Universal Readers Based on Hydrogen Bonding or π-π Stacking for Identification of DNA Nucleotides in Electron Tunnel Junctions

Regulation of π-π interactions between single aromatic molecules by bias voltage

π-stacking interaction, as a fundamental type of intermolecular interaction, plays a crucial role in generating new functional molecules, altering the optoelectronic properties of materials, and maintaining protein structural stability. However, regulating intermolecular π-π interactions at the single-molecule level without altering the molecular conformation as well as the chemical properties remains a significant challenge. To this end, via conductance measurement with thousands of single molecular junctions employing a series of aromatic molecules, we demonstrate that the π-π coupling between neighboring aromatic molecules with rigid structures in a circuit can be greatly enhanced by increasing the bias voltage. We further reveal that this universal regulating effect of bias voltage without molecular conformational variation originates from the increases of the molecular dipole upon an applied electric field. These findings not only supply a non-destructive method to regulate the intermolecular interactions offering an approach to modulate the electron transport through a single molecular junction, but also deepen the understanding of the mechanism of π-π interactions.

Solvent- and functional-group-assisted tautomerism of 3-alkyl substituted 5-(2-pyridyl)-1,2,4-triazoles in DMSO-water

The tautomerism of a series of 5-alkyl substituted 3-(2-pyridyl)-1,2,4-triazoles in DMSO-d6-containing water has been investigated by 1H, 13C and 15N NMR spectroscopy. The populations of the three possible regioisomers in the tautomeric equilibrium (A [3-alkyl-5-(2-pyridyl)-1H], B [5-alkyl-3-(2-pyridyl)-1H] and C [5-alkyl-3-(2-pyridyl)-4H]) were determined. Isomers A (17-40%) and B (54-79%) are the major components and their ratio is insensitive to the substitution pattern, except for the unsubstituted and the methoxymethyl substituted derivatives. The isomer C (3-5%) has been fully characterised for the first time by NMR spectroscopy. Activation energies of tautomerisation (14.74-16.78 kcal mol-1) were determined by EXSY experiments, which also supported the involvement of water in the tautomerisation. Substituent effects on the 15N chemical shifts are relatively small. The DFT study of the tautomerism in DMSO-water showed that both A/B and B/C interconversions are assisted by the pyridine substituent and catalysed by solvent molecules. The NH-A/NH-B tautomerisation takes place via a relayed quadruple proton transfer mediated by three water molecules in the hydrogen-bonded cyclic substructure of a triazole·4H2O complex. The equilibrium B ⇄ C involves three steps: NH-B transfer to the pyridyl nitrogen mediated by a water molecule in a 1 : 1 cyclic complex, rotamerisation to bring the pyridinium NH close to N4 of the triazole catalysed by complexation to a DMSO molecule and transfer of the NH from the pyridinium donor to the N4 acceptor via a 1 : 1 complex with a bridging water molecule. This mechanism of 1,3-prototropic shift in triazoles is unprecedented in the literature.

Carbon Nitride-Based siRNA Vectors with Self-Produced O2 Effects for Targeting Combination Therapy of Liver Fibrosis via HIF-1α-Mediated TGF-β1/Smad Pathway

Hypoxia is an important feature, which can upregulate the hypoxia-inducible factor-1α (HIF-1α) expression and promote the activation of hepatic stellate cells (HSCs), leading to liver fibrosis. Currently, effective treatment for liver fibrosis is extremely lacking. Herein, a safe and effective method is established to downregulate the expression of HIF-1α in HSCs via targeted delivery of VA-PEG-modified CNs-based nanosheets-encapsulated (VA-PEG-CN@GQDs) HIF-1α small interfering RNA (HIF-1α-siRNA). Due to the presence of lipase in the liver, the reversible release of siRNA can be promoted to complete the transfection process. Simultaneously, VA-PEG-CN@GQD nanosheets enable trigger the water splitting process to produce O2 under near-infrared (NIR) irradiation, thereby improving the hypoxic environment of the liver fibrosis site and maximizing the downregulation of HIF-1α expression to improve the therapeutic effect, as demonstrated in liver fibrosis mice. Such combination therapy can inhibit the activation of HSCs via HIF-1α-mediated TGF-β1/Smad pathway, achieving outstanding therapeutic effects in liver fibrosis mice. In conclusion, this study proposes a novel strategy for the treatment of liver fibrosis by regulating the hypoxic environment and the expression of HIF-1α at lesion site.

Exploring π-π interactions and electron transport in complexes involving a hexacationic host and PAH guest: a promising avenue for molecular devices

Single isolated molecules and supramolecular host-guest systems, which consist of π-π stacking interactions, are emerging as promising building blocks for creating molecular electronic devices. In this article, we have investigated the noncovalent π-π interaction and intermolecular electron charge transport involved in a series of host-guest complexes formed between a cage-like host (H6+) and polycyclic aromatic hydrocarbon (PAH) guests (G1-G7) using different quantum chemical approaches. The host (H6+) consists of two triscationic π-electron-deficient trispyridiniumtriazine (TPZ3+) units that are bridged face-to-face by three ethylene-triazole-ethylene. Our theoretical calculations show that the perylene and naphthalene inclusion complexes G7⊂H and G1⊂H have the highest and lowest interaction energies, respectively. In addition, energy decomposition analysis (EDA) indicated that the dispersion interaction term, ΔEdisp, significantly contributes to the host-guest interaction and is correlated with the existence of π-π van der Waals interaction. Using the nonequilibrium Greens function (NEGF) method in combination with density functional theory (DFT), the current-voltage (I-V) curves of the complexes were estimated. The conductance values increased when the guests were embedded inside the host cavity. Notably, the complex G7⊂H has the maximum conductance value. Overall, this study provided the electron transport of the PAH inclusion host-guest complex through π-π interaction and provided a direction for the fabrication of future supramolecular molecular devices.

Molecular Electronics: Creating and Bridging Molecular Junctions and Promoting Its Commercialization

Molecular electronics is driven by the dream of expanding Moore's law to the molecular level for next-generation electronics through incorporating individual or ensemble molecules into electronic circuits. For nearly 50 years, numerous efforts have been made to explore the intrinsic properties of molecules and develop diverse fascinating molecular electronic devices with the desired functionalities. The flourishing of molecular electronics is inseparable from the development of various elegant methodologies for creating nanogap electrodes and bridging the nanogap with molecules. This review first focuses on the techniques for making lateral and vertical nanogap electrodes by breaking, narrowing, and fixed modes, and highlights their capabilities, applications, merits, and shortcomings. After summarizing the approaches of growing single molecules or molecular layers on the electrodes, the methods of constructing a complete molecular circuit are comprehensively grouped into three categories: 1) directly bridging one-molecule-electrode component with another electrode, 2) physically bridging two-molecule-electrode components, and 3) chemically bridging two-molecule-electrode components. Finally, the current state of molecular circuit integration and commercialization is discussed and perspectives are provided, hoping to encourage the community to accelerate the realization of fully scalable molecular electronics for a new era of integrated microsystems and applications.

Enhanced π-π Stacking between Dipole-Bearing Single Molecules Revealed by Conductance Measurement

Dipoles are widely involved in π-π interactions and are central to many chemical and biological functions, but their influence on the strength of π-π interactions remains unclear. Here, we report a study of π-π interaction between azulene-based, polar single molecules and between naphthalene-based, nonpolar single molecules. By performing scanning tunneling microscopy break junction measurements of single-molecule conductance, we show that the π-stacked dimers formed by the azulene-based, polar aromatic structures feature higher electrical conductivity and mechanical stability than those formed by the naphthalene-based, nonpolar molecules. Mechanical control of π-π interactions in both rotational and translational motion reveals a sensitive dependence of the stacking strength on relative alignment between the dipoles. The antiparallel alignment of the dipoles was found to be the optimal stacking configuration that underpins the observed enhancement of π-π stacking between azulene-based single molecules. Density functional theory calculations further explained the observed enhancement of stacking strength and the corresponding charge transport efficiency. Our experimental and theoretical results show that the antiparallel alignment of the dipole moments significantly enhances the electronic coupling and mechanical stability of π-π stacking. In addition, in the formation of single-molecule junctions, the azulene group was experimentally and theoretically proved to form a Au-π contact with electrodes with high charge transport efficiency. This paper provides evidence and interpretation of the role of dipoles in π-π interactions at the single-molecule level and offers new insights into potential applications in supramolecular devices.

Machine Learning Prediction of the Transmission Function for Protein Sequencing with Graphene Nanoslit

Protein sequencing has rapidly changed the landscape of healthcare and life science by accelerating the growth of diagnostics and personalized medicines for a variety of fatal diseases. Next-generation nanopore/nanoslit sequencing is promising to achieve single-molecule resolution with chromosome-size-long readability. However, due to inherent complexity, high-throughput sequencing of all 20 amino acids demands different approaches. Aiming to accelerate the detection of amino acids, a general machine learning (ML) method has been developed for quick and accurate prediction of the transmission function for amino acid sequencing. Among the utilized ML models, the XGBoost regression model is found to be the most effective algorithm for fast prediction of the transmission function with a very low test root-mean-square error (RMSE ∼0.05). In addition, using the random forest ML classification technique, we are able to classify the neutral amino acids with a prediction accuracy of 100%. Therefore, our approach is an initiative for the prediction of the transmission function through ML and can provide a platform for the quick identification of amino acids with high accuracy.

Minor adjustments in the chemical structures of pyridine derivatives induced different co-assemblies by O-H⋯N hydrogen bonds

The co-adsorption behaviours of aromatic carboxylic acids with various pyridine derivatives were investigated with scanning tunneling microscopy and density functional theory. Surprisingly, minor adjustments in the chemical structures of the pyridine derivatives, such as the relative position of the nitrogen atom or the lengths of the side chains on the backbone would evidently affect the intermolecular O-H⋯N hydrogen bonds and further form various co-adsorption structures.

Predicting Finite-Bias Tunneling Current Properties from Zero-Bias Features: The Frontier Orbital Bias Dependence at an Exemplar Case of DNA Nucleotides in a Nanogap

The electrical current properties of single-molecule sensing devices based on electronic (tunneling) transport strongly depend on molecule frontier orbital energy, spatial distribution, and position with respect to the electrodes. Here, we present an analysis of the bias dependence of molecule frontier orbital properties at an exemplar case of DNA nucleotides in the gap between H-terminated (3, 3) carbon nanotube (CNT) electrodes and its relation to transversal current rectification. The electronic transport properties of this simple single-molecule device, whose characteristic is the absence of covalent bonding between electrodes and a molecule between them, were obtained using density functional theory and non-equilibrium Green's functions. As in our previous studies, we could observe two distinct bias dependences of frontier orbital energies: the so-called strong and the weak pinning regimes. We established a procedure, from zero-bias and empty-gap characteristics, to estimate finite-bias electronic tunneling transport properties, i.e., whether the molecular junction would operate in the weak or strong pinning regime. We also discuss the use of the zero-bias approximation to calculate electric current properties at finite bias. The results from this work could have an impact on the design of new single-molecule applications that use tunneling current or rectification applicable in high-sensitivity sensors, protein, or DNA sequencing.

A Guide to Signal Processing Algorithms for Nanopore Sensors

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

Identifying DNA Nucleotides via Transverse Electronic Transport in Atomically Thin Topologically Defected Graphene Electrodes

Extended line defects in graphene (ELDG) sheets have been found to be promising for biomolecule sensing applications. By means of the consistent-exchange van der Waals density-functional (vdW-DF-cx) method, the electronic, structural, and quantum transport properties of the ELDG nanogap setup has been studied when a DNA nucleotide molecule is positioned inside the nanogap electrodes. The interaction energy (E_i) values indicate charge transfer interaction between the nucleotide molecule and electrode edges. The charge density difference plots reveal that charge fluctuates around the ELDG nanogap edges adjacent to the nucleotides. This charge redistribution grounds the modulation of electronic charge transport in the ELDG nanogap device. Further, we study the electronic transverse-conductance and tunnelling current-voltage (I-V) characteristics across two closely spaced ELDG nanogap electrodes using the density functional theory and the nonequilibrium Green's function methods when a DNA nucleotide is translocated through the nanogap. Our outcomes indicate that the ELDG nano gap device could allow sequencing of DNA nucleotides with a robust and consistent yield, giving the tunneling electric current signals that vary by more than 1 order of magnitude electric current (I) for the different DNA nucleotides. So, we predict that the ELDG nanogap-based tunneling device can be suitable for sequencing DNA nucleobases.

Field Effect and Local Gating in Nitrogen-Terminated Nanopores (NtNP) and Nanogaps (NtNG) in Graphene

Functionalization of electrodes is a wide-used strategy in various applications ranging from single-molecule sensing and protein sequencing, to ion trapping, to desalination. We demonstrate, employing non-equilibrium Green's function formalism combined with density functional theory, that single-species (N, H, S, Cl, F) termination of graphene nanogap electrodes results in a strong in-gap electrostatic field, induced by species-dependent dipoles formed at the electrode ends. Consequently, the field increases or decreases electronic transport through a molecule (benzene) placed in the nanogap by shifting molecular levels by almost 2 eV in respect to the electrode Fermi level via a field effect akin to the one used for field-effect transistors. We also observed the local gating in graphene nanopores terminated with different single-species atoms. Nitrogen-terminated nanogaps (NtNGs) and nanopores (NtNPs) show the strongest effect. The in-gap potential can be transformed from a plateau-like to a saddle-like shape by tailoring NtNG and NtNP size and termination type. In particular, the saddle-like potential is applicable in single-ion trapping and desalination devices.

Functionalized carbon nanotube electrodes for controlled DNA sequencing

In the last decade, solid-state nanopores/nanogaps have attracted significant attention in the rapid detection of DNA nucleotides. However, reducing the noise through controlled translocation of the DNA nucleobases is a central issue for the development of nanogap/nanopore-based DNA sequencing to achieve single-nucleobase resolution. Furthermore, the high reactivity of the graphene pores/gaps causes clogging of the pore/gap, leading to the blockage of the pores/gaps, sticking, and irreversible pore closure. To address the prospective of functionalization of the carbon nanostructure and for accomplishing this objective, herein, we have studied the performance of functionalized closed-end cap armchair carbon nanotube (CNT) nanogap-embedded electrodes, which can improve the coupling through non-bonding electrons and may provide the possibility of N/O-H⋯π interactions with the nucleotides, as single-stranded DNA is transmigrated across the electrode. We have investigated the effect of functionalizing the closed-end cap CNT (6,6) electrodes with purine (adenine, guanine) and pyrimidine (thymine, cytosine) molecules. Weak hydrogen bonds formed between the probe molecule and the target DNA nucleobase enhance the electronic coupling and temporarily stabilize the translocating nucleobase against the orientational fluctuations, which may reduce noise in the current signal during experimental measurements. The findings of our density functional theory and non-equilibrium Green's function-based study indicate that this modeled setup could allow DNA nucleotide sequencing with a better and reliable yield, giving current traces that differ by at least 1 order of current magnitude for all the four target nucleotides. Thus, we feel that the functionalized armchair CNT (6,6) nanogap-embedded electrodes may be utilized for controlled DNA sequencing.

Combination of Single-Molecule Electrical Measurements and Machine Learning for the Identification of Single Biomolecules

The development of a next-generation DNA sequencer has provided a method for electrically measuring single molecules. Methods for electrically measuring one molecule are roughly divided into methods for measuring tunneling and ion currents. These methods enable identification of a single molecule of DNA, a RNA nucleotide, or a single protein based on current histograms. However, overlapping of current histograms of molecules with similar properties has been a major barrier to identifying single molecules with high accuracy. This barrier was broken by introducing machine learning. Combining single-molecule electrical measurement and machine learning enables high-precision identification of single molecules. Highly accurate discrimination has been demonstrated for DNA nucleotides, RNA nucleotides, amino acids, sugars, viruses, and bacteria. This combination enables quantitative evaluation of molecular recognition ability. Furthermore, a device structure suitable for high-precision identification has been designed. Combining single-molecule electrical measurement with machine learning enables digital analytical chemistry that can count certain types of molecules. Digital analytical chemistry enables comprehensive analysis of chemical reactions. This new analytical method will lead to the discovery of unknown or missed valuable molecules.

Highly Conductive Nucleotide Analogue Facilitates Base-Calling in Quantum-Tunneling-Based DNA Sequencing

Quantum-tunneling-based DNA sequencing is a single molecular technology that has great potential for achieving facile and high-throughput DNA sequencing. In principle, the sequence of DNA could be read out by the time trace of the tunnel current that can be changed according to molecular conductance of nucleobases passing through nanosized gap electrodes. However, efficient base-calling of four genetic alphabets has been seriously impeded due to the similarity of molecular conductance among canonical nucleotides. In this article, we demonstrate that replacement of canonical 2'-deoxyadenosine (dA) with a highly conductive dA analogue, 7-deaza dA, could expand the difference of molecular conductance between four genetic alphabets. Additionally, systematic evaluation of molecular conductance using a series of dA and dG analogues revealed that molecular conductance of the nucleotide is highly dependent on the HOMO level. Thus, the present study demonstrating that signal characteristics of the nucleotide can be modulated based on the HOMO level provides a widely applicable chemical approach and insight for facilitation of single molecular sensing as well as DNA sequencing based on quantum tunneling.

Recognition Tunneling of Canonical and Modified RNA Nucleotides for Their Identification with the Aid of Machine Learning

In the present study, we demonstrate a tunneling nanogap technique to identify individual RNA nucleotides, which can be used as a mechanism to read the nucleobases for direct sequencing of RNA in a solid-state nanopore. The tunneling nanogap is composed of two electrodes separated by a distance of <3 nm and functionalized with a recognition molecule. When a chemical entity is captured in the gap, it generates electron tunneling currents, a process we call recognition tunneling (RT). Using RT nanogaps created in a scanning tunneling microscope (STM), we acquired the electron tunneling signals for the canonical and two modified RNA nucleotides. To call the individual RNA nucleotides from the RT data, we adopted a machine learning algorithm, support vector machine (SVM), for the data analysis. Through the SVM, we were able to identify the individual RNA nucleotides and distinguish them from their DNA counterparts with reasonably high accuracy. Since each RNA nucleoside contains a hydroxyl group at the 2'-position of its sugar ring in an RNA strand, it allows for the formation of a tunneling junction at a larger nanogap compared to the DNA nucleoside in a DNA strand, which lacks the 2' hydroxyl group. It also proves advantageous for the manufacture of RT devices. This study is a proof-of-principle demonstration for the development of an RT nanopore device for directly sequencing single RNA molecules, including those bearing modifications.

Sensitive detection of intracellular microRNA based on a flowerlike vector with catalytic hairpin assembly

A flowerlike nanovector with horn-shaped tips is developed for in situ detection of intracellular microRNA with multiple signal outputs.