2 association hierarchy, stemming from the size and amino acid residue rearrangement, in the 1:1 M ratio, to obtain a stable conjugate ultimately able to interact with the tumor cell membrane. To our knowledge, the structural and mechanistic rationale for the formation of hybrid polymer-peptide constructs, including HA-c(RGDfK)-H7k(R2)2, for glioblastoma has not been addressed so far.
publishDate 2020
dc.date.none.fl_str_mv 2020
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/10316/90813
http://hdl.handle.net/10316/90813
https://doi.org/10.1016/j.molliq.2020.113774
url http://hdl.handle.net/10316/90813
https://doi.org/10.1016/j.molliq.2020.113774
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 01677322
https://www.sciencedirect.com/science/article/pii/S016773222032331X
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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
repository.mail.fl_str_mv
_version_ 1822226281730670592
dc.identifier.doi.none.fl_str_mv 10.1016/j.molliq.2020.113774