Effects of flexibility in coarse-grained models for bovine serum albumin and immunoglobulin G.

We construct a coarse-grained, structure-based, low-resolution, 6-bead flexible model of bovine serum albumin (BSA, PDB: 4F5S), which is a popular example of a globular protein in biophysical research. The model is obtained via direct Boltzmann inversion using all-atom simulations of a single molecule, and its particular form is selected from a large pool of 6-bead coarse-grained models using two suitable metrics that quantify the agreement in the distribution of collective coordinates between all-atom and coarse-grained Brownian dynamics simulations of solutions in the dilute limit. For immunoglobulin G (IgG), a similar structure-based 12-bead model has been introduced in the literature [Chaudhri et al., J. Phys. Chem. B 116, 8045 (2012)] and is employed here to compare findings for the compact BSA molecule and the more anisotropic IgG molecule. We define several modified coarse-grained models of BSA and IgG, which differ in their internal constraints and thus account for a variation of flexibility. We study denser solutions of the coarse-grained models with purely repulsive molecules (achievable by suitable salt conditions) and address the effect of packing and flexibility on dynamic and static behavior. Translational and rotational self-diffusivity is enhanced for more elastic models. Finally, we discuss a number of effective sphere sizes for the BSA molecule, which can be defined from its static and dynamic properties. Here, it is found that the effective sphere diameters lie between 4.9 and 6.1 nm, corresponding to a relative spread of about ±10% around a mean of 5.5 nm.

Short-Time Transport Properties of Bidisperse Suspensions of Immunoglobulins and Serum Albumins Consistent with a Colloid Physics Picture.

The crowded environment of biological systems such as the interior of living cells is occupied by macromolecules with a broad size distribution. This situation of polydispersity might influence the dependence of the diffusive dynamics of a given tracer macromolecule in a monodisperse solution on its hydrodynamic size and on the volume fraction. The resulting size dependence of diffusive transport crucially influences the function of a living cell. Here, we investigate a simplified model system consisting of two constituents in aqueous solution, namely, of the proteins bovine serum albumin (BSA) and bovine polyclonal gamma-globulin (Ig), systematically depending on the total volume fraction and ratio of these constituents. From high-resolution quasi-elastic neutron spectroscopy, the separate apparent short-time diffusion coefficients for BSA and Ig in the mixture are extracted, which show substantial deviations from the diffusion coefficients measured in monodisperse solutions at the same total volume fraction. These deviations can be modeled quantitatively using results from the short-time rotational and translational diffusion in a two-component hard sphere system with two distinct, effective hydrodynamic radii. Thus, we find that a simple colloid picture well describes short-time diffusion in binary mixtures as a function of the mixing ratio and the total volume fraction. Notably, the self-diffusion of the smaller protein BSA in the mixture is faster than the diffusion in a pure BSA solution, whereas the self-diffusion of Ig in the mixture is slower than in the pure Ig solution.

A microfluidic approach for synthesis and kinetic profiling of branched gold nanostructures.

Automatized approaches for nanoparticle synthesis and characterization represent a great asset to their applicability in the biomedical field by improving reproducibility and standardization, which help to meet the selection criteria of regulatory authorities. The scaled-up production of nanoparticles with carefully defined characteristics, including intrinsic morphological features, and minimal intra-batch, batch-to-batch, and operator variability, is an urgent requirement to elevate nanotechnology towards more trustable biological and technological applications. In this work, microfluidic approaches were employed to achieve fast mixing and good reproducibility in synthesizing a variety of gold nanostructures. The microfluidic setup allowed exploiting spatial resolution to investigate the growth evolution of the complex nanoarchitectures. By physically isolating intermediate reaction fractions, we performed an advanced characterization of the shape properties during their growth, not possible with routine characterization methods. Employing an in-house developed method to assign a specific identity to shapes, we followed the particle growth/deformation process and identified key reaction parameters for more precise control of the generated morphologies. Besides, this investigation led to the optimization of a one-pot multi-size and multi-shape synthesis of a variety of gold nanoparticles. In summary, we describe an optimized platform for highly controlled synthesis and a novel approach for the mechanistic study of shape-evolving nanomaterials.

A Nanoscale Shape-Discovery Framework Supporting Systematic Investigations of Shape-Dependent Biological Effects and Immunomodulation.

Since it is now possible to make, in a controlled fashion, an almost unlimited variety of nanostructure shapes, it is of increasing interest to understand the forms of biological control that nanoscale shape allows. However, a priori rational investigation of such a vast universe of shapes appears to present intractable fundamental and practical challenges. This has limited the useful systematic investigation of their biological interactions and the development of innovative nanoscale shape-dependent therapies. Here, we introduce a concept of biologically relevant inductive nanoscale shape discovery and evaluation that is ideally suited to, and will ultimately become, a vehicle for machine learning discovery. Combining the reproducibility and tunability of microfluidic flow nanochemistry syntheses, quantitative computational shape analysis, and iterative feedback from biological responses in vitro and in vivo, we show that these challenges can be mastered, allowing shape biology to be explored within accepted scientific and biomedical research paradigms. Early applications identify significant forms of shape-induced biological and adjuvant-like immunological control.

In depth characterisation of the biomolecular coronas of polymer coated inorganic nanoparticles with differential centrifugal sedimentation.

Advances in nanofabrication methods have enabled the tailoring of new strategies towards the controlled production of nanoparticles with attractive applications in healthcare. In many cases, their characterisation remains a big challenge, particularly for small-sized functional nanoparticles of 5 nm diameter or smaller, where current particle sizing techniques struggle to provide the required sensitivity and accuracy. There is a clear need for the development of new reliable characterisation approaches for the physico-chemical characterisation of nanoparticles with significant accuracy, particularly for the analysis of the particles in the presence of complex biological fluids. Herein, we show that the Differential Centrifugal Sedimentation can be utilised as a high-precision tool for the reliable characterisation of functional nanoparticles of different materials. We report a method to correlate the sedimentation shift with the polymer and biomolecule adsorption on the nanoparticle surface, validating the developed core-shell model. We also highlight its limit when measuring nanoparticles of smaller size and the need to use several complementary methods when characterising nanoparticle corona complexes.

Impact of dynamic sub-populations within grafted chains on the protein binding and colloidal stability of PEGylated nanoparticles.

Polyethylene glycol grafting has played a central role in preparing the surfaces of nano-probes for biological interaction, to extend blood circulation times and to modulate protein recognition and cellular uptake. However, the role of PEG graft dynamics and conformation in determining surface recognition processes is poorly understood primarily due to the absence of a microscopic picture of the surface presentation of the polymer. Here a detailed NMR analysis reveals three types of dynamic ethylene glycol units on PEG-grafted SiO2 nanoparticles (NPs) of the type commonly evaluated as long-circulating theranostic nano-probes; a narrow fraction with fast dynamics associated with the chain ends; a broadened fraction spectrally overlapped with the former arising from those parts of the chain experiencing some dynamic restriction; and a fraction too broad to be observed in the spectrum arising from units closer to the surface/graft which undergo slow motion on the NMR timescale. We demonstrate that ethylene glycol units transition between fractions as a function of temperature, core size, PEG chain length and surface coverage and demonstrate how this distribution affects colloidal stability and protein uptake. The implications of the findings for biological application of grafted nanoparticles are discussed in the context of accepted models for surface ligand conformation.

Low-Resolution Models for the Interaction Dynamics of Coated Gold Nanoparticles with ß2-microglobulin.

A large number of low-resolution models have been proposed in the last decades to reduce the computational cost of molecular dynamics simulations for bio-nano systems, such as those involving the interactions of proteins with functionalized nanoparticles (NPs). For the proteins, "minimalist" models at the one-bead-per residue (Cα-based) level and with implicit solvent are well established. For the gold NPs, widely explored for biotechnological applications, mesoscale (MS) models treating the NP core with a single spheroidal object are commonly proposed. In this representation, the surface details (coating, roughness, etc.) are lost. These, however, and the specificity of the functionalization, have been shown to have fundamental roles for the interaction with proteins. We presented a mixed-resolution coarse-grained (CG) model for gold NPs in which the surface chemistry is reintroduced as superficial smaller beads. We compared molecular dynamics simulations of the amyloid ß2-microglobulin represented at the minimalist level interacting with NPs represented with this model or at the MS level. Our finding highlights the importance of describing the surface of the NP at a finer level as the chemical-physical properties of the surface of the NP are crucial to correctly understand the protein-nanoparticle association.

Protein Short-Time Diffusion in a Naturally Crowded Environment.

The interior of living cells is a dense and polydisperse suspension of macromolecules. Such a complex system challenges an understanding in terms of colloidal suspensions. As a fundamental test we employ neutron spectroscopy to measure the diffusion of tracer proteins (immunoglobulins) in a cell-like environment (cell lysate) with explicit control over crowding conditions. In combination with Stokesian dynamics simulation, we address protein diffusion on nanosecond time scales where hydrodynamic interactions dominate over negligible protein collisions. We successfully link the experimental results on these complex, flexible molecules with coarse-grained simulations providing a consistent understanding by colloid theories. Both experiments and simulations show that tracers in polydisperse solutions close to the effective particle radius Reff = ⟨ Ri3⟩1/3 diffuse approximately as if the suspension was monodisperse. The simulations further show that macromolecules of sizes R > Reff ( R < Reff) are slowed more (less) effectively even at nanosecond time scales, which is highly relevant for a quantitative understanding of cellular processes.

Role of contact inhibition of locomotion and junctional mechanics in epithelial collective responses to injury.

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 to injuries by reorganizing their cell-cell junctions and migrating directionally towards the sites of damage. Notwithstanding, the mechanisms that drive collective responses in epithelial aggregates remain poorly understood. In this work, we develop a minimal mechanistic model that is able to capture the essential features of epithelial collective responses to injuries. We show that a model that integrates the mechanics of cells at the cell-cell and cell-substrate interfaces as well as contact inhibition of locomotion (CIL) correctly predicts two key properties of epithelial response to injury as: (1) local relaxation of the tissue and (2) collective reorganization involving the extension of cryptic lamellipodia that extend, on average, up to 3 cell diameters from the site of injury and morphometric changes in the basal regions. Our model also suggests that active responses (like the actomyosin purse string and softening of cell-cell junctions) are needed to drive morphometric changes in the apical region. Therefore, our results highlight the importance of the crosstalk between junctional biomechanics, cell substrate adhesion, and CIL, as well as active responses, in guiding the collective rearrangements that are required to preserve the epithelial barrier in response to injury.

Using single nanoparticle tracking obtained by nanophotonic force microscopy to simultaneously characterize nanoparticle size distribution and nanoparticle-surface interactions.

Comprehensive characterization of nanomaterials for medical applications is a challenging and complex task due to the multitude of parameters which need to be taken into consideration in a broad range of conditions. Routine methods such as dynamic light scattering or nanoparticle tracking analysis provide some insight into the physicochemical properties of particle dispersions. For nanomedicine applications the information they supply can be of limited use. For this reason, there is a need for new methodologies and instruments that can provide additional data on nanoparticle properties such as their interactions with surfaces. Nanophotonic force microscopy has been shown as a viable method for measuring the force between surfaces and individual particles in the nano-size range. Here we outline a further application of this technique to measure the size of single particles and based on these measurement build the distribution of a sample. We demonstrate its efficacy by comparing the size distribution obtained with nanophotonic force microscopy to established instruments, such as dynamic light scattering and differential centrifugal sedimentation. Our results were in good agreement to those observed with all other instruments. Furthermore, we demonstrate that the methodology developed in this work can be used to study complex particle mixtures and the surface alteration of materials. For all cases studied, we were able to obtain both the size and the interaction potential of the particles with a surface in a single measurement.

Multiscale Modelling of Bionano Interface.

We present a framework for coarse-grained modelling of the interface between foreign nanoparticles (NP) and biological fluids and membranes. Our model includes united-atom presentations of membrane lipids and globular proteins in implicit solvent, which are based on all-atom structures of the corresponding molecules and parameterised using experimental data or atomistic simulation results. The NPs are modelled by homogeneous spheres that interact with the beads of biomolecules via a central force that depends on the NP size. The proposed methodology is used to predict the adsorption energies for human blood plasma proteins on NPs 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 NP, which can be used for predicting the composition of the NP-protein corona for the corresponding material. We also show how the model can be used for studying NP interaction with a lipid bilayer membrane and thus can provide a mechanistic insight for modelling NP toxicity.

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

We used a computational approach to analyze the biomechanics of epithelial cell aggregates-islands, stripes, or entire monolayers-that combines both vertex and contact-inhibition-of-locomotion models to include 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 scale up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Without formally being a three-dimensional model, our approach has the minimal elements necessary to reproduce the distribution of cellular forces and mechanical cross-talk, as well as the distribution of principal stress in cells within epithelial cell aggregates. By making experimentally testable predictions, our approach can aid in mechanical analysis of epithelial tissues, especially when local changes in cell-cell and/or cell-substrate adhesion drive collective cell behavior.

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 (NPs). 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.

Gradient dynamics description for films of mixtures and suspensions: dewetting triggered by coupled film height and concentration fluctuations.

A thermodynamically consistent gradient dynamics model for the evolution of thin layers of liquid mixtures, solutions, and suspensions on solid substrates is presented which is based on a film-height- and mean-concentration-dependent free energy functional. It is able to describe a large variety of structuring processes, including coupled dewetting and decomposition processes. As an example, the model is employed to investigate the dewetting of thin films of liquid mixtures and suspensions under the influence of effective long-range van der Waals forces that depend on solute concentration. The occurring fluxes are discussed, and it is shown that spinodal dewetting may be triggered through the coupling of film height and concentration fluctuations. Fully nonlinear calculations provide the time evolution and resulting steady film height and concentration profiles.

Entangled trajectory dynamics in the Husimi representation.

We solve quantum dynamical equations of simple systems by propagating ensembles of interacting trajectories. A scheme is proposed which uses adaptive kernel density estimation for representing probability distribution functions and their derivatives. The formulation is carried on in the Husimi representation to ensure the positiveness of the distribution functions. By comparing to previous work, the effect of changing representations is studied as well as the advantage of using adaptive kernels for the estimation of probability distributions. We found significant improvement in the accuracy of the results.

Oscillation of viscous drops with smoothed particle hydrodynamics.

We investigate the nonlinear oscillations of heat-conductive, viscous, liquid drops in vacuum with zero gravity, using smoothed particle hydrodynamics (SPH). The liquid drops are modeled as a van der Waals fluid in two dimensions so that the models apply to flat, disklike drops. Attention is focused on small- to large-amplitude oscillations of drops that are released from a static elliptic shape. We find that for small-amplitude motions the combined dissipative effects of finite viscosity and heat conduction induce rapid decay of the oscillations after a few periods, while for large-amplitude motions wave damping is governed by the action of both viscous dissipation and surface tension forces. The transition from periodic to aperiodic decay at Re approximately 1 as well as the quadratic decrease of the frequency with the initial aspect ratio at large Re are reproduced in good agreement with previous theoretical predictions and experimental results.