RT-TDDFT study of hole oscillations in B-DNA monomers and dimers

Attochemistry Regulation of Charge Migration

Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. To determine the relationship between a molecule's structure and the CM dynamics it exhibits, we perform systematic studies of para-functionalized bromobenzene molecules (X-C₆H₄-R) using real-time time-dependent density functional theory. We initiate valence-electron dynamics by emulating rapid strong-field ionization leading to a localized hole on the bromine atom. The resulting CM, which takes on the order of 1 fs, occurs via an X localized → C₆H₄ delocalized → R localized mechanism. Interestingly, the hole contrast on the acceptor functional group increases with increasing electron-donating strength. This trend is well-described by the Hammett σ value of the group, which is a commonly used metric for quantifying the effect of functionalization on the chemical reactivity of benzene derivatives. These results suggest that simple attochemistry principles and a density-based picture can be used to predict and understand CM.

First-principles study of benzo[a]pyrene-7,8-dione and DNA adducts

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in environments, and some of them are causative agents of human cancer. Previous studies concluded that benzo[a]pyrene-7,8-dione (BPQ), which is one kind of carcinogenic PAH metabolites, forms covalently bonded adducts with DNA, and the major adduct formed is a deoxyguanosine adduct. In this work, we investigate the interactions between BPQ and DNA molecules via first-principles calculations. We identify six possible DNA adducts with BPQ. In addition to the four adducts forming covalent bonds, there are two adducts bound purely by van der Waals (vdW) interactions. Remarkably, the two vdW-bound adducts have comparable, if not larger, binding energies as the covalent adducts. The results may help us gain more understanding of the interactions between PAH metabolites and DNA.

Effects of Structural Dynamics on Charge Carrier Transfer in B-DNA: A Combined MD and RT-TDDFT Study

Hole transfer along the axis of duplex DNA has been the focus of physical chemistry research for decades, with implications in diverse fields, from nanotechnology to cell oxidative damage. Computational approaches are particularly amenable for this problem, to complement experimental data for interpretation of transfer mechanisms. To be predictive, computational results need to account for the inherent mobility of biological molecules during the time frame of experimental measurements. Here, we address the structural variability of B-DNA and its effects on hole transfer in a combined molecular dynamics (MD) and real-time time-dependent density functional theory (RT-TDDFT) study. Our results show that quantities that characterize the charge transfer process, such as the time-dependent dipole moment and hole population at a specific site, are sensitive to structural changes that occur on the nanosecond time scale. We extend the range of physical properties for which such a correlation has been observed, further establishing the fact that quantitative computational data on charge transfer properties should include statistical averages. Furthermore, we use the RT-TDDFT results to assess an efficient tight-binding method suitable for high-throughput predictions. We demonstrate that charge transfer, although affected by structural variability, on average, remains strong in AA and GG dimers.

Revealing Charge-Transfer Dynamics at Electrified Sulfur Cathodes Using Constrained Density Functional Theory

To understand and control the behavior of electrochemical systems, including batteries and electrocatalysts, we seek molecular-level details of the charge transfer mechanisms at electrified interfaces. Recognizing some key limitations of standard equilibrium electronic structure methods to model materials and their interfaces, we propose applying charge constraints to effectively separate electronic and nuclear degrees of freedom, which are especially beneficial to the study of conversion electrodes, where electronic charge carriers are converted to much slower polarons within a material that is nonmetallic. We demonstrate the need for such an approach within the context of sulfur cathodes and the arrival of Li ions during discharge of a Li-S cell. The requirement that electronic degrees of freedom are arrested is justified by comparison with real-time evolution of the electronic structure. Long-lived metastable configurations provide plenty of time for nuclear dynamics and relaxation in response to the electrification of the interface, a process that would be completely missed without applying charge constraints. This approach will be vital to the study of dynamics at electrified interfaces which may be created deliberately, adding charge to the electrode, or spontaneously, due to finite temperature dynamics in the electrolyte.

Predicting the DNA Conductance Using a Deep Feedforward Neural Network Model

Double-stranded DNA (dsDNA) has been established as an efficient medium for charge migration, bringing it to the forefront of the field of molecular electronics and biological research. The charge migration rate is controlled by the electronic couplings between the two nucleobases of DNA/RNA. These electronic couplings strongly depend on the intermolecular geometry and orientation. Estimating these electronic couplings for all the possible relative geometries of molecules using the computationally demanding first-principles calculations requires a lot of time and computational resources. In this article, we present a machine learning (ML)-based model to calculate the electronic coupling between any two bases of dsDNA/dsRNA and bypass the computationally expensive first-principles calculations. Using the Coulomb matrix representation which encodes the atomic identities and coordinates of the DNA base pairs to prepare the input dataset, we train a feedforward neural network model. Our neural network (NN) model can predict the electronic couplings between dsDNA base pairs with any structural orientation with a mean absolute error (MAE) of less than 0.014 eV. We further use the NN-predicted electronic coupling values to compute the dsDNA/dsRNA conductance.

Tight-Binding Modeling of Nucleic Acid Sequences: Interplay between Various Types of Order or Disorder and Charge Transport

This review is devoted to tight-binding (TB) modeling of nucleic acid sequences like DNA and RNA. It addresses how various types of order (periodic, quasiperiodic, fractal) or disorder (diagonal, non-diagonal, random, methylation et cetera) affect charge transport. We include an introduction to TB and a discussion of its various submodels [wire, ladder, extended ladder, fishbone (wire), fishbone ladder] and of the process of renormalization. We proceed to a discussion of aperiodicity, quasicrystals and the mathematics of aperiodic substitutional sequences: primitive substitutions, Perron–Frobenius eigenvalue, induced substitutions, and Pisot property. We discuss the energy structure of nucleic acid wires, the coupling to the leads, the transmission coefficients and the current–voltage curves. We also summarize efforts aiming to examine the potentiality to utilize the charge transport characteristics of nucleic acids as a tool to probe several diseases or disorders.

Quasi-Periodic and Fractal Polymers: Energy Structure and Carrier Transfer

We study the energy structure and the coherent transfer of an extra electron or hole along aperiodic polymers made of N monomers, with fixed boundaries, using B-DNA as our prototype system. We use a Tight-Binding wire model, where a site is a monomer (e.g., in DNA, a base pair). We consider quasi-periodic (Fibonacci, Thue-Morse, Double-Period, Rudin-Shapiro) and fractal (Cantor Set, Asymmetric Cantor Set) polymers made of the same monomer (I polymers) or made of different monomers (D polymers). For all types of such polymers, we calculate the highest occupied molecular orbital (HOMO) eigenspectrum and the lowest unoccupied molecular orbital (LUMO) eigenspectrum, the HOMO-LUMO gap and the density of states. We examine the mean over time probability to find the carrier at each monomer, the frequency content of carrier transfer (Fourier spectra, weighted mean frequency of each monomer, total weighted mean frequency of the polymer), and the pure mean transfer rate k. Our results reveal that there is a correspondence between the degree of structural complexity and the transfer properties. I polymers are more favorable for charge transfer than D polymers. We compare k ( N ) of quasi-periodic and fractal sequences with that of periodic sequences (including homopolymers) as well as with randomly shuffled sequences. Finally, we discuss aspects of experimental results on charge transfer rates in DNA with respect to our coherent pure mean transfer rates.

Periodic, quasiperiodic, fractal, Kolakoski, and random binary polymers: Energy structure and carrier transport

We study periodic, quasiperiodic (Thue-Morse, Fibonacci, period doubling, Rudin-Shapiro), fractal (Cantor, generalized Cantor), Kolakoski, and random binary sequences using a tight-binding wire model, where a site is a monomer (e.g., in DNA, a base pair). We use B-DNA as our prototype system. All sequences have purines, guanine (G) or adenine (A), on the same strand, i.e., our prototype binary alphabet is {G,A}. Our aim is to examine the influence of sequence intricacy and magnitude of parameters on energy structure, localization, and charge transport. We study quantities such as autocorrelation function, eigenspectra, density of states, Lyapunov exponents, transmission coefficients, and current-voltage curves. We show that the degree of sequence intricacy and the presence of correlations decisively affect the aforementioned physical properties. Periodic segments have enhanced transport properties. Specifically, in homogeneous sequences transport efficiency is maximum. There are several deterministic aperiodic sequences that can support significant currents, depending on the Fermi level of the leads. Random sequences is the less efficient category.