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An Efficient Multilayer Approach to Model DNA-Based Nanobiosensors.

Jesús Lucia-Tamudo1, Juan J Nogueira1,2, Sergio Díaz-Tendero1,2,3

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|February 13, 2023
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Summary

We developed a computational method to calculate the reduction potential of DNA nucleobase biosensors on gold. Guanine biosensors are more easily oxidized due to molecular interactions, and linker modifications can tune redox properties.

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Area of Science:

  • Computational chemistry
  • Biosensor technology
  • Electrochemistry

Background:

  • Nanobiosensors utilize DNA nucleobases on gold substrates.
  • Understanding their redox properties is crucial for applications.
  • Existing models may not fully capture environmental and conformational effects.

Purpose of the Study:

  • To present a computational protocol for determining the one-electron reduction potential of DNA nucleobase-based nanobiosensors.
  • To investigate the influence of molecular assembly and linker modification on biosensor redox behavior.

Main Methods:

  • A hybrid quantum mechanics/molecular mechanics (QM/MM) approach combined with molecular dynamics (MD) simulations.
  • Utilizing Marcus theory to analyze electron transfer processes.
  • Incorporating environmental effects via a continuum solvation model.

Main Results:

  • The computational model accurately predicts the reduction potential of nanobiosensors.
  • Guanine-based biosensors exhibit increased oxidation susceptibility compared to isolated guanine due to intermolecular electrostatic interactions.
  • The choice of linker significantly impacts the biosensor's redox properties.

Conclusions:

  • The developed computational protocol provides an efficient means to study nanobiosensor electrochemistry.
  • Intermolecular interactions within the self-assembled monolayer play a key role in determining redox potential.
  • Tailoring linker chemistry offers a strategy for tuning biosensor performance.