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An Efficient Multilayer Approach to Model DNA-Based Nanobiosensors
[Image: see text] In this work, we present a full computational protocol to successfully obtain the one-electron reduction potential of nanobiosensors based on a self-assembled monolayer of DNA nucleobases linked to a gold substrate. The model is able to account for conformational sampling and envir...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969517/ https://www.ncbi.nlm.nih.gov/pubmed/36779932 http://dx.doi.org/10.1021/acs.jpcb.2c07225 |
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author | Lucia-Tamudo, Jesús Nogueira, Juan J. Díaz-Tendero, Sergio |
author_facet | Lucia-Tamudo, Jesús Nogueira, Juan J. Díaz-Tendero, Sergio |
author_sort | Lucia-Tamudo, Jesús |
collection | PubMed |
description | [Image: see text] In this work, we present a full computational protocol to successfully obtain the one-electron reduction potential of nanobiosensors based on a self-assembled monolayer of DNA nucleobases linked to a gold substrate. The model is able to account for conformational sampling and environmental effects at a quantum mechanical (QM) level efficiently, by combining molecular mechanics (MM) molecular dynamics and multilayer QM/MM/continuum calculations within the framework of Marcus theory. The theoretical model shows that a guanine-based biosensor is more prone to be oxidized than the isolated nucleobase in water due to the electrostatic interactions between the assembled guanine molecules. In addition, the redox properties of the biosensor can be tuned by modifying the nature of the linker that anchor the nucleobases to the metal support. |
format | Online Article Text |
id | pubmed-9969517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99695172023-02-28 An Efficient Multilayer Approach to Model DNA-Based Nanobiosensors Lucia-Tamudo, Jesús Nogueira, Juan J. Díaz-Tendero, Sergio J Phys Chem B [Image: see text] In this work, we present a full computational protocol to successfully obtain the one-electron reduction potential of nanobiosensors based on a self-assembled monolayer of DNA nucleobases linked to a gold substrate. The model is able to account for conformational sampling and environmental effects at a quantum mechanical (QM) level efficiently, by combining molecular mechanics (MM) molecular dynamics and multilayer QM/MM/continuum calculations within the framework of Marcus theory. The theoretical model shows that a guanine-based biosensor is more prone to be oxidized than the isolated nucleobase in water due to the electrostatic interactions between the assembled guanine molecules. In addition, the redox properties of the biosensor can be tuned by modifying the nature of the linker that anchor the nucleobases to the metal support. American Chemical Society 2023-02-13 /pmc/articles/PMC9969517/ /pubmed/36779932 http://dx.doi.org/10.1021/acs.jpcb.2c07225 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Lucia-Tamudo, Jesús Nogueira, Juan J. Díaz-Tendero, Sergio An Efficient Multilayer Approach to Model DNA-Based Nanobiosensors |
title | An Efficient Multilayer Approach to Model DNA-Based
Nanobiosensors |
title_full | An Efficient Multilayer Approach to Model DNA-Based
Nanobiosensors |
title_fullStr | An Efficient Multilayer Approach to Model DNA-Based
Nanobiosensors |
title_full_unstemmed | An Efficient Multilayer Approach to Model DNA-Based
Nanobiosensors |
title_short | An Efficient Multilayer Approach to Model DNA-Based
Nanobiosensors |
title_sort | efficient multilayer approach to model dna-based
nanobiosensors |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969517/ https://www.ncbi.nlm.nih.gov/pubmed/36779932 http://dx.doi.org/10.1021/acs.jpcb.2c07225 |
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