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1. Role of Intercalation on Electrical Properties of Nucleic Acids for use in Molecular Electronics

   https://doi.org/10.1039/D1NH00211B  

   Mohammad, Hashem ; Demir, Busra ; Akin, Caglanaz ; Luan, Binquan ; Hihath, Joshua ; Oren, Ersin Emre ; Anantram, M. P. ( January 2021 , Nanoscale Horizons)

   null (Ed.)

   Intercalating ds-DNA/RNA with small molecules can play an essential role in controlling the electron transmission probability for molecular electronics applications such as biosensors, single-molecule transistors, and data storage. However, its applications are limited due to a lack of understanding the nature of intercalation and electron transport mechanisms. We addressed this long-standing problem by studying the effect of intercalation on both the molecular structure and charge transport along the nucleic acids using molecular dynamics simulations and first-principle calculations coupled with Green’s function method, respectively. The study on anthraquinone and anthraquinone-neomycin conjugate intercalation into short nucleic acids reveals some universal features: 1) the intercalation affects the transmission by two mechanisms: a) inducing energy levels within the bandgap and b) shifting the location of the Fermi energy with respect to the molecular orbitals of the nucleic acid, 2) the effect of intercalation was found to be dependent on the redox state of the intercalator: while oxidized anthraquinone decreases, reduced anthraquinone increases the conductance, and 3) the sequence of intercalated nucleic acid further affects the transmission: lowering the AT-region length was found to enhance the electronic coupling of the intercalator with GC bases, hence yielding an increase of more than four times in conductance. We anticipate our study to inspire designing intercalator-nucleic acid complexes for potential use in molecular electronics via creating a multi-level gating effect. 

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2. Charge transport in individual short base stacked single-stranded RNA molecules

   https://doi.org/10.1038/s41598-023-46263-0  

   Chandra, Subrata ; Williams, Ajoke ; Maksudov, Farkhad ; Kliuchnikov, Evgenii ; Pattiya Arachchillage, Keshani G. G. ; Piscitelli, Patrick ; Castillo, Aderlyn ; Marx, Kenneth A. ; Barsegov, Valeri ; Artes Vivancos, Juan M. ( November 2023 , Scientific Reports)

   Charge transport in biomolecules is crucial for many biological and technological applications, including biomolecular electronics devices and biosensors. RNA has become the focus of research because of its importance in biomedicine, but its charge transport properties are not well understood. Here, we use the Scanning Tunneling Microscopy-assisted molecular break junction method to measure the electrical conductance of particular 5-base and 10-base single-stranded (ss) RNA sequences capable of base stacking. These ssRNA sequences show single-molecule conductance values around$$10^{-3}G_0$$${10}^{-3}{G}_0$($$G_0= 2e^2/h$$$G_0=2e^2/h$), while equivalent-length ssDNAs result in featureless conductance histograms. Circular dichroism (CD) spectra and MD simulations reveal the existence of extended ssRNA conformations versus folded ssDNA conformations, consistent with their different electrical behaviors. Computational molecular modeling and Machine Learning-assisted interpretation of CD data helped us to disentangle the structural and electronic factors underlying CT, thus explaining the observed electrical behavior differences. RNA with a measurable conductance corresponds to sequences with overall extended base-stacking stabilized conformations characterized by lower HOMO energy levels delocalized over a base-stacking mediating CT pathway. In contrast, DNA and a control RNA sequence without significant base-stacking tend to form closed structures and thus are incapable of efficient CT.

    

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3. The pivotal role of non-covalent interactions in single-molecule charge transport

   https://doi.org/10.1039/D3QM00210A  

   Ayinla, Ridwan Tobi ; Shiri, Mehrdad ; Song, Bo ; Gangishetty, Mahesh ; Wang, Kun ( May 2023 , Materials Chemistry Frontiers)

   Integrating multidisciplinary efforts from physics, chemistry, biology, and materials science, the field of single-molecule electronics has witnessed remarkable progress over the past two decades thanks to the development of single-molecule junction techniques. To date, researchers have interrogated charge transport across a broad spectrum of single molecules. While the electrical properties of covalently linked molecules have been extensively investigated, the impact of non-covalent interactions has only started to garner increasing attention in recent years. Undoubtedly, a deep understanding of both covalent and non-covalent interactions is imperative to expand the functionality and scalability of molecular-scale devices with the potential of using molecules as active components in various applications. In this review, we survey recent advances in probing how non-covalent interactions affect electron transmission through single molecules using single-molecule junction techniques. We concentrate on understanding the role of several key non-covalent interactions, including π–π and σ–σ stacking, hydrogen bonding, host–guest interactions, charge transfer complexation, and mechanically interlocked molecules. We aim to provide molecular-level insights into the structure–property relations of molecular junctions that feature these interactions from both experimental and theoretical perspectives. 

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4. Gaussian accelerated molecular dynamics: Principles and applications

   https://doi.org/10.1002/wcms.1521  

   Wang, Jinan ; Arantes, Pablo R. ; Bhattarai, Apurba ; Hsu, Rohaine V. ; Pawnikar, Shristi ; Huang, Yu‐ming M. ; Palermo, Giulia ; Miao, Yinglong ( March 2021 , WIREs Computational Molecular Science)

   Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., “Gaussian approximation”). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica‐exchange GaMD (rex‐GaMD) and replica‐exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new “selective GaMD” algorithms including the Ligand GaMD (LiGaMD) and Peptide GaMD (Pep‐GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small‐molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein–protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

   This article is categorized under:

   Structure and Mechanism > Computational Biochemistry and Biophysics

   Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods

   Molecular and Statistical Mechanics > Free Energy Methods

    

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5. Proceedings of the 29th International Conference on DNA Computing and Molecular Programming (DNA 29)

   https://doi.org/10.4230/LIPIcs.DNA.29.8  

   Petrack, Joshua ; Soloveichik, David ; Doty, David ( January 2023 , Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Chen, Ho-Lin ; Evans, Constantine G. (Ed.)

   The field of chemical computation attempts to model computational behavior that arises when molecules, typically nucleic acids, are mixed together. By modeling this physical phenomenon at different levels of specificity, different operative computational behavior is observed. Thermodynamic binding networks (TBNs) is a highly abstracted model that focuses on which molecules are bound to each other in a "thermodynamically stable" sense. Stability is measured based only on how many bonds are formed and how many total complexes are in a configuration, without focusing on how molecules are binding or how they became bound. By defocusing on kinetic processes, TBNs attempt to naturally model the long-term behavior of a mixture (i.e., its thermodynamic equilibrium). We study the problem of signal amplification: detecting a small quantity of some molecule and amplifying its signal to something more easily detectable. This problem has natural applications such as disease diagnosis. By focusing on thermodynamically favored outcomes, we seek to design chemical systems that perform the task of signal amplification robustly without relying on kinetic pathways that can be error prone and require highly controlled conditions (e.g., PCR amplification). It might appear that a small change in concentrations can result in only small changes to the thermodynamic equilibrium of a molecular system. However, we show that it is possible to design a TBN that can "exponentially amplify" a signal represented by a single copy of a monomer called the analyte: this TBN has exactly one stable state before adding the analyte and exactly one stable state afterward, and those two states "look very different" from each other. In particular, their difference is exponential in the number of types of molecules and their sizes. The system can be programmed to any desired level of resilience to false positives and false negatives. To prove these results, we introduce new concepts to the TBN model, particularly the notions of a TBN’s entropy gap to describe how unlikely it is to be observed in an undesirable state, and feed-forward TBNs that have a strong upper bound on the number of polymers in a stable configuration. We also show a corresponding negative result: a doubly exponential upper bound, meaning that there is no TBN that can amplify a signal by an amount more than doubly exponential in the number and sizes of different molecules that comprise it. We leave as an open question to close this gap by either proving an exponential upper bound, or giving a construction with a doubly-exponential difference between the stable configurations before and after the analyte is added. Our work informs the fundamental question of how a thermodynamic equilibrium can change as a result of a small change to the system (adding a single molecule copy). While exponential amplification is traditionally viewed as inherently a non-equilibrium phenomenon, we find that in a strong sense exponential amplification can occur at thermodynamic equilibrium as well - where the "effect" (e.g., fluorescence) is exponential in types and complexity of the chemical components. 

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