The determination of the redox properties of nucleobases is of paramount importance to get insight into the charge-transfer processes in which they are involved, such as those occurring in DNA-inspired biosensors. Although many theoretical and experimental studies have been conducted, the value of the one-electron oxidation potentials of nucleobases is not well-defined. Moreover, the most appropriate theoretical protocol to model the redox properties has not been established yet. In this work, we have implemented and evaluated different static and dynamic approaches to compute the one-electron oxidation potentials of solvated nucleobases. In the static framework, two thermodynamic cycles have been tested to assess their accuracy against the direct determination of oxidation potentials from the adiabatic ionization energies. Then, the introduction of vibrational sampling, the effect of implicit and explicit solvation models, and the application of the Marcus theory have been analyzed through dynamic methods. The results revealed that the static direct determination provides more accurate results than thermodynamic cycles. Moreover, the effect of sampling has not shown to be relevant, and the results are improved within the dynamic framework when the Marcus theory is applied, especially in explicit solvent, with respect to the direct approach. Finally, the presence of different tautomers in water does not affect significantly the one-electron oxidation potentials.
We present a toolkit that allows for the preparation of QM/MM input files from a conformational ensemble of molecular geometries. The package is currently compatible with trajectory and topology files in Amber, CHARMM, GROMACS and NAMD formats, and has the possibility to generate QM/MM input files for Gaussian (09 and 16), Orca (≥4.0), NWChem and (Open)Molcas. The toolkit can be used in command line, so that no programming experience is required, although it presents some features that can also be employed as a python application programming interface. We apply the toolkit in four situations in which different electronic-structure properties of organic molecules in the presence of a solvent or a complex biological environment are computed: the reduction potential of the nucleobases in acetonitrile, an energy decomposition analysis of tyrosine interacting with water, the absorption spectrum of an azobenzene derivative integrated into a voltage-gated ion channel, and the absorption and emission spectra of the luciferine/luciferase complex. These examples show that the toolkit can be employed in a manifold of situations for both the electronic ground state and electronically excited states. It also allows for the automatic correction of the active space in the case of CASSCF calculations on an ensemble of geometries, as it is shown for the azobenzene derivative photoswitch case.
We present a toolkit that allows for the preparation of QM/MM input files from a conformational ensemble of molecular geometries. The toolkit can be used in command line, so that no programming experience is required, although it presents some features that can also be employed as a python application programming interface. We apply the toolkit in four situations in which different electronic-structure properties of organic molecules in the presence of a solvent or a complex biological environment are computed: the reduction potential of the nucleobases in acetonitrile, an energy decomposition analysis of tyrosine interacting with water, the absorption spectrum of an azobenzene derivative integrated into a voltage-gated ion channel, and the absorption and emission spectra of the luciferine/luciferase complex. These examples show that the toolkit can be employed in a manifold of situations for both the electronic ground state and electronically excited states. It also allows for the automatic correction of the active space in the case of CASSCF calculations on an ensemble of geometries, as it is shown for the azobenzene derivative photoswitch case.
The study of DNA processes is essential to understand not only its intrinsic biological functions, but also its role in many innovative applications. The use of DNA as a nanowire or electrochemical biosensor leads to the need for a deep investigation of the charge transfer process along the strand, as well as of the redox properties. In this contribution, the one-electron oxidation potential and the charge delocalization of the hole formed after oxidation is computationally investigated for different heterogeneous single-stranded DNA strands. We have established a two-steps protocol: (i) molecular dynamics (MD) simulations in the frame of quantum mechanics / molecular mechanics (QM/MM) were performed to sample the conformational space; (ii) energetic properties were then obtained within a QM1/QM2/continuum approach in combination with the Marcus theory over an ensemble of selected geometries. The results reveal that the one-electron oxidation potential in the heterogeneous strands can be seen as a linear combination of that property within homogeneous strands. In addition, the hole delocalization between different nucleobases is, in general, small, supporting the conclusion of a hopping mechanism for the charge transport along the strands. However, charge delocalization becomes more important, and so the tunneling mechanism contribution, when the reducing power of the nucleobases forming the strand is similar. Moreover, an important charge delocalization is also obtained when there is correlation between pairs of some of the interbase coordinates of the strand: twist/shift, shift/slide and rise/tilt.
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.
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