Solid-state thermal rectification of bilayers by asymmetric elastic modulus.

A highly efficient thermal rectification applicable to large panels still needs to be developed. Here, we experimentally achieve a high thermal rectification efficiency of 33% by carefully engineering elastic modulus asymmetry in a centimeter-scale bilayered silver-graphene oxide sponge. The thermal conduction primarily occurs in the out-of-plane direction, and the forward heat flow direction is from the hard silver to the soft graphene oxide. Surprisingly, the forward heat flow direction is reversed when a silver layer is formed on a harder polystyrene foam. The forward direction is always from the harder side to the softer side, and the asymmetry in elastic modulus is suggested as a possible mechanism based on the one-dimensional Frenkel-Kontorova (FK) model. The finite element analysis indicates that other mechanisms such as temperature-dependent thermal conductivity and radiation asymmetry cannot explain the high rectification efficiency. This scalable work over a wide temperature range may find immediate industrial applications.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures.

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Raman Scattering Measurement of Suspended Graphene under Extreme Strain Induced by Nanoindentation.

Graphene is known as a superstiff and extremely strong material. Hence, applying strains greater than 1% to graphene and simultaneously measuring changes in its physical properties has been challenging because of the limited methodologies for measuring both high strain and other physical properties. Here, Raman scattering measurement of suspended graphene under extremely high biaxial strain as large as 6.1% using an atomic force microscopy (AFM)-Raman spectroscopy measurement tool is reported. Nanoindentation is performed using AFM tips machined to have a flat top and a hole shape, resulting in a strained graphene area sufficiently large to enable the acquisition of a Raman signal. At the same time, the laser light is focused on the strained flat area of the graphene membrane. The Raman signals of the G and 2D bands of graphene are redshifted by 282 and 684 cm-1 , respectively, which is unprecedented for graphene. This measurement technique provides an effective methodology to measure variations in the physical properties of atomically thin materials under superhigh strain.

Protein conformational transitions explored by a morphing approach based on normal mode analysis in internal coordinates.

Large-scale conformational changes are essential for proteins to function properly. Given that these transition events rarely occur, however, it is challenging to comprehend their underlying mechanisms through experimental and theoretical approaches. In this study, we propose a new computational methodology called internal coordinate normal mode-guided elastic network interpolation (ICONGENI) to predict conformational transition pathways in proteins. Its basic approach is to sample intermediate conformations by interpolating the interatomic distance between two end-point conformations with the degrees of freedom constrained by the low-frequency dynamics afforded by normal mode analysis in internal coordinates. For validation of ICONGENI, it is applied to proteins that undergo open-closed transitions, and the simulation results (i.e., simulated transition pathways) are compared with those of another technique, to demonstrate that ICONGENI can explore highly reliable pathways in terms of thermal and chemical stability. Furthermore, we generate an ensemble of transition pathways through ICONGENI and investigate the possibility of using this method to reveal the transition mechanisms even when there are unknown metastable states on rough energy landscapes.

Selective HDAC8 Inhibition Attenuates Isoproterenol-Induced Cardiac Hypertrophy and Fibrosis via p38 MAPK Pathway.

Histone deacetylase (HDAC) expression and enzymatic activity are dysregulated in cardiovascular diseases. Among Class I HDACs, HDAC2 has been reported to play a key role in cardiac hypertrophy; however, the exact function of HDAC8 remains unknown. Here we investigated the role of HDAC8 in cardiac hypertrophy and fibrosis using the isoproterenol-induced cardiac hypertrophy model system.Isoproterenol-infused mice were injected with the HDAC8 selective inhibitor PCI34051 (30 mg kg-1 body weight). Enlarged hearts were assessed by HW/BW ratio, cross-sectional area, and echocardiography. RT-PCR, western blotting, histological analysis, and cell size measurements were performed. To elucidate the role of HDAC8 in cardiac hypertrophy, HDAC8 knockdown and HDAC8 overexpression were also used. Isoproterenol induced HDAC8 mRNA and protein expression in mice and H9c2 cells, while PCI34051 treatment decreased cardiac hypertrophy in isoproterenol-treated mice and H9c2 cells. PCI34051 treatment also reduced the expression of cardiac hypertrophic markers (Nppa, Nppb, and Myh7), transcription factors (Sp1, Gata4, and Gata6), and fibrosis markers (collagen type I, fibronectin, and Ctgf) in isoproterenol-treated mice. HDAC8 overexpression stimulated cardiac hypertrophy in cells, whereas HDAC8 knockdown reversed those effects. HDAC8 selective inhibitor and HDAC8 knockdown reduced the isoproterenol-induced activation of p38 MAPK, whereas HDAC8 overexpression promoted p38 MAPK phosphorylation. Furthermore, p38 MAPK inhibitor SB203580 significantly decreased the levels of p38 MAPK phosphorylation, as well as ANP and BNP protein expression, induced by HDAC8 overexpression.Here we show that inhibition of HDAC8 activity or expression suppresses cardiac hypertrophy and fibrosis. These findings suggest that HDAC8 could be a promising target to treat cardiac hypertrophy and fibrosis by regulating p38 MAPK.

Effects of aquaporin-lipid molar ratio on the permeability of an aquaporin Z-phospholipid membrane system.

Aquaporins are water-permeable membrane-channel proteins found in biological cell membranes that selectively exclude ions and large molecules and have high water permeability, which makes them promising candidates for water desalination systems. To effectively apply the properties of aquaporins in the desalination process, many studies have been conducted on aquaporin-lipid membrane systems using phospholipids, which are the main component of cell membranes. Many parametric studies have evaluated the permeability of such systems with various aquaporin types and lipid compositions. In this study, we performed molecular dynamics simulations for four cases with different protein-lipid molar ratios (1:50, 1:75, 1:100, and 1:150) between aquaporin Z and the phospholipids, and we propose a possibility of the existence of optimal protein-lipid molar ratio to maximize water permeability. Elucidating these simulation results from a structural viewpoint suggests that there is a relationship between the permeability and changes in the hydrophobic thickness of the lipid membrane adjacent to the aquaporin as a structural parameter. The results of this study can help optimize the design of an aquaporin-lipid membrane by considering its molar ratio at an early stage of development.

Electron tunneling of hierarchically structured silver nanosatellite particles for highly conductive healable nanocomposites.

Healable conductive materials have received considerable attention. However, their practical applications are impeded by low electrical conductivity and irreversible degradation after breaking/healing cycles. Here we report a highly conductive completely reversible electron tunneling-assisted percolation network of silver nanosatellite particles for putty-like moldable and healable nanocomposites. The densely and uniformly distributed silver nanosatellite particles with a bimodal size distribution are generated by the radical and reactive oxygen species-mediated vigorous etching and reduction reaction of silver flakes using tetrahydrofuran peroxide in a silicone rubber matrix. The close work function match between silicone and silver enables electron tunneling between nanosatellite particles, increasing electrical conductivity by ~5 orders of magnitude (1.02×103 Scm-1) without coalescence of fillers. This results in ~100% electrical healing efficiency after 1000 breaking/healing cycles and stability under water immersion and 6-month exposure to ambient air. The highly conductive moldable nanocomposite may find applications in improvising and healing electrical parts.

Fabrication and Characterization of Finite-Size DNA 2D Ring and 3D Buckyball Structures.

In order to incorporate functionalization into synthesized DNA nanostructures, enhance their production yield, and utilize them in various applications, it is necessary to study their physical stabilities and dynamic characteristics. Although simulation-based analysis used for DNA nanostructures provides important clues to explain their self-assembly mechanism, structural function, and intrinsic dynamic characteristics, few studies have focused on the simulation of DNA supramolecular structures due to the structural complexity and high computational cost. Here, we demonstrated the feasibility of using normal mode analysis for relatively complex DNA structures with larger molecular weights, i.e., finite-size DNA 2D rings and 3D buckyball structures. The normal mode analysis was carried out using the mass-weighted chemical elastic network model (MWCENM) and the symmetry-constrained elastic network model (SCENM), both of which are precise and efficient modeling methodologies. MWCENM considers both the weight of the nucleotides and the chemical bonds between atoms, and SCENM can obtain mode shapes of a whole structure by using only a repeated unit and its connectivity with neighboring units. Our results show the intrinsic vibrational features of DNA ring structures, which experience inner/outer circle and bridge motions, as well as DNA buckyball structures having overall breathing and local breathing motions. These could be used as the fundamental basis for designing and constructing more complicated DNA nanostructures.

Normal mode analysis of Zika virus.

In recent years, Zika virus (ZIKV) caused a new pandemic due to its rapid spread and close relationship with microcephaly. As a result, ZIKV has become an obvious global health concern. Information about the fundamental viral features or the biological process of infection remains limited, despite considerable efforts. Meanwhile, the icosahedral shell structure of the mature ZIKV was recently revealed by cryo-electron microscopy. This structural information enabled us to simulate ZIKV. In this study, we analyzed the dynamic properties of ZIKV through simulation from the mechanical viewpoint. We performed normal mode analysis (NMA) for a dimeric structure of ZIKV consisting of the envelope proteins and the membrane proteins as a unit structure. By analyzing low-frequency normal modes, we captured intrinsic vibrational motions and defined basic vibrational properties of the unit structure. Moreover, we also simulated the entire shell structure of ZIKV at the reduced computational cost, similar to the case of the unit structure, by utilizing its icosahedral symmetry. From the NMA results, we can not only comprehend the putative dynamic fluctuations of ZIKV but also verify previous inference such that highly mobile glycosylation sites would play an important role in ZIKV. Consequently, this theoretical study is expected to give us an insight on the underlying biological functions and infection mechanism of ZIKV.

Facilitated Water Transport through Graphene Oxide Membranes Functionalized with Aquaporin-Mimicking Peptides.

Water purification by membranes is widely investigated to address concerns related to the scarcity of clean water. Achieving high flux and rejection simultaneously is a difficult challenge using such membranes because these properties are mutually exclusive in common artificial membranes. Nature has developed a method for this task involving water-channel membrane proteins known as aquaporins. Here, the design and fabrication of graphene oxide (GO)-based membranes with a surface-tethered peptide motif designed to mimic the water-selective filter of natural aquaporins is reported. The short RF8 (RFRFRFRF, where R and F represent arginine and phenylalanine, respectively) octapeptide is a concentrated form of the core component of the Ar/R (aromatic/arginine) water-selective filter in aquaporin. The resulting GO-RF8 shows superior flux and high rejection similar to natural aquaporins. Molecular dynamics simulation reveal the unique configuration of RF8 peptides and the transport of water in GO-RF8 membranes, supporting that RF8 effectively emulates the core function of aquaporins.

Understanding carbon nanotube channel formation in the lipid membrane.

Carbon nanotubes (CNTs) have been considered a prominent nano-channel in cell membranes because of their prominent ion-conductance and ion-selectivity, offering agents for a biomimetic channel platform. Using a coarse-grained molecular dynamics simulation, we clarify a construction mechanism of vertical CNT nano-channels in a lipid membrane for a long period, which has been difficult to observe in previous CNT-lipid interaction simulations. The result shows that both the lipid coating density and length of CNT affect the suitable fabrication condition for a vertical and stable CNT channel. Also, simulation elucidated that a lipid coating on the surface of the CNT prevents the CNT from burrowing into the lipid membrane and the vertical channel is stabilized by the repulsion force between the lipids in the coating and membrane. Our study provides an essential understanding of how CNTs can form stable and vertical channels in the membrane, which is important for designing new types of artificial channels as biosensors for bio-fluidic studies.

Dynamic characteristics of a flagellar motor protein analyzed using an elastic network model.

At the base of a flagellar motor, its rotational direction and speed are regulated by the interaction between rotor and stator proteins. A switching event occurs when the cytoplasmic rotor protein, called C-ring, changes its conformation in response to binding of the CheY signal protein. The C-ring structure consists of FliG, FliM, and FliN proteins and its conformational changes in FliM and FliG including HelixMC play an important role in switching the motor direction. Therefore, clarifying their dynamic properties as well as conformational changes is a key to understanding the switching mechanism of the motor protein. In this study, to elucidate dynamic characteristics of the C-ring structure, both harmonic (intrinsic vibration) and anharmonic (transition pathway) analyses are conducted by using the symmetry-constrained elastic network model. As a result, the first three normal modes successfully capture the essence of transition pathway from wild type to CW-biased state. Their cumulative square overlap value reaches up to 0.842. Remarkably, it is also noted from the transition pathway that the cascade of interactions from the signal protein to FliM to FliG, highlighted by the major mode shapes from the first three normal modes, induces the reorientation (∼100° rotation of FliGC5) of FliG C-terminal that directly interacts with the stator protein. Presumably, the rotational direction of the motor protein is switched by this substantial change in the stator-rotor interaction.

Normal mode-guided transition pathway generation in proteins.

The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this.

Computational Simulation of the Activation Cycle of Gα Subunit in the G Protein Cycle Using an Elastic Network Model.

Agonist-activated G protein-coupled receptors (GPCRs) interact with GDP-bound G protein heterotrimers (Gαßγ) promoting GDP/GTP exchange, which results in dissociation of Gα from the receptor and Gßγ. The GTPase activity of Gα hydrolyzes GTP to GDP, and the GDP-bound Gα interacts with Gßγ, forming a GDP-bound G protein heterotrimer. The G protein cycle is allosterically modulated by conformational changes of the Gα subunit. Although biochemical and biophysical methods have elucidated the structure and dynamics of Gα, the precise conformational mechanisms underlying the G protein cycle are not fully understood yet. Simulation methods could help to provide additional details to gain further insight into G protein signal transduction mechanisms. In this study, using the available X-ray crystal structures of Gα, we simulated the entire G protein cycle and described not only the steric features of the Gα structure, but also conformational changes at each step. Each reference structure in the G protein cycle was modeled as an elastic network model and subjected to normal mode analysis. Our simulation data suggests that activated receptors trigger conformational changes of the Gα subunit that are thermodynamically favorable for opening of the nucleotide-binding pocket and GDP release. Furthermore, the effects of GTP binding and hydrolysis on mobility changes of the C and N termini and switch regions are elucidated. In summary, our simulation results enabled us to provide detailed descriptions of the structural and dynamic features of the G protein cycle.

Structural insights into the mechanism defining substrate affinity in Arabidopsis thaliana dUTPase: the role of tryptophan 93 in ligand orientation.

BACKGROUND: Deoxyuridine triphosphate nucleotidohydrolase (dUTPase) hydrolyzes dUTP to dUMP and pyrophosphate to maintain the cellular thymine-uracil ratio. dUTPase is also a target for cancer chemotherapy. However, the mechanism defining its substrate affinity remains unclear. Sequence comparisons of various dUTPases revealed that Arabidopsis thaliana dUTPase has a unique tryptophan at position 93, which potentially contributes to its degree of substrate affinity. To better understand the roles of tryptophan 93, A. thaliana dUTPase was studied. RESULTS: Enzyme assays showed that A. thaliana dUTPase belongs to a high-affinity group of isozymes, which also includes the enzymes from Escherichia coli and Mycobacterium tuberculosis. Enzymes from Homo sapiens and Saccharomyces cerevisiae are grouped as low-affinity dUTPases. The structure of the homo-trimeric A. thaliana dUTPase showed three active sites, each with a different set of ligand interactions between the amino acids and water molecules. On an α-helix, tryptophan 93 appears to keep serine 89 in place via a water molecule and to specifically direct the ligand. Upon being oriented in the active site, the C-terminal residues close the active site to promote the reaction. CONCLUSIONS: In the high-affinity group, the prefixed direction of the serine residues was oriented by a positively charged residue located four amino acids away, while low-affinity enzymes possess small hydrophobic residues at the corresponding sites.

Investigation of Ion Channel Activities of Gramicidin A in the Presence of Ionic Liquids Using Model Cell Membranes.

Ionic liquids (ILs) are considered to be green solvents because of their non-volatility. Although ILs are relatively safe in the atmospheric environment, they may be toxic in other environments. Our previous research showed that the cytotoxicity of ILs to biological organisms is attributable to interference with cell membranes by IL insertion. However, the effects of ILs on ion channels, which play important roles in cell homeostasis, have not been comprehensively studied to date. In this work, we studied the interactions between ILs and lipid bilayer membranes with gramicidin A ion channels. We used two methods, namely electrical and fluorescence measurements of ions that permeate the membrane. The lifetimes of channels were increased by all the ILs tested in this work via stabilizing the compressed structure of the lipid bilayer and the rate of ion flux through gA channels was decreased by changing the membrane surface charge. The former effect, which increased the rate of ion flux, was dominant at high salt concentrations, whereas the latter, which decreased the rate of ion flux, was dominant at low salt concentrations. The effects of ILs increased with increasing concentration and alkyl chain length. The experimental results were further studied using molecular dynamics simulations.

Robust elastic network model: A general modeling for precise understanding of protein dynamics.

In the study of protein dynamics relevant to functions, normal mode analysis based on elastic network models (ENMs) has become popular. These models are usually validated by comparing the calculated atomic fluctuation for a single protein in a vacuum to experimental temperature factors in the crystal packing state. Without reflecting the crystal packing effect, in addition, their arbitrary assignment of spring constants leads to inaccurate simulation results, yielding a low correlation of the B-factor. To overcome this limitation, we propose a robust elastic network model (RENM) that not only considers the crystalline effect by using symmetric constraint information but also uses lumped masses and specific spring constants based on the type of amino acids and chemical interactions, respectively. Simulation results with more than 500 protein structures verify qualitatively and quantitatively that one can obtain the better correlation of the B-factor by RENM without additional computational burden. Moreover, an optimal spring constant in physical units (dyne/cm) is quantitatively determined as a function of the temperature at 100 and 290K, which enables us to predict the atomic fluctuations and vibrational density of states (VDOS) without a fitting process. The additional investigation of 80 high-resolution crystal structures with anisotropic displacement parameters (ADPs) indicates that RENM could give a full description of vibrational characteristics of individual residues in proteins.

Vibrational characteristics of graphene sheets elucidated using an elastic network model.

Recent studies of graphene have demonstrated its great potential for highly sensitive resonators. In order to capture the intrinsic vibrational characteristics of graphene, we propose an atomistic modeling method called the elastic network model (ENM), in which a graphene sheet is modeled as a mass-spring network of adjacent atoms connected by various linear springs with specific bond ratios. Normal mode analysis (NMA) reveals the various vibrational features of bi-layer graphene sheets (BLGSs) clamped at two edges. We also propose a coarse-graining (CG) method to extend our graphene study into the meso- and macroscales, at which experimental measurements and synthesis of graphene become practical. The simulation results show good agreement with experimental observations. Therefore, the proposed ENM approach will not only shed light on the theoretical study of graphene mechanics, but also play an important role in the design of highly-sensitive graphene-based resonators.

Opening and closing of a toroidal group II chaperonin revealed by a symmetry constrained elastic network model.

Recently, the atomic structures of both the closed and open forms of Group 2 chaperonin protein Mm-cpn were revealed through crystallography and cryo-electron microscopy. This toroidal-like chaperonin is composed of two eightfold rings that face back-to-back. To gain a computational advantage, we used a symmetry constrained elastic network model (SCENM), which requires only a repeated subunit structure and its symmetric connectivity to neighboring subunits to simulate the entire system. In the case of chaperonin, only six subunits (i.e., three from each ring) were used out of the eight subunits comprising each ring. A smooth and symmetric pathway between the open and closed conformations was generated by elastic network interpolation (ENI). To support this result, we also performed a symmetry-constrained normal mode analysis (NMA), which revealed the intrinsic vibration features of the given structures. The NMA and ENI results for the representative single subunit were duplicated according to the symmetry pattern to reconstruct the entire assembly. To test the feasibility of the symmetry model, its results were also compared with those obtained from the full model. This study allowed the folding mechanism of chaperonin Mm-cpn to be elucidated by SCENM in a timely manner.

Ternary and senary representations using DNA double-crossover tiles.

The information capacity of DNA double-crossover (DX) tiles was successfully increased beyond a binary representation to higher base representations. By controlling the length and the position of DNA hairpins on the DX tile, ternary and senary (base-3 and base-6) digit representations were realized and verified by atomic force microscopy. Also, normal mode analysis was carried out to study the mechanical characteristics of each structure.