arXiv subjects

Vladimir Lobaskin

Publications and source records attributed to Vladimir Lobaskin.

At least 19 recordsLinked to original sources

arXiv2026

Orientation-Dependent Protein Binding at Nanoparticle Interfaces

Accurate quantification of protein-nanoparticle interactions is essential for applications in nanobiotechnology, nanomedicine, and drug delivery. Motivated by recent computational and experimental work, we combine coarse-grained united-atom (UA) models with molecular docking to characterize protein adsorption on SiO_2 nanoparticles. We construct orientation-resolved heatmaps in which polar and azimuthal angles uniquely specify the relative protein-nanoparticle pose, and the map amplitude reports binding propensity via the minimum UA adsorption energy or the docking score. Each angular bin corresponds to a distinct docked complex, enabling systematic comparison of binding geometries across models. To relate docking score landscapes to Boltzmann-averaged UA adsorption energetics, we analyze eight birch pollen allergen proteins previously studied experimentally. Similarity between the two orientational distributions is quantified using the Jensen-Shannon divergence (JSD). We find encouraging agreement between the two approaches in several cases, while also identifying limitations and routes for improvement, including optimized angular resolution and iterative refinement of interaction parameters. Overall, this framework provides a quantitative bridge between coarse-grained energetics and docking outputs at protein-nanoparticle interfaces, supporting improved predictive modeling and mechanistic insight into protein-nanoparticle binding landscapes.

physics.bio-ph↗

arXiv2024

NPCoronaPredict: A computational pipeline for the prediction of the nanoparticle-biomolecule corona

The corona of a nanoparticle immersed in a biological fluid is of key importance to its eventual fate and bioactivity in the environment or inside live tissues. It is critical to have insight into both the underlying bionano interactions and the corona composition to ensure biocompatibility of novel engineered nanomaterials. A prediction of these properties in silico requires the successful spanning of multiple orders of magnitude of both time and physical dimensions to produce results in a reasonable amount of time, necessitating the development of a multiscale modelling approach. Here, we present the NPCoronaPredict open-source software package: a suite of software tools to enable this prediction for complex multi-component nanomaterials in essentially arbitrary biological fluids, or more generally any medium containing organic molecules. The package integrates several recent physics-based computational models and a library of both physics-based and data-driven parameterisations for nanomaterials and organic molecules. We describe the underlying theoretical background and the package functionality from the design of multi-component NPs through to the evaluation of the corona.

cond-mat.mes-hall↗

arXiv2022

Machine-learning based prediction of small molecule -- surface interaction potentials

Predicting the adsorption affinity of a small molecule to a target surface is of importance to a range of fields, from catalysis to drug delivery and human safety, but a complex task to perform computationally when taking into account the effects of the surrounding medium. We present a flexible machine-learning approach to predict potentials of mean force (PMFs) and adsorption energies for chemical -- surface pairs from the separate interaction potentials of each partner with a set of probe atoms. We use a pre-existing library of PMFs obtained via atomistic molecular dynamics for a variety of inorganic materials and molecules to train the model. We find good agreement between original and predicted PMFs in both training and validation groups, confirming the predictive power of this approach, and demonstrate the flexibility of the model by producing PMFs for molecules and surfaces outside the training set.

physics.chem-ph↗

arXiv2020

Advanced in silico characterization of nanomaterials for nanoparticle toxicology

Nanomaterials possess a wide range of potential applications due to their novel properties compared to bulk matter, but these same properties may represent an unknown risk to health. Experimental safety testing cannot keep pace with the rate at which new nanoparticles are developed and, being lengthy and expensive, often hinders the development of technology. An economic alternative to in vitro and in vivo testing is offered by nanoinformatics, potentially enabling the quantitative relation of the nanomaterial properties to their crucial biological activities. Recent research efforts have demonstrated that such activities can be successfully predicted from the physicochemical characteristics of nanoparticles, especially those related to the bionano interface, by means of statistical models. In this work, as a step towards in silico prediction of toxicity of nanomaterials, an advanced computational characterization of these materials has been proposed and applied to titanium dioxide nanoparticles. The characteristics of nanoparticles and bionano interface are computed using a systematic multiscale approach relying only on information on chemistry and structure of the nanoparticles.

cond-mat.mtrl-sci↗

arXiv2018

Polarized Ukraine 2014: Opinion and Territorial Split Demonstrated with the Bounded Confidence XY Model, Parameterized by Twitter Data

Multiple countries have recently experienced extreme political polarization, which in some cases led to escalation of hate crime, violence and political instability. Beside the much discussed presidential elections in the United States and France, Britain's Brexit vote and Turkish constitutional referendum, showed signs of extreme polarization. Among the countries affected, Ukraine faced some of the gravest consequences. In an attempt to understand the mechanisms of these phenomena, we here combine social media analysis with agent-based modeling of opinion dynamics, targeting Ukraine's crisis of 2014. We use Twitter data to quantify changes in the opinion divide and parameterize an extended Bounded-Confidence XY Model, which provides a spatiotemporal description of the polarization dynamics. We demonstrate that the level of emotional intensity is a major driving force for polarization that can lead to a spontaneous onset of collective behavior at a certain degree of homophily and conformity. We find that the critical level of emotional intensity corresponds to a polarization transition, marked by a sudden increase in the degree of involvement and in the opinion bimodality.

physics.soc-ph↗

arXiv2017

Contact inhibition of locomotion and junctional mechanics guide collective cell behavior in epithelial wound repair

Epithelial tissues form physically integrated barriers against the external environment protecting organs from infection and invasion. Within each tissue, epithelial cells respond to different challenges that can potentially compromise tissue integrity. In particular, cells collectively respond by reorganizing their cell-cell junctions and migrating directionally towards the sites of injury. Notwithstanding, the mechanisms that define the spatiotemporal scales and driving forces of these collective responses remain poorly understood. To address this we first analyzed the collective response of epithelial monolayers to injury and compare the results with different computational models of epithelial cells. We found that a model that integrates the mechanics of cells at the cell-cell and cell-substrate interface as well as contact inhibition of locomotion predicts two key properties of epithelial response to injury as: 1) local relaxation of the tissue and 2) collective responses involving the elongation of cells (basal and apical regions) and extension of cryptic lamellipodia that extend up to < 3 cell diameters from the site of injury. Our results therefore highlight the integration between junctional biomechanics, cell substrate adhesion and contact inhibition of locomotion to guide the rapid collective rearrangements that are required to preserve the epithelial barrier in response to injury.

physics.bio-ph↗

arXiv2016

Electrophoresis of Janus Particles: a Molecular Dynamics simulation study

In this work, we use Molecular Dynamics and Lattice-Boltzmann simulations to study the properties of charged Janus particles in an electric field. We show that for relatively small net charge and thick electrostatic diffuse layer mobilities of Janus particles and uniformly charged colloids of the same net charge are identical. However, for higher charges and thinner diffuse layers Janus particles always show lower electrophoretic mobility. We also demonstrate that Janus particles align with the electric field and the angular deviation from the field's direction are related to their dipole moment. We show that the latter is affected by the thickness of the electrostatic diffuse layer and strongly correlates with the electrophoretic mobility.

cond-mat.soft↗

arXiv2016

Contact inhibition of locomotion and mechanical cross-talk between cell-cell and cell-substrate adhesion determines the pattern of junctional tension in epithelial cell aggregates

We generated a computational approach to analyze the biomechanics of epithelial cell aggregates, either island or stripes or entire monolayers, that combines both vertex and contact-inhibition-of-locomotion models to include both cell-cell and cell-substrate adhesion. Examination of the distribution of cell protrusions (adhesion to the substrate) in the model predicted high order profiles of cell organization that agree with those previously seen experimentally. Cells acquired an asymmetric distribution of basal protrusions, traction forces and apical aspect ratios that decreased when moving from the edge to the island center. Our in silico analysis also showed that tension on cell-cell junctions and apical stress is not homogeneous across the island. Instead, these parameters are higher at the island center and scales up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Without formally being a 3-dimensional model, our approach has the minimal elements necessary to reproduce the distribution of cellular forces and mechanical crosstalk as well as distribution of principal stress in cells within epithelial cell aggregates. By making experimental testable predictions, our approach would benefit the mechanical analysis of epithelial tissues, especially when local changes in cell-cell and/or cell-substrate adhesion drive collective cell behavior.

physics.bio-ph↗

arXiv2015

Multiscale modelling of bionano interface

In this work we describe a set of Coarse-grained (CG) tools that allow to simulate the uptake of the nanoparticles (NPs) coated with proteins by a lipid bilayer. We describe a CG model to calculate the adsorption energies and the most favorable adsorption orientations of proteins onto a hydrophobic NP. The proposed method is then used to calculate the adsorption energies of two common proteins in human blood onto neutral and negative charged NPs. We also report the effect of the NP radius on the adsorption energies and validate the proposed methodology against full atomistic simulations. We also describe a methodology in which full atomistic simulations of a lipid bilayer and various lipid-cholesterol mixtures are used for the extraction of CG pair potentials. We also compare and validate the predictions of simulations at molecular and CG level. Finally, we present a CG simulation of the interaction a bare NP and of a NP-protein complex with a lipid bilayer.

cond-mat.soft↗

arXiv2015

Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles

We present a coarse-grained model for evaluation of interactions of globular proteins with nanoparticles. The protein molecules are represented by one bead per aminoacid and the nanoparticle by a homogeneous sphere that interacts with the aminoacids via a central force that depends on the nanoparticle size. The proposed methodology is used to predict the adsorption energies for six common human blood plasma proteins on hydrophobic charged or neutral nanoparticles of different sizes as well as the preferred orientation of the molecules upon adsorption. Our approach allows one to rank the proteins by their binding affinity to the nanoparticle, which can be used for predicting the composition of the NP-protein corona. The predicted ranking is in good agreement with known experimental data for protein adsorption on surfaces.

cond-mat.soft↗

arXiv2015

Motion of Euglena Gracilis: Active Fluctuations and Velocity Distribution

We study the velocity distribution of unicellular swimming algae Euglena gracilis using optical microscopy and theory. To characterize a peculiar feature of the experimentally observed distribution at small velocities we use the concept of active fluctuations, which was recently proposed for the description of stochastically self-propelled particles [Romanczuk, P. and Schimansky-Geier, L., Phys. Rev. Lett. 106, 230601 (2011)]. In this concept, the fluctuating forces arise due to internal random performance of the propulsive motor. The fluctuating forces are directed in parallel to the heading direction, in which the propulsion acts. In the theory, we introduce the active motion via the depot model [Schweitzer et al., Phys. Rev. Lett. 80, 23, 5044 (1998)]. We demonstrate that the theoretical predictions based on the depot model with active fluctuations are consistent with the experimentally observed velocity distributions. In addition to the model with additive active noise, we obtain theoretical results for a constant propulsion with multiplicative noise.

physics.bio-ph↗

arXiv2015

Orientational hysteresis in swarms of active particles in external field

Structure and ordering in swarms of active particles have much in common with condensed matter systems like magnets or liquid crystals. A number of important characteristics of such materials can be obtained via dynamic tests such as hysteresis. In this work, we show that dynamic hysteresis can be observed also in swarms of active particles and possesses similar properties to the counterparts in magnetic materials. To study the swarm dynamics, we use computer simulations of the active Brownian particle model with dissipative interactions. The swarm is confined to a narrow linear channel and the one-dimensional polar order parameter is measured. In an oscillating external field, the order parameter demonstrates dynamic hysteresis with the shape of the loop and its area varying with the amplitude and frequency of the applied field, swarm density and the noise intensity. We measure the scaling exponents for the hysteresis loop area, which can be associated with the controllability of the swarm. Although the exponents are non-universal and depend on the system's parameters, their limiting values can be predicted using a generic model of dynamic hysteresis. We also discuss similarities and differences between the swarm ordering dynamics and two-dimensional magnets.

physics.bio-ph↗

arXiv2014

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

We study the orientational ordering in systems of self-propelled particles with selective interactions. To introduce the selectivity we augment the standard Vicsek model with a bounded-confidence collision rule: a given particle only aligns to neighbors who have directions quite similar to its own. Neighbors whose directions deviate more than a fixed restriction angle $α$ are ignored. The collective dynamics of this systems is studied by agent-based simulations and kinetic mean field theory. We demonstrate that the reduction of the restriction angle leads to a critical noise amplitude decreasing monotonically with that angle, turning into a power law with exponent 3/2 for small angles. Moreover, for small system sizes we show that upon decreasing the restriction angle, the kind of the transition to polar collective motion changes from continuous to discontinuous. Thus, an apparent tricritical point is identified and calculated analytically. We also find that at very small interaction angles the polar ordered phase becomes unstable with respect to the apolar phase. We show that the mean-field kinetic theory permits stationary nematic states below a restriction angle of $0.681 π$. We calculate the critical noise, at which the disordered state bifurcates to a nematic state, and find that it is always smaller than the threshold noise for the transition from disorder to polar order. The disordered-nematic transition features two tricritical points: At low and high restriction angle the transition is discontinuous but continuous at intermediate $α$. We generalize our results to systems that show fragmentation into more than two groups and obtain scaling laws for the transition lines and the corresponding tricritical points. A novel numerical method to evaluate the nonlinear Fredholm integral equation for the stationary distribution function is also presented.

cond-mat.stat-mech↗

arXiv2013

Electrostatic Interaction of Heterogeneously Charged Surfaces with Semipermeable Membranes

In this paper we study the electrostatic interaction of a heterogeneously charged wall with a neutral semipermeable membrane. The wall consists of periodic stripes, where the charge density varies in one direction. The membrane is in a contact with a bulk reservoir of an electrolyte solution and separated from the wall by a thin film of salt-free liquid. One type of ions (small counterions) permeates into the gap and gives rise to a distance-dependent membrane potential, which translates into a repulsive electrostatic disjoining pressure due to an overlap of counterion clouds in the gap. To quantify it we use two complementary approaches. First, we propose a mean-field theory based on a linearized Poisson-Boltzmann equation and Fourier analysis. These calculations allow us to estimate the effect of a heterogeneous charge pattern at the wall on the induced heterogeneous membrane potential, and the value of the disjoining pressure as a function of the gap. Second, we perform Langevin dynamics simulations of the same system with explicit ions. The results of the two approaches are in good agreement with each other at low surface charge and small gap, but differ due to nonlinearity at the higher charge. These results demonstrate that a heterogeneity of the wall charge can lead to a huge reduction in the electrostatic repulsion, which could dramatically facilitate a self-assembly in complex synthetic and biological systems.

cond-mat.soft↗

arXiv2013

Collective dynamics in systems of active Brownian particles with dissipative interactions

We use computer simulations to study the onset of collective motion in systems of interacting active particles. Our model is a swarm of active Brownian particles with internal energy depot and interactions inspired by the dissipative particle dynamics method, imposing pairwise friction force on the nearest neighbours. We study orientational ordering in a 2D system as a function of energy influx rate and particle density. The model demonstrates a transition into the ordered state on increasing the particle density and increasing the input power. Although both the alignment mechanism and the character of individual motion in our model differ from those in the well-studied Vicsek model, it demonstrates identical statistical properties and phase behaviour.

cond-mat.stat-mech↗

arXiv2013

Statistical properties of swarms of self-propelled particles with repulsions across the order-disorder transition

We study dynamic self-organisation and order-disorder transitions in a two-dimensional system of self-propelled particles. Our model is a variation of the Vicsek model, where particles align the motion to their neighbours but repel each other at short distances. We use computer simulations to measure the orientational order parameter for particle velocities as a function of intensity of internal noise or particle density. We show that in addition to the transition to an ordered state on increasing the particle density, as reported previously, there exists a transition into a disordered phase at the higher densities, which can be attributed to the destructive action of the repulsions. We demonstrate that the transition into the ordered phase is accompanied by the onset of algebraic behaviour of the two-point velocity correlation function and by a non-monotonous variation of the velocity relaxation time. The critical exponent for the decay of the velocity correlation function in the ordered phase depends on particle concentration at low densities but assumes a universal value in more dense systems.

cond-mat.stat-mech↗

arXiv2012

Interactions of neutral semipermeable shells in asymmetric electrolyte solutions

We study the ionic equilibria and interactions of neutral semi-permeable spherical shells immersed in electrolyte solutions, including polyions. Although the shells are uncharged, only one type of ions of the electrolyte can permeate them, thus leading to a steric charge separation in the system. This gives rise to a charge accumulation inside the shell and a build up of concentration- dependent shell potential, which converts into a disjoining pressure between the neighboring shells. These are quantified by using the Poisson-Boltzmann and integral equations theory. In particular, we show that in case of low valency electrolytes, interactions between shells are repulsive and can be sufficiently strong to stabilize the shell dispersion. In contrast, the charge correlation effects in solutions of polyvalent ions result in attractions between the shells, with can lead to their aggregation.

cond-mat.soft↗

arXiv2012

Electrostatic interaction of neutral semipermeable membranes

We consider an osmotic equilibrium between bulk solutions of polyelectrolyte bounded by semipermeable membranes and separated by a thin film of salt-free liquid. Although the membranes are neutral, the counter-ions of the polyelectrolyte molecules permeate into the gap and lead to a steric charge separation. This gives rise to a distance-dependent membrane potential, which translates into a repulsive electrostatic disjoining pressure. From the solution of the non-linear Poisson-Boltzmann equation we obtain the distribution of the potential and of ions. We then derive an explicit formula for the pressure exerted on the membranes and show that it deviates from the classical van't Hoff expression for the osmotic pressure. This difference is interpreted in terms of a repulsive electrostatic disjoining pressure originating from the overlap of counterion clouds inside the gap. We also develop a simplified theory based on a linearized Poisson-Boltzmann approach. A comparison with simulation of a primitive model for the electrolyte is provided and does confirm the validity of the theoretical predictions Beyond the fundamental result that the neutral surfaces can repel, this mechanism not only helps to control the adhesion and long-range interactions of living cells, bacteria, and vesicles, but also allows us to argue that electrostatic interactions should play enormous role in determining behavior and functions of systems bounded by semipermeable membranes.

cond-mat.soft↗