Self-assembled aggregates in the gravitational field: growth and nematic order

The influence of the gravitational field on the reversible process of assembly and disassembly of linear aggregates is focus of this paper. Even the earth gravitational field can affect the equilibrium properties of heavy biological aggregates such as microtubules or actin filaments. The gravity gives rise to the concentration gradient which results in the distribution of aggregates of different lengths with height. Strong enough gravitational field induces the overall growth of the aggregates. The gravitational field facilitates the isotropic to nematic phase transition reflecting in a broader transition region. Coexisting phases have notedly different length distributions and the phase transition represent the interplay between the growth in the isotropic phase and the precipitation into nematic phase. The fields in an ultracentrifuge can only reinforce the effect of gravity, so the present description can be applied to a wider range of systems

General model of phospholipid bilayers in fluid phase within the single chain mean field theory

Coarse-grained model for saturated (DCPC, DLPC, DMPC, DPPC, DSPC) and unsaturated (POPC, DOPC) phospholipids is introduced within the Single Chain Mean Field theory. A single set of parameters adjusted for DMPC bilayers gives an adequate description of equilibrium and mechanical properties of a range of saturated lipid molecules that differ only in length of their hydrophobic tails and unsaturated (POPC, DOPC) phospholipids which have double bonds in the tails. A double bond is modeled with a fixed angle of 120 degrees, while the rest of the parameters are kept the same as saturated lipids. The thickness of the bilayer and its hydrophobic core, the compressibility and the equilibrium area per lipid correspond to experimentally measured values for each lipid, changing linearly with the length of the tail. The model for unsaturated phospholipids also fetches main thermodynamical properties of the bilayers. This model is used for an accurate estimation of the free energies of the compressed or stretched bilayers in stacks or multilayers and gives reasonable estimates for free energies. The proposed model may further be used for studies of mixtures of lipids, small molecule inclusions, interactions of bilayers with embedded proteins

Neural network learns physical rules for copolymer translocation through amphiphilic barriers

Recent developments in computer processing power lead to new paradigms of how problems in many-body physics and especially polymer physics can be addressed. Parallel processors can be exploited to generate millions of molecular configurations in complex environments at a second, and concomitant free-energy landscapes can be estimated. Databases that are complete in terms of polymer sequences and architecture form a powerful training basis for cross-checking and verifying machine learning-based models. We employ an exhaustive enumeration of polymer sequence space to benchmark the prediction made by a neural network. In our example, we consider the translocation time of a copolymer through a lipid membrane as a function of its sequence of hydrophilic and hydrophobic units. First, we demonstrate that massively parallel Rosenbluth sampling for all possible sequences of a polymer allows for meaningful dynamic interpretation in terms of the mean first escape times through the membrane. Second, we train a multi-layer neural network on logarithmic translocation times and show by the reduction of the training set to a narrow window of translocation times that the neural network develops an internal representation of the physical rules for sequence-controlled diffusion barriers. Based on the narrow training set, the network result approximates the order of magnitude of translocation times in a window that is several orders of magnitude wider than the training window. We investigate how prediction accuracy depends on the distance of unexplored sequences from the training window. © 2020, The Author(s)

Self-Consistent Field Theory of Brushes of Neutral Water-Soluble Polymers

The Self-Consistent Field theory of brushes of neutral water-soluble polymers described by two-state models is formulated in terms of the effective Flory interaction parameter $\chi_{eff}(T,\phi)$ that depends on both temperature, T and the monomer volume fraction, $\phi$. The concentration profiles, distribution of free ends and compression force profiles are obtained in the presence and in the absence of a vertical phase separation. A vertical phase separation within the layer leads to a distinctive compression force profile and a minimum in the plot of the moments of the concentration profile vs. the grafting density. The analysis is applied explicitly to the Karalstrom model. The relevance to brushes of Poly(N-isopropylacrylamide)(PNIPAM) is discussed.Comment: Accepted for publication in the Journal of Chemical Physic

Critical adsorption controls translocation of polymer chains through lipid bilayers and permeation of solvent

Monte Carlo simulations using an explicit solvent model indicate a new pathway for translocation of a polymer chain through a lipid bilayer. We consider a polymer chain composed of repeat units with a given hydrophobicity and a coarse-grained model of a lipid bilayer in the self-organized liquid state. By varying the degree of hydrophobicity the chain undergoes an adsorption transition with respect to the lipid bilayer. Close to the transition point, at a properly balanced hydrophobicity of the chain, the membrane becomes transparent with respect to the chain. At the same time the solvent permeability of the bilayer is strongly increased in the region close to adsorbed chain. Our results indicate that the critical point of adsorption of the polymer chain interacting with the fluctuating lipid bilayer could play a key role for the translocation of molecules though biological membranes.Comment: published in EP

Collision induced spatial organization of microtubules

The dynamic behavior of microtubules in solution can be strongly modified by interactions with walls or other structures. We examine here a microtubule growth model where the increase in size of the plus-end is perturbed by collisions with other microtubules. We show that such a simple mechanism of constrained growth can induce ordered structures and patterns from an initially isotropic and homogeneous suspension. First, microtubules self-organize locally in randomly oriented domains that grow and compete with each other. By imposing even a weak orientation bias, external forces like gravity or cellular boundaries may bias the domain distribution eventually leading to a macroscopic sample orientation.Comment: Submitted to Biophysical Journa