Coarse-grained Brownian dynamics simulations of protein translocation through nanopores

Brownian dynamics of cylindrical capsule-like particles in a nanopore in an electrically biased solid-state membrane

We use Brownian dynamics simulations to study the motion of cylindrical capsule-like particles (capsules) as they translocate through nanopores of various radii in an electrically biased silicon membrane. We find that for all pore sizes the electrostatic interaction between the particle and the pore results in the particle localization towards the pore 's center when the membrane and the particle have charges of the same sign (case 1) while in case of the opposite sign charges, the capsule prefers to stay near and along the nanopore wall (case 2). The preferential localization leads to all capsules rotating less while inside the pore compared to the bulk solution, with a larger net charge and/or particle length resulting in a smaller range of rotational movement. It also strongly affects the whole translocation process: in the first case, the translocation is due to the free diffusion along the pore axis and is weakly dependent on the particle charge and the nanopore radius while in the second case, the translocation time dramatically increases with the particle size and charge as the capsule gets "stuck" to the nanopore surface.

Coarse-grained simulation of the translational and rotational diffusion of globular proteins by dissipative particle dynamics

With simplified interactions and degrees of freedom, coarse-grained (CG) simulations have been successfully applied to study the translational and rotational diffusion of proteins in solution. However, in order to reach larger lengths and longer timescales, many CG simulations employ an oversimplified model for proteins or an implicit-solvent model in which the hydrodynamic interactions are ignored, and thus, the real kinetics are more or less unfaithful. In this work, we develop a CG model based on the dissipative particle dynamics (DPD) that can be universally applied to different types of proteins. The proteins are modeled as a group of rigid DPD beads without conformational changes. The fluids (including solvent and ions) are also modeled as DPD beads. The electrostatic interactions between charged species are explicitly considered by including charge distributions on DPD particles. Moreover, a surface friction between the protein and fluid beads is applied to control the slip boundary condition. With this model, we investigate the self-diffusion of a single globular protein in bulk solution. The translational and rotational diffusion coefficients of the protein can be tuned by the surface frictional constant to fit the predictions of the Stokes-Einstein (SE) relation. We find that both translational and rotational diffusion coefficients that meet with the prediction of the SE relation based on experimental results of the hydrodynamic radius are reached at almost the same frictional constant for different types of proteins. Such scaling behavior indicates that the model can be applied to simulate the translational and rotational diffusion together for various types of proteins.

A Review of Multiscale Computational Methods in Polymeric Materials

Polymeric materials display distinguished characteristics which stem from the interplay of phenomena at various length and time scales. Further development of polymer systems critically relies on a comprehensive understanding of the fundamentals of their hierarchical structure and behaviors. As such, the inherent multiscale nature of polymer systems is only reflected by a multiscale analysis which accounts for all important mechanisms. Since multiscale modelling is a rapidly growing multidisciplinary field, the emerging possibilities and challenges can be of a truly diverse nature. The present review attempts to provide a rather comprehensive overview of the recent developments in the field of multiscale modelling and simulation of polymeric materials. In order to understand the characteristics of the building blocks of multiscale methods, first a brief review of some significant computational methods at individual length and time scales is provided. These methods cover quantum mechanical scale, atomistic domain (Monte Carlo and molecular dynamics), mesoscopic scale (Brownian dynamics, dissipative particle dynamics, and lattice Boltzmann method), and finally macroscopic realm (finite element and volume methods). Afterwards, different prescriptions to envelope these methods in a multiscale strategy are discussed in details. Sequential, concurrent, and adaptive resolution schemes are presented along with the latest updates and ongoing challenges in research. In sequential methods, various systematic coarse-graining and backmapping approaches are addressed. For the concurrent strategy, we aimed to introduce the fundamentals and significant methods including the handshaking concept, energy-based, and force-based coupling approaches. Although such methods are very popular in metals and carbon nanomaterials, their use in polymeric materials is still limited. We have illustrated their applications in polymer science by several examples hoping for raising attention towards the existing possibilities. The relatively new adaptive resolution schemes are then covered including their advantages and shortcomings. Finally, some novel ideas in order to extend the reaches of atomistic techniques are reviewed. We conclude the review by outlining the existing challenges and possibilities for future research.

Analysis of Ligand-Receptor Association and Intermediate Transfer Rates in Multienzyme Nanostructures with All-Atom Brownian Dynamics Simulations

We present the second-generation GeomBD Brownian dynamics software for determining interenzyme intermediate transfer rates and substrate association rates in biomolecular complexes. Substrate and intermediate association rates for a series of enzymes or biomolecules can be compared between the freely diffusing disorganized configuration and various colocalized or complexed arrangements for kinetic investigation of enhanced intermediate transfer. In addition, enzyme engineering techniques, such as synthetic protein conjugation, can be computationally modeled and analyzed to better understand changes in substrate association relative to native enzymes. Tools are provided to determine nonspecific ligand-receptor association residence times, and to visualize common sites of nonspecific association of substrates on receptor surfaces. To demonstrate features of the software, interenzyme intermediate substrate transfer rate constants are calculated and compared for all-atom models of DNA origami scaffold-bound bienzyme systems of glucose oxidase and horseradish peroxidase. Also, a DNA conjugated horseradish peroxidase enzyme was analyzed for its propensity to increase substrate association rates and substrate local residence times relative to the unmodified enzyme. We also demonstrate the rapid determination and visualization of common sites of nonspecific ligand-receptor association by using HIV-1 protease and an inhibitor, XK263. GeomBD2 accelerates simulations by precomputing van der Waals potential energy grids and electrostatic potential grid maps, and has a flexible and extensible support for all-atom and coarse-grained force fields. Simulation software is written in C++ and utilizes modern parallelization techniques for potential grid preparation and Brownian dynamics simulation processes. Analysis scripts, written in the Python scripting language, are provided for quantitative simulation analysis. GeomBD2 is applicable to the fields of biophysics, bioengineering, and enzymology in both predictive and explanatory roles.

Protein permeation through an electrically tunable membrane

Protein filtration is important in many fields of science and technology such as medicine, biology, chemistry, and engineering. Recently, protein separation and filtering with nanoporous membranes has attracted interest due to the possibility of fast separation and high throughput volume. This, however, requires understanding of the protein's dynamics inside and in the vicinity of the nanopore. In this work, we utilize a Brownian dynamics approach to study the motion of the model protein insulin in the membrane-electrolyte electrostatic potential. We compare the results of the atomic model of the protein with the results of a coarse-grained and a single-bead model, and find that the coarse-grained representation of protein strikes the best balance between the accuracy of the results and the computational effort required. Contrary to common belief, we find that to adequately describe the protein, a single-bead model cannot be utilized without a significant effort to tabulate the simulation parameters. Similar to results for nanoparticle dynamics, our findings also indicate that the electric field and the electro-osmotic flow due to the applied membrane and electrolyte biases affect the capture and translocation of the biomolecule by either attracting or repelling it to or from the nanopore. Our computational model can also be applied to other types of proteins and separation conditions.

Soft matter in hard confinement: phase transition thermodynamics, structure, texture, diffusion and flow in nanoporous media

Spatial confinement in nanoporous media affects the structure, thermodynamics and mobility of molecular soft matter often markedly. This article reviews thermodynamic equilibrium phenomena, such as physisorption, capillary condensation, crystallisation, self-diffusion, and structural phase transitions as well as selected aspects of the emerging field of spatially confined, non-equilibrium physics, i.e. the rheology of liquids, capillarity-driven flow phenomena, and imbibition front broadening in nanoporous materials. The observations in the nanoscale systems are related to the corresponding bulk phenomenologies. The complexity of the confined molecular species is varied from simple building blocks, like noble gas atoms, normal alkanes and alcohols to liquid crystals, polymers, ionic liquids, proteins and water. Mostly, experiments with mesoporous solids of alumina, gold, carbon, silica, and silicon with pore diameters ranging from a few up to 50 nm are presented. The observed peculiarities of nanopore-confined condensed matter are also discussed with regard to applications. A particular emphasis is put on texture formation upon crystallisation in nanoporous media, a topic both of high fundamental interest and of increasing nanotechnological importance, e.g. for the synthesis of organic/inorganic hybrid materials by melt infiltration, the usage of nanoporous solids in crystal nucleation or in template-assisted electrochemical deposition of nano structures.

Selective on site separation and detection of molecules in diluted solutions with super-hydrophobic clusters of plasmonic nanoparticles

Super-hydrophobic surfaces are bio-inspired interfaces with a superficial texture that, in its most common evolution, is formed by a periodic lattice of silicon micro-pillars. Similar surfaces reveal superior properties compared to conventional flat surfaces, including very low friction coefficients. In this work, we modified meso-porous silicon micro-pillars to incorporate networks of metal nano-particles into the porous matrix. In doing so, we obtained a multifunctional-hierarchical system in which (i) at a larger micrometric scale, the super-hydrophobic pillars bring the molecules dissolved in an ultralow-concentration droplet to the active sites of the device, (ii) at an intermediate meso-scale, the meso-porous silicon film adsorbs the low molecular weight content of the solution and, (iii) at a smaller nanometric scale, the aggregates of silver nano-particles would measure the target molecules with unprecedented sensitivity. In the results, we demonstrated how this scheme can be utilized to isolate and detect small molecules in a diluted solution in very low abundance ranges. The presented platform, coupled to Raman or other spectroscopy techniques, is a realistic candidate for the protein expression profiling of biological fluids.

Sensing of protein molecules through nanopores: a molecular dynamics study

Solid-state nanopores have been shown to be suitable for single molecule detection. While numerous modeling investigations exist for DNA within nanopores, there are few simulations of protein translocations. In this paper, we use atomistic molecular dynamics to investigate the translocation of proteins through a silicon nitride nanopore. The nanopore dimensions and profile are representative of experimental systems. We are able to calculate the change in blockade current and friction coefficient for different positions of the protein within the pore. The change in ionic current is found to be negligible until the protein is fully within the pore and the current is lowest when the protein is in the pore center. Using a simple theory that gives good quantitative agreement with the simulation results we are able to show that the variation in current with position is a function of the pore shape. In simulations that guide the protein through the nanopore we identify the effect that confinement has on the friction coefficient of the protein. This integrated view of translocation at the nanoscale provides useful insights that can be used to guide the design of future devices.

ReaDDy--a software for particle-based reaction-diffusion dynamics in crowded cellular environments

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics.

Filtering of nanoparticles with tunable semiconductor membranes

Translocation dynamics of nanoparticles permeating through the nanopore in an n-Si semiconductor membrane is studied. With the use of Brownian Dynamics to describe the motion of the charged nanoparticles in the self-consistent membrane-electrolyte electrostatic potential, we asses the possibility of using our voltage controlled membrane for the macroscopic filtering of the charged nanoparticles. The results indicate that the tunable local electric field inside the membrane can effectively control interaction of a nanoparticle with the nanopore by either blocking its passage or increasing the translocation rate. The effect is particularly strong for larger nanoparticles due to their stronger interaction with the membrane while in the nanopore. By extracting the membrane permeability from our microsopic simulations, we compute the macroscopic sieving factors and show that the size selectivity of the membrane can be tuned by the applied voltage.