Cargando…

Parallel screening and cheminformatics modeling of flavonoid activated aptasensors

A parallel screening of 27 different flavonoids and chalcones was conducted using 6 artificial naringenin-activated riboswitches (M1, M2, M3, O, L and H). A quantitative structure-property relationship approach was applied to understand the physicochemical properties of the flavonoid structures resu...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiu, Yu, Zhang, Ni, Prabhakaran, Pranesha, Jang, Sungho, Yuan, Qipeng, Breneman, Curt M., Jung, Gyoo Yeol, Vongsangnak, Wanwipa, Koffas, Mattheos A.G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445297/
https://www.ncbi.nlm.nih.gov/pubmed/36101898
http://dx.doi.org/10.1016/j.synbio.2022.07.006
_version_ 1784783398919733248
author Xiu, Yu
Zhang, Ni
Prabhakaran, Pranesha
Jang, Sungho
Yuan, Qipeng
Breneman, Curt M.
Jung, Gyoo Yeol
Vongsangnak, Wanwipa
Koffas, Mattheos A.G.
author_facet Xiu, Yu
Zhang, Ni
Prabhakaran, Pranesha
Jang, Sungho
Yuan, Qipeng
Breneman, Curt M.
Jung, Gyoo Yeol
Vongsangnak, Wanwipa
Koffas, Mattheos A.G.
author_sort Xiu, Yu
collection PubMed
description A parallel screening of 27 different flavonoids and chalcones was conducted using 6 artificial naringenin-activated riboswitches (M1, M2, M3, O, L and H). A quantitative structure-property relationship approach was applied to understand the physicochemical properties of the flavonoid structures resulting in specificity differences relied on the fluorescence intensity of a green fluorescent protein reporter. Robust models of riboswitches M1, M2 and O that had good predictive power were constructed with descriptors selected for their high correlation. Increased electronegativity and hydrophilicity of the flavonoids structures were identified as two properties that increased binding affinity to RNA riboswitches. Hydroxyl groups at the C-3′ and C-4’ positions of the flavonoid molecule were strictly required for ligand-activation with riboswitches M1 and M2. Riboswitches O and L preferred multi-hydroxylated flavones as ligands. Substitutions on the A ring of the flavonoid molecule were not important in the molecular recognition process. O-glycosylated derivatives were not recognized by any of the riboswitches, presumably due to steric hindrances. Despite the challenges of detecting RNA conformational change after ligand binding, the resulting models elucidate important physicochemical features in the ligands for conformational structural studies of artificial aptamer complexes and for design of ligands having higher binding specificity.
format Online
Article
Text
id pubmed-9445297
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher KeAi Publishing
record_format MEDLINE/PubMed
spelling pubmed-94452972022-09-12 Parallel screening and cheminformatics modeling of flavonoid activated aptasensors Xiu, Yu Zhang, Ni Prabhakaran, Pranesha Jang, Sungho Yuan, Qipeng Breneman, Curt M. Jung, Gyoo Yeol Vongsangnak, Wanwipa Koffas, Mattheos A.G. Synth Syst Biotechnol Original Research Article A parallel screening of 27 different flavonoids and chalcones was conducted using 6 artificial naringenin-activated riboswitches (M1, M2, M3, O, L and H). A quantitative structure-property relationship approach was applied to understand the physicochemical properties of the flavonoid structures resulting in specificity differences relied on the fluorescence intensity of a green fluorescent protein reporter. Robust models of riboswitches M1, M2 and O that had good predictive power were constructed with descriptors selected for their high correlation. Increased electronegativity and hydrophilicity of the flavonoids structures were identified as two properties that increased binding affinity to RNA riboswitches. Hydroxyl groups at the C-3′ and C-4’ positions of the flavonoid molecule were strictly required for ligand-activation with riboswitches M1 and M2. Riboswitches O and L preferred multi-hydroxylated flavones as ligands. Substitutions on the A ring of the flavonoid molecule were not important in the molecular recognition process. O-glycosylated derivatives were not recognized by any of the riboswitches, presumably due to steric hindrances. Despite the challenges of detecting RNA conformational change after ligand binding, the resulting models elucidate important physicochemical features in the ligands for conformational structural studies of artificial aptamer complexes and for design of ligands having higher binding specificity. KeAi Publishing 2022-08-18 /pmc/articles/PMC9445297/ /pubmed/36101898 http://dx.doi.org/10.1016/j.synbio.2022.07.006 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Xiu, Yu
Zhang, Ni
Prabhakaran, Pranesha
Jang, Sungho
Yuan, Qipeng
Breneman, Curt M.
Jung, Gyoo Yeol
Vongsangnak, Wanwipa
Koffas, Mattheos A.G.
Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title_full Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title_fullStr Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title_full_unstemmed Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title_short Parallel screening and cheminformatics modeling of flavonoid activated aptasensors
title_sort parallel screening and cheminformatics modeling of flavonoid activated aptasensors
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445297/
https://www.ncbi.nlm.nih.gov/pubmed/36101898
http://dx.doi.org/10.1016/j.synbio.2022.07.006
work_keys_str_mv AT xiuyu parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT zhangni parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT prabhakaranpranesha parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT jangsungho parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT yuanqipeng parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT brenemancurtm parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT junggyooyeol parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT vongsangnakwanwipa parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors
AT koffasmattheosag parallelscreeningandcheminformaticsmodelingofflavonoidactivatedaptasensors