An Efficient Multilayer Approach to Model DNA-Based Nano-Biosensors

22 September 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

In this work we present a full computational protocol to successfully obtain the one-electron reduction potential of nano-biosensors 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 classical molecular dynamics (MM) 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.

Keywords

Reduction potential
Biosensors
DNA
QM/MM
QM/COSMO
Molecular Dynamics
DFT
Marcus Theory

Supplementary materials

Title
Description
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Title
Supporting Information for "An Efficient Multilayer Approach to Model DNA-Based Nano-Biosensors''
Description
-Methods to compute the reduction potentials. -Computational details of molecular dynamics and QM/MM and QM/COSMO calculatios. -Setup of the self assembled monolayers. -Computed reduction potentials of guanine-linker complexes.
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