Published papers

© 2017 Informa UK Limited, trading as Taylor & Francis Group. In recent years, many studies on a molecular motor have been conducted in the fields of biorheology and nanoengineering. The molecular motor is a molecule that converts the chemical energy obtained by ATP hydrolysis into mechanical energy. Explaining this mechanism is important for nanoengineering. A kinesin, which is a type of molecular motor, has the characteristics to move on a microtubule with hand-over-hand steps. The kinesin walking behaviour is explained by the ‘asymmetric Brownian ratchet model’. Previously, we had suggested that the walking mechanism was achieved by the bubble formation in a nanosized channel surrounded by hydrophobic atoms with the transition between the two states–bubble state and liquid state. However, the walking behaviour of the model motor was different from that of a single molecule measurement of a kinesin. In this study, we constructed a new motor system focused on the asymmetric binding affinity of a motor protein and performed a model simulation using the dissipative particle dynamics method. As a result, it was observed that hand-over-hand walking depends on the transition position ratio and the transition frequency coefficient. Moreover, the efficiency of the new motor system is higher than that of the previous motor systems. The new motor model can provide a simulation guide for the design of biomimetic nanomachines.

The "asymmetric Brownian ratchet model", a variation of Feynman's ratchet and pawl system, is invoked to understand the kinesin walking behavior along a microtubule. The model system, consisting of a motor and a rail, can exhibit two distinct binding states, namely, the random Brownian state and the asymmetric potential state. When the system is transformed back and forth between the two states, the motor can be driven to "walk" in one direction. Previously, we suggested a fundamental mechanism, that is, bubble formation in a nanosized channel surrounded by hydrophobic atoms, to explain the transition between the two states. In this study, we propose a more realistic and viable switching method in our computer simulation of molecular motor walking. Specifically, we propose a thermosensitive polymer model with which the transition between the two states can be controlled by temperature pulses. Based on this new motor system, the stepping size and stepping time of the motor can be recorded. Remarkably, the "walking" behavior observed in the newly proposed model resembles that of the realistic motor protein. The bubble formation based motor not only can be highly efficient but also offers new insights into the physical mechanism of realistic biomolecule motors. © 2013 American Chemical Society.

We propose a water pump that actively transports water molecules through nanochannels. Spatially asymmetric thermal fluctuations imposed on the channel radius cause unidirectional water flow without osmotic pressure, which can be attributed to hysteresis in the cyclic transition between the wetting/drying states. We show that the water transport depends on fluctuations, such as white, Brownian, and pink noises. Because of the high-frequency components in white noise, fast switching of open and close states inhibits channel wetting. Conversely, pink and Brownian noises generate high-pass filtered net flow. Brownian fluctuation leads to a faster water transport rate, whereas pink noise has a higher capability to overcome osmotic pressure in the opposite direction. A trade-off relationship exists between the resonant frequency of the fluctuation and the flow amplification. The proposed pump can be considered as an analogy for the reversed Carnot cycle, which is the upper limit on the energy conversion efficiency.

Molecular dynamics (MD) simulations, which are central to drug discovery, offer detailed insights into protein-ligand interactions. However, analyzing large MD datasets remains a challenge. Current machine-learning solutions are predominantly supervised and have data labelling and standardisation issues. In this study, we adopted an unsupervised deep-learning framework, previously benchmarked for rigid proteins, to study the more flexible SARS-CoV-2 main protease (Mpro). We ran MD simulations of Mpro with various ligands and refined the data by focusing on binding-site residues and time frames in stable protein conformations. The optimal descriptor chosen was the distance between the residues and the center of the binding pocket. Using this approach, a local dynamic ensemble was generated and fed into our neural network to compute Wasserstein distances across system pairs, revealing ligand-induced conformational differences in Mpro. Dimensionality reduction yielded an embedding map that correlated ligand-induced dynamics and binding affinity. Notably, the high-affinity compounds showed pronounced effects on the protein's conformations. We also identified the key residues that contributed to these differences. Our findings emphasize the potential of combining unsupervised deep learning with MD simulations to extract valuable information and accelerate drug discovery.

In recent years, Janus amphiphilic nanotubes with complex surfaces have been synthesized. However, the self-assembly behaviour of surfactant solutions confined in a Janus amphiphilic nanotube has not been investigated so far. We performed molecular simulations to investigate the morphologies and phase diagrams of a surfactant confined in Janus amphiphilic nanotube consisting of both hydrophobic and hydrophilic surfaces. We derived a phase diagram of the representative snapshots of equilibrium morphologies. Morphologies that were not observed in the bulk eventuated in confined systems. Moreover, the self-assembled structures were found to be dependent on the spatial confinement. Furthermore, the self-assembled structures confined in hydroneutral and Janus amphiphilic nanotubes were compared. The results suggested that the self-assembled structures confined in the Janus amphiphilic nanotube resembled that confined in the hydroneutral nanotube owing to a strong confinement effect. Further developments in controlling the morphologies and self-assemblies will greatly advance their applications of these materials in nanofluidic devices, or for nanopatterning.

We study self-assembly and polymorphic transitions of surfactant molecules in water within a nanotube and the effect of water-nanotube interactions on the self-assembly morphologies. We present a simulation evidence of a cornucopia of polymorphic structures of surfactant assemblies-many of which have not been observed in bulk solutions-through adjusting the water-nanotube chemical interactions which range from hydrophilic to hydroneutral and to hydrophobic. The ability to control the morphologies of surfactant assemblies within nanoscale confinement can be used for patterning the interior surface of nanochannels for application in nanofluidics and nanomedical devices.

We have performed molecular simulations to investigate morphologies and the phase diagram of the self-assembled triblock Janus nanoparticle confined to nanotubes. The triblock Janus nanoparticle is decorated with two hydrophobic caps at the north and south poles with a tunable area, separated by an electrically charged middle band. On the basis of the observed pressure- and tube-radius-dependent morphologies, we derive semiquantitative phase diagrams of the axial pressure versus the ratio of the radius of the nanoparticle to the radius of the nanotube. Three distinct walls of the nanotube, namely, hydrophobic, hydrophilic, and hydroneutral, are considered. We find that the three phase diagrams corresponding to three chemically different walls of the nanotube show some universal features. These features can be illustrated through a schematic assembly map and a roadmap on the variation of coordination number of the nanoparticles. In particular, we find that highly ordered morphologies tend to form when the coordination number of Janus particles is a multiple of 2. The orientation ordering and self-assembly behavior of the Janus nanoparticles can be qualitatively predicted when the chemical nature of the nanotube wall is known.

More than 100 mu s dissipative particle dynamics simulations were carried out to investigate the spontaneous formation process of threadlike micelles from the random configuration for surfactant molecules. Stable spherical micelles were formed during the earlier stage. These spherical micelles fused to each other and grew into rodlike and threadlike micelles during the later stage. The length and radius of a micelle were estimated by tracing the backbone positions and the distance between the head group particles and the backbone of the micelles, respectively. The ratio of the largest to the smallest principal moments of inertia for each micelle was calculated as the micelle shape. (c) 2007 American Institute of Physics.

This journal is © The Royal Society of Chemistry. We study the structure formation and flow properties of colloidal dispersions comprised of Janus spheres, Janus spherocylinders, and their mixtures, using hybrid molecular dynamics simulations that take into account hydrodynamic interactions. We systematically vary the Janus balance and the shape anisotropy of the particles, and explore a range of colloid volume fractions in the liquid regime of the phase diagram. At rest, Janus spheres with small hydrophobic patches form spherical micelles for all investigated colloid concentrations. In contrast, Janus spheres with an entirely hydrophobic hemisphere aggregate to larger worm-like micelles and network-like structures. Janus spherocylinders exhibit a similar self-assembly behavior. At small and intermediate shear, we observe deformation and rearrangement of the micelles, accompanied by a Newtonian-like rheology with slightly higher shear viscosity compared to homoparticle dispersions at the same concentration. As the shear rate is increased further, the micelles eventually break up into small dimers and free particles, causing a distinct shear-thinning of the dispersions. The network-like structures exhibit a similar flow behavior at high shear rates, but for weak shear we find an almost threefold increase of the shear viscosity and a distinct shear-thinning behavior due to the fracturing of the intertwined networks. In general, we identify a strong correlation between the size of the aggregates and the rheology of the dispersions, allowing for the determination of dynamic properties solely based on structural information.

:This paper presents a fundamental theory of nanobubble formation and induced force in confined nanochannels. It is shown that nanobubble formation between hydrophobic plates can be predicted from their surface tension and geometry, with estimated values for the surface free energy and the force acting on the plates in good agreement with the results of molecular dynamics simulation and experimentation. When a bubble is formed between two plates, vertical attractive force and horizontal retract force due to the shifted plates are applied to the plates. The net force exerted on the plates is not dependent on the distance between them. The short-range force between hydrophobic surfaces due to hydrophobic interaction appears to correspond to the force estimated by our theory. We compared between experimental and theoretical values for the binding energy of a molecular motor system to validate our theory. The tendency that the binding energy increases as the size of the protein increases is consistent with the theory.

The mechanisms underlying the thermal conductivity behavior of nanofluids have not been completely clarified thus far. This is due to the various competing factors and the lack of a molecular-level understanding of the heat transfer enhancement of nanofluids. In this study, energy-conserving dissipative particle dynamics simulations were conducted to investigate the effects of the self-assembly of nanoparticles (NPs) on the nanoscale heat transfer properties. We demonstrated that considering the balance between the effects of the distance between the NPs and the solvent and the enhancement in thermal conductivity on adding NPs is important for controlling the thermal conductivity of nanofluids.

Nanoparticles exhibit diverse self-assembly attributes and are expected to be applicable under unique settings. For instance, biomolecules can be sandwiched between dimer nanoparticles and detected by surface-enhanced Raman scattering. Controlling the gap between extremely close dimers and stably capturing the target molecule in the gap are crucial aspects of this strategy. Therefore, polymer-tethered nanoparticles (PTNPs), which show promise as high-performance materials that exhibit the attractive features of both NPs and polymers, were targeted in this study to achieve stable biomolecule sensing. Using coarse-grained molecular dynamics simulations, the dependence of the PTNP interactions on the length of the grafted polymer, graft density, and coverage ratio of a hydrophobic tether were examined. The results indicated that the smaller the tether length and graft density, the smaller was the distance between the PTNP surfaces ((Formula presented.)). In contrast, (Formula presented.) decreased as the coverage ratio of the hydrophobic surface ((Formula presented.)) increased. The sandwiching probability of the sensing target increased in proportion to the coverage ratio. At high (Formula presented.) values, the PTNPs aggregated into three or more particles, which hindered their sensing attributes. These results provide fundamental insight into the sensing applications of NPs and demonstrate the usefulness of PTNPs in sensing biomolecules.

In the case of covalent polymers, immiscible polymers can be integrated by covalently linking them together, but such a strategy is not possible in supramolecular polymers. Here we report the supramolecular copolymerization of two porphyrin-based monomers, C10P2H and TEGPCu with side chains bearing cyanobiphenyl (CB) groups at the ends of hydrophobic alkyl or hydrophilic tetraethylene glycol chains, respectively. These monomers undergo self-sorting supramolecular polymerization in highly diluted solutions ([monomer] = 3.4 × 10−9 mol% (2.0 × 10−8 mol L−1)) in nonpolar media due to the incompatibility of the side chains. Surprisingly, these monomers undergo supramolecular copolymerization under high concentration conditions ([monomer] = 7.7 mol%) in the medium of 4-cyano-4′-pentyloxybiphenyl (5OCB) to form a columnar liquid crystalline phase under thermodynamic conditions, where the individual columns are composed of supramolecular block copolymers. The combination of CB ends of both monomers and the 5OCB medium is essential for the two monomers to form an integrated structure in a condensed system without phase separation.

Bio-inspired (biomimetic) materials, which are inspired by living organisms, offer exciting opportunities for the development of advanced functionalities. Among them, bio-inspired superhydrophobic surfaces have attracted considerable interest due to their potential applications in self-cleaning surfaces and reducing fluid resistance. Although the mechanism of superhydrophobicity is understood to be the free energy barrier between the Cassie and Wenzel states, the solid-surface technology to control the free energy barrier is still unclear. Therefore, previous studies have fabricated solid surfaces with desired properties through trial and error by measuring contact angles. In contrast, our study directly evaluates the free energy barrier using molecular simulations and attempts to relate it to solid-surface parameters. Through a series of simulations, we explore the behavior of water droplets on surfaces with varying values of surface pillar spacing and surface pillar height. The results show that the free energy barrier increases significantly as the pillar spacing decreases and/or as the pillar height increases. Our study goes beyond traditional approaches by exploring the relationship between free energy barriers, surface parameters, and hydrophobicity, providing a more direct and quantified method to evaluate surface hydrophobicity. This knowledge contributes significantly to material design by providing valuable insights into the relationship between surface parameters, free energy barriers, and hydrophilicity/hydrophobicity.

Graphene and graphene oxide (GO) are promising two-dimensional nanomaterials. An ultimate goal is to achieve large-scale bottom-up syntheses of perfect graphene and GO. However, controlled syntheses of perfect graphitic structures still remain challenges in chemistry and materials science. Moreover, amorphous types have not received much attention. The present work shows syntheses, structures, and applications of amorphous graphene and GO analogues alternative to the ideal ones. The simultaneous multiple reactions of two conjugated monomers provide amorphous conjugated polymer networks containing low-crystalline graphitic domains and their stacking. The stacked amorphous graphene and GO are exfoliated into thin nanosheets including few-layers and monolayers. Moreover, in situ syntheses of the amorphous GO analogues are applied to obtain a reinforced plastic with high mechanical strength. The present work implies that various functional nanocarbons can be designed and synthesized by tailored combinations of conjugated monomers.

Tail unsaturation is a standard design lever in emulsifier formulation, yet its coverage-dependent link to oil–water interfacial tension remains incomplete. Here we combine pendant-drop tensiometry with atomistic molecular dynamics (MD) using the mechanical (pressure-tensor) route to establish a quantitative structure–property for two monoglycerides that differ only in tail chemistry: monopalmitin (saturated) and monoolein (cis-unsaturated) at the triolein–saline interface. Experiments show that the unsaturated analogue lowers interfacial tension more effectively across comparable surface coverages. MD reproduces the coverage-resolved trends and attributes the difference to packing frustration from the cis double bond, which yields more disordered/fluid monolayers, greater interfacial thickness, enhanced headgroup hydration (higher hydrogen-bond occupancy and larger solvent-accessible surface area), and reduced short-range lateral order relative to the saturated analogue. These results establish a coverage-resolved structure–property linking tail chemistry to interfacial organization and to macroscopic interfacial tension, providing practical guidance for selecting and blending glyceride-based emulsifiers under formulation-relevant conditions.