Deeper Insights into Mixed Crowding through Enzyme Activity, Dynamics, and Crowder Diffusion

Given the fact that the cellular interior is crowded by many different kinds of macromolecules, it is important that in vitro studies be carried out in the presence of mixed crowder systems. In this regard, we have used binary crowders formed by the combination of some of the commonly used crowding agents, namely, Ficoll 70, Dextran 70, Dextran 40, and PEG 8000 (PEG 8), to study how these affect enzyme activity, dynamics, and crowder diffusion. The enzyme chosen is AK3L1, an isoform of adenylate kinase. To investigate its dynamics, we have carried out three single point mutations (A74C, A132C, and A209C) with the cysteine residues being labeled with a coumarin-based solvatochromic probe [CPM: (7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin)]. Both enzyme activity and dynamics decreased in the binary mixtures as compared with the sum of the individual crowders, suggesting a reduction in excluded volume (in the mixture). To gain deeper insights into the binary mixtures, fluorescence correlation spectroscopy studies were carried out using fluorescein isothiocyanate-labeled Dextran 70 and tetramethylrhodamine-labeled AK3L1 as the diffusion probes. Diffusion in binary mixtures was observed to be much more constrained (relative to the sum of the individual crowders) for the labeled enzyme as compared to the labeled crowder showing different environments being faced by the two species. This was further confirmed during imaging of the phase-separated droplets formed in the binary mixtures having PEG as one of the crowding agents. The interior of these droplets was found to be rich in crowders and densely packed, as shown by confocal and digital holographic microscopy images, with the enzymes predominantly residing outside these droplets, that is, in the relatively less crowded regions. Taken together, our data provide important insights into various aspects of the simplest form of mixed crowding, that is, composed of just two components, and also hint at the enhanced complexity that the cellular interior presents toward having a detailed and comprehensive understanding of the same.

Metastable States in the Hinge-Bending Landscape of an Enzyme in an Atomistic Cytoplasm Simulation

Many enzymes undergo major conformational changes to function in cells, particularly when they bind to more than one substrate. We quantify the large-amplitude hinge-bending landscape of human phosphoglycerate kinase (PGK) in a human cytoplasm. Approximately 70 μs of all-atom simulations, upon coarse graining, reveal three metastable states of PGK with different hinge angle distributions and additional substates. The "open" state was more populated than the "semi-open" or "closed" states. In addition to free energies and barriers within the landscape, we characterized the average transition state passage time of ≈0.3 μs and reversible substrate and product binding. Human PGK in a dilute solution simulation shows a transition directly from the open to closed states, in agreement with previous SAXS experiments, suggesting that the cell-like model environment promotes stability of the human PGK semi-open state. Yeast PGK also sampled three metastable states within the cytoplasm model, with the closed state favored in our simulation.

Particle-based mesoscopic model for phase separation in a binary fluid mixture

A mesoscopic simulation model to study the phase separation in a binary fluid mixture in three dimensions (3D) is presented here by augmenting the existing particle-based multiparticle collision dynamics (MPCD) algorithm. The approach describes the nonideal equation of the fluid state by incorporating the excluded-volume interaction between the two components within the framework of stochastic collision, which depends on the local fluid composition and velocity. Calculating the nonideal contribution to the pressure both from simulation and analytics shows the model to be thermodynamically consistent. A phase diagram to explore the range of parameters that give rise to phase separation in the model is investigated. The interfacial width and phase growth obtained from the model agree with the literature for a wide range of temperatures and parameters.

PEG mediated destabilization of holo α-lactalbumin probed by in silico and in vitro studies: deviation from excluded volume effect

Crowded and confined macromolecular milieus surround proteins, and both are stabilizing if the nature of the interaction between crowder and proteins are considered hard-core repulsive interactions. However, non-specific chemical interactions between a protein and its surroundings also play a significant role and the sum effect of both hard-core repulsion and soft interaction balances the overall effect of crowding/confinement. Previous studies showing the effect of polyethylene glycol (PEG) on protein and nucleic acid may be interpreted as either primarily excluded volume effect or, in some cases, chemical effect by changing solvent properties. In case of destabilizing interactions, charge-charge and hydrophobic contact have to gain more attention. For instance, in vitro and in vivo studies using protein as crowding agent revealed the destabilization of proteins induced by charge-charge interactions. To investigate the effect of PEG 10 kDa on holo α-lactalbumin (holo α-LA), structure and thermal stability of the protein were measured at different pH values using several techniques. Structural characterization by Trp-fluorescence, near-UV CD and far-UV measurements at different pH values clearly shows perturbation of tertiary and secondary structure of holo α-LA by PEG 10 kDa. Furthermore, the dynamic light scattering measurement shows that the protein is homogeneous under all experimental conditions. Analysis of the heat-induced denaturation profile in the presence of the crowder shows destabilization of the protein in terms of T_m (midpoint of denaturation) and ΔG_D⁰ (Gibbs free energy change at 25 °C). To evaluate the interaction of PEG 10 kDa with holo α-LA and stability of PEG-α-LA complex, docking and molecular dynamic simulation were carried out for 100 ns.Communicated by Ramaswamy H. Sarma.

Time-correlation functions for odd Langevin systems

We investigate the statistical properties of fluctuations in active systems that are governed by non-symmetric responses. Both an underdamped Langevin system with an odd resistance tensor and an overdamped Langevin system with an odd elastic tensor are studied. For a system in thermal equilibrium, the time-correlation functions should satisfy time-reversal symmetry and the anti-symmetric parts of the correlation functions should vanish. For the odd Langevin systems, however, we find that the anti-symmetric parts of the time-correlation functions can exist and that they are proportional to either the odd resistance coefficient or the odd elastic constant. This means that the time-reversal invariance of the correlation functions is broken due to the presence of odd responses in active systems. Using the short-time asymptotic expressions of the time-correlation functions, one can estimate an odd elastic constant of an active material such as an enzyme or a motor protein.

Fluorine NMR Spectroscopy Enables to Quantify the Affinity Between DNA and Proteins in Cell Lysate

The determination of the binding affinity quantifying the interaction between proteins and nucleic acids is of crucial interest in biological and chemical research. Here, we have made use of site-specific fluorine labeling of the cold shock protein from Bacillus subtilis, BsCspB, enabling to directly monitor the interaction with single stranded DNA molecules in cell lysate. High-resolution 19 F NMR spectroscopy has been applied to exclusively report on resonance signals arising from the protein under study. We have found that this experimental approach advances the reliable determination of the binding affinity between single stranded DNA molecules and its target protein in this complex biological environment by intertwining analyses based on NMR chemical shifts, signal heights, line shapes and simulations. We propose that the developed experimental platform offers a potent approach for the identification of binding affinities characterizing intermolecular interactions in native surroundings covering the nano-to-micromolar range that can be even expanded to in cell applications in future studies.

All atom insights into the impact of crowded environments on protein stability by NMR spectroscopy

The high density of macromolecules affecting proteins due to volume exclusion has been discussed in theory but numerous in vivo experiments cannot be sufficiently understood taking only pure entropic stabilization into account. Here, we show that the thermodynamic stability of a beta barrel protein increases equally at all atomic levels comparing crowded environments with dilute conditions by applying multidimensional high-resolution NMR spectroscopy in a systematic manner. Different crowding agents evoke a pure stabilization cooperatively and do not disturb the surface or integrity of the protein fold. The here developed methodology provides a solid base that can be easily expanded to incorporate e.g. binding partners to recognize functional consequences of crowded conditions. Our results are relevant to research projects targeting soluble proteins in vivo as it can be anticipated that their thermodynamic stability increase comparably and has consequently to be taken into account to coherently understand intracellular processes.

Tuning of the Aggregation Behavior of Fluorinated Polymeric Nanoparticles for Improved Therapeutic Efficacy

Incorporation of fluorinated moieties in polymeric nanoparticles has been shown in many instances to increase their uptake by living cells and, hence, has proven to be a useful approach to enhancing delivery to cells. However, it remains unclear how incorporation of fluorine affects critical transport processes, such as interactions with membranes, intracellular transport, and tumor penetration. In this study, we investigate the influence of fluorine on transport properties using a series of rationally designed poly(oligo(ethylene glycol) methyl ether acrylate)-block-perfluoropolyether (poly(OEGA)_m-PFPE) copolymers. Copolymers with different fluorine contents were prepared and exhibit aggregate in solution in a manner dependent on the fluorine content. Doxorubicin-conjugated poly(OEGA)₂₀-PFPE nanoparticles with lower fluorine content exist in solution as unimers, leading to greater exposure of hydrophobic PFPE segments to the cell surface. This, in turn, results in greater cellular uptake, deeper tumor penetration, as well as enhanced therapeutic efficacy compared to that with the micelle-state nanoaggregates (poly(OEGA)₁₀-PFPE and poly(OEGA)₅-PFPE) with higher fluorine content but with less PFPE exposed to the cell membranes. Our results demonstrate that the aggregation behavior of these fluorinated polymers plays a critical role in internalization and transport in living cells and 3D spheroids, providing important design criteria for the preparation of highly effective delivery agents.

Nonuniform Crowding Enhances Transport

The cellular cytoplasm is crowded with macromolecules and other species that occupy up to 40% of the available volume. Previous studies have reported that for high crowder molecule concentrations, colloidal tracer particles have a dampened diffusion due to the higher solution viscosity. However, these studies employed uniform distributions of crowder molecules. We report a scenario, previously unexplored experimentally, of increased tracer transport driven by a nonuniform concentration of crowder macromolecules. In gradients of a polymeric crowder, tracer particles undergo transport several times higher than that of their bulk diffusion rate. The direction of the transport is toward regions of lower crowder concentration. Mechanistically, hard-sphere interactions and the resulting volume exclusion between the tracer and crowder increase the effective diffusion by inducing a convective motion of tracers, which we explain through modeling. Strikingly, soft deformable particles show even greater enhancement in transport in crowder gradients compared to similarly sized hard particles. Overall, this demonstration of enhanced transport in nonuniform distributions of crowders is anticipated to clarify aspects of multicomponent intracellular transport.

Macromolecular Crowding Tunes Protein Stability by Manipulating Solvent Accessibility

In all intracellular processes, protein structure and dynamics are subject to the influence of macromolecular crowding (MC). Here, the impact of MC agents of different types and sizes on the model protein Bacillus subtilis Cold shock protein B (BsCspB) during both thermal and chemical denaturation have been comprehensively investigated. We consistently reveal a distinct stabilization of BsCspB in a manner dependent on the MC concentration but not on viscosity, polarity, or size of the MC agent used. This general stabilization has been decoded by use of NMR spectroscopy, through monitoring of chemical shift (CS) perturbations and the intramolecular hydrogen‐bonding networks, as well as local protection of amide protons against exchange with solvent protons. Whereas CSs and hydrogen‐bonding networks are not systematically affected in the presence of MC, we detected a pronounced reduction in exchange in loop regions of BsCspB. We conclude that this reduced accessibility of solvent protons is a key parameter for the increases in protein stability seen under MC.

Coarse-Grained Protein Dynamics Studies Using Elastic Network Models

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.

Pair Interaction of Catalytical Sphere Dimers in Chemically Active Media

We study the pair dynamics of two self-propelled sphere dimers in the chemically active medium in which a cubic autocatalytic chemical reaction takes place. Concentration gradient around the dimer, created by reactions occurring on the catalytic sphere surface and responsible for the self-propulsion, is greatly influenced by the chemical activities of the environment. Consequently, the pair dynamics of two dimers mediated by the concentration field are affected. In the particle-based mesoscopic simulation, we combine molecular dynamics (MD) for potential interactions and reactive multiparticle collision dynamics (RMPC) for solvent flow and bulk reactions. Our results indicate three different configurations between a pair of dimers after the collision, i.e., two possible scenarios of bound dimer pairs and one unbound dimer pair. A phase diagram is sketched as a function of the rate coefficients of the environment reactions. Since the pair interactions are the basic elements of larger scale systems, we believe the results may shed light on the understanding of the collective dynamics.

The effect of hydrodynamic interactions on nanoparticle diffusion in polymer solutions: a multiparticle collision dynamics study

The diffusion of nanoparticles (NPs) in polymer solutions is studied by a combination of a mesoscale simulation method, multiparticle collision dynamics (MPCD), and molecular dynamics (MD) simulations. We investigate the long-time diffusion coefficient D as well as the subdiffusive behavior in the intermediate time region. The dependencies of both D and subdiffusion factor α on NP size and polymer concentration, respectively, are explicitly calculated. Particular attention is paid to the role of hydrodynamic interaction (HI) in the NP diffusion dynamics. Our simulation results show that the long-time diffusion coefficients satisfy perfectly the scaling relation found by experimental observations. Meanwhile, the subdiffusive factor decreases with the increase in polymer concentration but is of little relevance to the NP size. By parallel simulations with and without HI, we reveal that HI will generally enhance D, while the enhancement effect is non-monotonous with increasing polymer concentration, and it becomes most pronounced at semidilute concentrations. With the aid of a scaling law based on the diffusive activation energy model, we understand that HI affects diffusion through decreasing the diffusive activation energy on the one hand while increasing the effective diffusion size on the other. In addition, HI will certainly influence the subdiffusive behavior of the NP, leading to a larger subdiffusion exponent.

Diffusion of a Rouse chain in porous media: A mode-coupling-theory study

We use a kinetic mode-coupling theory (MCT) combining with generalized Langevin equation (GLE) to study the diffusion and conformational dynamics of a bead-spring Rouse chain (RC) dissolved in porous media. The media contains fluid particles and immobile matrix ones wherein the latter leads to the lack of translational invariance. The friction kernel ζ(t) used in the GLE can be obtained directly by adopting a simple density-functional approach in which the density correlators calculated by MCT equations of porous media serve as inputs. Due to cage effects generated by surrounding particles, ζ(t) shows a very long tail memory in the high volume fraction of fluid and matrix. It is found that the long-time center-of-mass diffusion constant D_{CM} of the RC decreases with the increment of volume fraction, influencing more strongly by the matrix particles than by the fluid ones. The auto-correlation function (ACF) of the end-to-end distance fluctuation can also be calculated theoretically based on GLE. Of particular interest is that the power-law region of ACF has a nearly fixed length in logarithmic scale when it shifts to longer time range, with increasing the volume fraction of media particles. Moreover, the effect of lack of translational invariance has been investigated by comparing the results between fluid-matrix and pure fluid cases under identical total volume fraction.

Structural fluctuations and thermal stability of proteins in crowded environments: effects of the excluded volume

We perform molecular dynamics simulations for a simple coarse-grained model of a protein placed inside of a softly repulsive sphere of radius R. The protein is surrounded either by a number of same molecules or a number of spherical crowding particles that immitate other biomolecules such as the osmolytes. The two descriptions are shown to lead to distinct results when testing thermal stability as assessed by studying the unfolding times as a function of temperature. We consider three examples of proteins and show that crowding increases the thermal stability provided the inter-protein or protein-crowder interactions are repulsive. On the other hand, an introduction of attraction between the proteins is found to destabilize the proteins. Crowding by repulsive crowder particles is seen to enhance the RMSF in certain exposed regions. The effect grows on decreasing the size of the crowding particles. In the absence of crowding the RMSF anticorrelates with the coordination number related to the residue-residue interaction.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

Polymer Looping Is Controlled by Macromolecular Crowding, Spatial Confinement, and Chain Stiffness

We study by extensive computer simulations the looping characteristics of linear polymers with varying persistence length inside a spherical cavity in the presence of macromolecular crowding. For stiff chains, the looping probability and looping time reveal wildly oscillating patterns as functions of the chain length. The effects of crowding differ dramatically for flexible versus stiff polymers. While for flexible chains the looping kinetics is slowed down by the crowders, for stiffer chains the kinetics turns out to be either decreased or facilitated, depending on the polymer length. For severe confinement, the looping kinetics may become strongly facilitated by crowding. Our findings are of broad impact for DNA looping in the crowded and compartmentalized interior of living biological cells.

Non-universal tracer diffusion in crowded media of non-inert obstacles

For tracer motion in an array of attractive obstacles we observe transient, non-ergodic anomalous diffusion depending on the obstacle density.

Enzyme kinetics and transport in a system crowded by mobile macromolecules

The dynamics of an elastic network model for the enzyme 4-oxalocrotonate tautomerase is studied in a system crowded by mobile macromolecules, also modeled by elastic networks.

Structural features important for differences in protein partitioning in aqueous dextran-polyethylene glycol two-phase systems of different ionic compositions

Partitioning of 15 proteins in dextran-70-polyethylene glycol (PEG)-8000 aqueous two-phase systems (ATPSs) in the presence of 0.01M sodium phosphate buffer, pH7.4 was studied. The effect of salt additives (NaCl, CsCl, Na2SO4, NaClO4 and NaSCN) at different concentrations on the protein partition behavior was examined. The salt effects on protein partitioning were analyzed by using the Collander solvent regression relationship between the protein partition coefficients in ATPSs with and without salt additives. The results obtained show that the presence and concentration of salt additives affect the protein partition behavior. Analysis of ATPSs in terms of the differences between the relative hydrophobicity and electrostatic properties of the phases does not explain the protein partition behavior. The differences between protein partitioning could not be explained by the protein size. The structural signatures for the proteins were constructed from partition coefficient values in four ATPSs with different salt additives, and the structural distances were calculated using cytochrome c as the reference structure. The structural distances for all the examined proteins (except lysozyme) were found to be interrelated. Analysis of about 50 different descriptors of the protein structures revealed that the partition behavior of proteins is determined by the peculiarities of their surfaces (e.g., the number of water-filled cavities and the averaged hydrophobicity of the surface residues) and by the intrinsic flexibility of the protein structure measured in terms of the B-factor (or temperature factor).

Reaching new levels of realism in modeling biological macromolecules in cellular environments

An increasing number of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are additional challenges in integrating different aspects ranging from questions about biomolecular stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomolecules in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomolecules, as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.

Metabolic adaptation and protein complexes in prokaryotes

Protein complexes are classified and have been charted in several large-scale screening studies in prokaryotes. These complexes are organized in a factory-like fashion to optimize protein production and metabolism. Central components are conserved between different prokaryotes; major complexes involve carbohydrate, amino acid, fatty acid and nucleotide metabolism. Metabolic adaptation changes protein complexes according to environmental conditions. Protein modification depends on specific modifying enzymes. Proteins such as trigger enzymes display condition-dependent adaptation to different functions by participating in several complexes. Several bacterial pathogens adapt rapidly to intracellular survival with concomitant changes in protein complexes in central metabolism and optimize utilization of their favorite available nutrient source. Regulation optimizes protein costs. Master regulators lead to up- and downregulation in specific subnetworks and all involved complexes. Long protein half-life and low level expression detaches protein levels from gene expression levels. However, under optimal growth conditions, metabolite fluxes through central carbohydrate pathways correlate well with gene expression. In a system-wide view, major metabolic changes lead to rapid adaptation of complexes and feedback or feedforward regulation. Finally, prokaryotic enzyme complexes are involved in crowding and substrate channeling. This depends on detailed structural interactions and is verified for specific effects by experiments and simulations.