Physics

Enzymes have been shown to diffuse faster in the presence of their reactants. Recently, we revealed new insights into this process of enhanced diffusion using single-particle tracking (SPT) with total internal reflection fluorescence (TIRF) microscopy. We found that the mobility of individual enzymes was enhanced three fold in the presence of the substrate, and the motion remained Brownian. In this work, we compare different experimental designs, as well as different data analysis approaches, for studying single enzyme diffusion. We first tether enzymes directly on supported lipid bilayers (SLBs) to constrain the diffusion of enzymes to two dimensions. This experimental design recovers the 3-fold enhancement in enzyme diffusion in the presence of the substrate, as we observed before. We also simplify our system by replacing the bulky polymers used in the prior chamber design with a SLB-coated surface and glycerol. Using this newly-designed SLB/glycerol chamber, we compare two different analysis approaches for SPT: the mean-squared displacement (MSD) analysis and the jump-length analysis. We find that the MSD analysis requires high viscosity and large particles to accurately report the diffusion coefficient, while jump-length analysis depends less on the viscosity or size. Furthermore, the SLB-glycerol chamber fails to reproduce the enhanced diffusion of enzymes because glycerol inhibits enzyme activity.

In cells, cytoskeletal filament networks are responsible for cell movement, growth, and division. Filaments in the cytoskeleton are driven and organized by crosslinking molecular motors. In reconstituted cytoskeletal systems, motor activity is responsible for far-from-equilibrium phenomena such as active stress, self-organized flow, and spontaneous nematic defect generation. How microscopic interactions between motors and filaments lead to larger-scale dynamics remains incompletely understood. To build from motor-filament interactions to predict bulk behavior of cytoskeletal systems, more computationally efficient techniques for modeling motor-filament interactions are needed. Here we derive a coarse-graining hierarchy of explicit and continuum models for crosslinking motors that bind to and walk on filament pairs. We compare the steady-state motor distribution and motor-induced filament motion for the different models and analyze their computational cost. All three models agree well in the limit of fast motor binding kinetics. Evolving a truncated moment expansion of motor density speeds the computation by 10 3 -- 10 6 compared to the explicit or continuous-density simulations, suggesting an approach for more efficient simulation of large networks. These tools facilitate further study of motor-filament networks on micrometer to millimeter length scales.

Animals have evolved distinctive survival strategies in response to constant selective pressure. In this review, we highlight how animals exploit complex flow phenomena by manipulating their habitat or by producing complex fluids. In particular, we outline different strategies evolved for movement, defense from predators, attacking of prey, and reproduction and breeding. From the slimy defense of the notorious hagfish to the circus-like mating spectacle of leopard slugs, we unveil remarkable correlations within the flow behavior and biological purpose of biological complex fluids. We discuss recurring phenomena, propose flow behavior for undescribed complex fluids, and put these in context with the animals survival strategy. With this review, we hope to underline the importance of complex fluids and material flow in the animal kingdom.

Outer hair cell (OHC) nonlinear capacitance (NLC) represents voltage sensor charge movements of prestin (SLC26a5), the protein responsible for OHC electromotility. Previous measures of NLC frequency response have employed methods which did not assess the influence of dielectric loss (sensor charge movements out of phase with voltage) that may occur, and such loss conceivably may influence the frequency dependent activity of prestin. Here we evaluate complex capacitance of prestin out to 30 kHz and find that its frequency response determined using this approach coincides with all previous estimates. We also show that membrane tension has no effect on the frequency response of prestin, despite substantial shifts in its voltage operating range, indicating that prestin transition rate alterations do not account for the shifts. The magnitude roll-off of prestin activity across frequency surpasses the reductions of NLC caused by salicylate treatments that are known to abolish cochlear amplification. Such roll-off must therefore limit the effectiveness if prestin in contributing to cochlear amplification at the very high acoustic frequencies processed by some mammals.

RNAs play crucial and versatile roles in biological processes. Computational prediction approaches can help to understand RNA structures and their stabilizing factors, thus providing information on their functions, and facilitating the design of new RNAs. Machine learning (ML) techniques have made tremendous progress in many fields in the past few years. Although their usage in protein-related fields has a long history, the use of ML methods in predicting RNA tertiary structures is new and rare. Here, we review the recent advances of using ML methods on RNA structure predictions and discuss the advantages and limitation, the difficulties and potentials of these approaches when applied in the field.

Computational determination of the equilibrium state of heterogeneous phospholipid mem-branes is a significant challenge. We wish to explore the rich phase diagram of these multi-component systems. However, the diffusion and mixing times in membranes are long com-pared to typical times of computer simulations. To speed up the relaxation times, advanced simulation methods are used. We evaluate the combination of enhanced sampling tech-niques such as MDAS (Molecular Dynamics with Alchemical Steps) and MC-MD (Monte Carlo with Molecular Dynamics) with a coarse-grained model of membranes (Martini) to re-duce the number of steps and force evaluations that are needed to reach equilibrium. We illustrate a significant gain compared to straightforward Molecular Dynamics of the Martini model by factors between three to ten. The combination is a useful tool to enhance the study of phase separation and the formation of domains in biological membranes.

For a first principles understanding of macromolecular processes, a quantitative understanding of the underlying free energy landscape and in particular its entropy contribution is crucial. The stability of biomolecules, such as proteins, is governed by the hydrophobic effect, which arises from competing enthalpic and entropic contributions to the free energy of the solvent shell. While the statistical mechanics of liquids, as well as molecular dynamics simulations have provided much insight, solvation shell entropies remain notoriously difficult to calculate, especially when spatial resolution is required. Here, we present a method that allows for the computation of spatially resolved rotational solvent entropies via a non-parametric k-nearest-neighbor density estimator. We validated our method using analytic test distributions and applied it to atomistic simulations of a water box. With an accuracy of better than 9.6%, the obtained spatial resolution should shed new light on the hydrophobic effect and the thermodynamics of solvation in general.

We study the diffusive behavior of biased Brownian particles in a two dimensional confined geometry filled with the freezing obstacles. The transport properties of these particles are investigated for various values of the obstacles density η and the scaling parameter f , which is the ratio of work done to the particles to available thermal energy. We show that, when the thermal fluctuations dominate over the external force, i.e., small f regime, particles get trapped in the given environment when the system percolates at the critical obstacles density η c ≈1.2 . However, as f increases, we observe that particles trapping occurs prior to η c . In particular, we find a relation between η and f which provides an estimate of the minimum η up to a critical scaling parameter f c beyond which the Fick-Jacobs description is invalid. Prominent transport features like nonmonotonic behavior of the nonlinear mobility, anomalous diffusion, and greatly enhanced effective diffusion coefficient are explained for various strengths of f and η . Also, it is interesting to observe that particles exhibit different kinds of diffusive behaviors, i.e., subdiffusion, normal diffusion, and superdiffusion. These findings, which are genuine to the confined and random Lorentz gas environment, can be useful to understand the transport of small particles or molecules in systems such as molecular sieves and porous media which have a complex heterogeneous environment of the freezing obstacles.

Ultra-long-chain fatty acids (ULCFAs) are biosynthesized in the restricted tissues such as retina, testis, and skin. The conformation of a single ULCFA, in which the sn-1 unsaturated chain has 32 carbons, in three types of tensionless phospholipid bilayers is studied by molecular dynamics simulations. It is found that the ultra-long tail of the ULCFA flips between two leaflets and fluctuates among an elongation into the opposite leaflet, lying between two leaflets, and turning back. As the number ratio of lipids in the opposite leaflet increases, the ratio of the elongated shape linearly decreases in all three cases. Thus, ULCFAs can sense the density differences between the two leaflets and respond to these changes.

The theoretical study of deformability of special sequence of DNA double helix TATA-box is presentated. The paper elaborates on the mechanisms of abnormal deformation of DNA TATA-box double helix that cannot be explained using the standard mechanical model of polymer molecules (WLC) and needs more detailed modeling. Analyzing of DNA TATA-box deformation it is shown the molucule can undergo significant deformations due to its property of the structural polymorphism, that is, possibility of the double helix fragment to exist in more then one conformations. In addition to elastic components (bending, twisting), the presented model includes the following deformation features: possibility of conformation rearrangement of the shapes of the sugar rings, effects of a specific nucleotide sequence and anisotropy, the coupling between components. Presented model allows describe abnormal deformation based on physical special fitures of double helix inner structure.