A novel betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused a large respiratory outbreak in Wuhan, China in December 2019, is currently spreading across many countries globally. Here, we show that a TMPRSS2expressing VeroE6 cell line is highly susceptible to SARS-CoV-2 infection, making it useful for isolating and propagating SARS-CoV-2. Our results reveal that, in common with SARS-and Middle East respiratory syndrome-CoV, SARS-CoV-2 infection is enhanced by TMPRSS2.

Upon cooling, water freezes to ice. This familiar phase transition occurs widely in nature, yet unlike the freezing of simple liquids, it has never been successfully simulated on a computer. The difficulty lies with the fact that hydrogen bonding between individual water molecules yields a disordered three-dimensional hydrogen-bond network whose rugged and complex global potential energy surface permits a large number of possible network configurations. As a result, it is very challenging to reproduce the freezing of 'real' water into a solid with a unique crystalline structure. For systems with a limited number of possible disordered hydrogen-bond network structures, such as confined water, it is relatively easy to locate a pathway from a liquid state to a crystalline structure. For pure and spatially unconfined water, however, molecular dynamics simulations of freezing are severely hampered by the large number of possible network configurations that exist. Here we present a molecular dynamics trajectory that captures the molecular processes involved in the freezing of pure water. We find that ice nucleation occurs once a sufficient number of relatively long-lived hydrogen bonds develop spontaneously at the same location to form a fairly compact initial nucleus. The initial nucleus then slowly changes shape and size until it reaches a stage that allows rapid expansion, resulting in crystallization of the entire system.

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We present an instantaneous-normal-mode analysis of liquid water at room temperature based on a computer simulated set of liquid configurations and we compare the results to analogous inherent-structure calculations. The separate translational and rotational contributions to each instantaneous normal mode are first obtained by computing the appropriate projectors from the eigenvectors. The extent of localization of the different kinds of modes is then quantified with the aid of the inverse participation ratio-roughly the reciprocal of the number of degrees of freedom involved in each mode. The instantaneous normal modes also carry along with them an implicit picture of how the topography of the potential surface changes as one moves from point to point in the very-high dimensional configuration space of a liquid. To help us understand this topography, we use the instantaneous normal modes to compute the predicted heights and locations of the nearest extrema of the potential. The net result is that in liquid water, at least, it is the low frequency modes that seem to reflect the largest-scale structural transitions. The detailed dynamics of such transitions are probably outside of the instantaneous-normal-mode formalism, but we do find that short-time dynamical quantities, such as the angular velocity autocorrelation functions, are described extraordinarily well by the instantaneous modes. 6672

Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and inter-protein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an allencompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semi-empirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository website (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-theart multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future.

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Circadian clocks generate slow and ordered cellular dynamics but consist of fast-moving bio-macromolecules; consequently, the origins of the overall slowness remain unclear. We identified the adenosine triphosphate (ATP) catalytic region [adenosine triphosphatase (ATPase)] in the amino-terminal half of the clock protein KaiC as the minimal pacemaker that controls the in vivo frequency of the cyanobacterial clock. Crystal structures of the ATPase revealed that the slowness of this ATPase arises from sequestration of a lytic water molecule in an unfavorable position and coupling of ATP hydrolysis to a peptide isomerization with high activation energy. The slow ATPase is coupled with another ATPase catalyzing autodephosphorylation in the carboxyl-terminal half of KaiC, yielding the circadian response frequency of intermolecular interactions with other clock-related proteins that influences the transcription and translation cycle.

A supercooled liquid generally exhibits marked shear-thinning behavior, but its detailed mechanism remains elusive. Here we study the dynamics of structural rearrangements in supercooled liquids under shear, using two-dimensional (2D) molecular dynamics simulation. To elucidate the relationship between heterogeneous dynamics and the rheological behavior, we extend the four-point correlation function, which has been used for analyzing "dynamic heterogenity" in a quiescent condition, to a system under steady shear. In the Newtonian regime, the rearrangement dynamics is strongly heterogeneous in space, but remains isotropic. Contrary to this, in the non-Newtonian regime, where marked shear-thinning behavior appears, we find a novel dynamic effect: The mobile region tends to form anisotropic "fluidized bands." This finding suggests a link between nonlinear rheology and inhomogeneization of flow.