Morphological control of bundled actin networks subject to fixed-mass depletion

Depletion interactions are thought to significantly contribute to the organization of intracellular structures in the crowded cytosol. The strength of depletion interactions depends on physical parameters such as the depletant number density and the depletant size ratio. Cells are known to dynamically regulate these two parameters by varying the copy number of proteins of a wide distribution of sizes. However, mammalian cells are also known to keep the total protein mass density remarkably constant, to within 0.5% throughout the cell cycle. We thus ask how the strength of depletion interactions varies when the total depletant mass is held fixed, a.k.a. fixed-mass depletion. We answer this question via scaling arguments, as well as by studying depletion effects on networks of reconstituted semiflexible actin in silico and in vitro. We examine the maximum strength of the depletion interaction potential U∗ as a function of q, the size ratio between the depletant and the matter being depleted. We uncover a scaling relation U∗ ∼ qζ for two cases: fixed volume fraction φ and fixed mass density ρ. For fixed volume fraction, we report ζ < 0. For the fixed mass density case, we report ζ > 0, which suggests that the depletion interaction strength increases as the depletant size ratio is increased. To test this prediction, we prepared our filament networks at fixed mass concentrations with varying sizes of the depletant molecule poly(ethylene glycol) (PEG). We characterize the depletion interaction strength in our simulations via the mesh size. In experiments, we observe two distinct actin network morphologies, which we call weakly bundled and strongly bundled. We identify a mass concentration where different PEG depletant sizes lead to weakly bundled or strongly bundled morphologies. For these conditions, we find that the mesh size and intra-bundle spacing between filaments across the different morphologies do not show significant differences, while the dynamic light scattering relaxation time and storage modulus between the two states do show significant differences. Our results demonstrate the ability to tune actin network morphology and mechanics by controlling depletant size and give insights into depletion interaction mechanisms under the fixed-depletant-mass constraint relevant to living cells.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

PolyQ-Expanded Mutant Huntingtin Forms Inclusion Body Following Transient Cold Shock in a Two-Step Aggregation Mechanism

Age-dependent formation of insoluble protein aggregates is a hallmark of many neurodegenerative diseases. We are interested in the cell chemistry that drives the aggregation of polyQ-expanded mutant Huntingtin (mHtt) protein into insoluble inclusion bodies (IBs). Using an inducible cell model of Huntington's disease, we show that a transient cold shock (CS) at 4 °C followed by recovery incubation at temperatures of 25-37 °C strongly and rapidly induces the compaction of diffuse polyQ-expanded HuntingtinExon1-enhanced green fluorescent protein chimera protein (mHtt) into round, micron size, cytosolic IBs. This transient CS-induced mHtt IB formation is independent of microtubule integrity or de novo protein synthesis. The addition of millimolar concentrations of sodium chloride accelerates, whereas urea suppresses this transient CS-induced mHtt IB formation. These results suggest that the low temperature of CS constrains the conformation dynamics of the intrinsically disordered mHtt into labile intermediate structures to facilitate de-solvation and hydrophobic interaction for IB formation at the higher recovery temperature. This work, along with our previous observation of the effects of heat shock protein chaperones and osmolytes in driving mHtt IB formation, underscores the primacy of mHtt structuring and rigidification for H-bond-mediated cross-linking in a two-step mechanism of mHtt IB formation in living cells.

Analysis of the effect of metal ions on the ability of Xylanase to hydrolyze wheat bran by molecular dynamics simulations

Introduction: Wheat bran is the main by-product of wheat processing, containing about 30% pentosan and 0.4%-0.7% ferulic acid. Wheat bran is the main raw material used to prepare feruloyl oligosaccharides by hydrolysis of Xylanase, we discovered that the ability of Xylanase to hydrolyze wheat bran could be affected in the presence of different metal ions. Methods: In the present study, we have probed the effects of different metal ions on the hydrolysis activity of Xylanase on wheat bran and tried to analyze the effect of Mn²⁺ and Xylanase by molecular dynamic (MD) simulation. Results: Our results suggested that Mn²⁺ had improved the Xylanase hydrolyzing wheat bran to obtain feruloyl oligosaccharides. Particularly when the concentration of Mn²⁺ reached 4 mmol/L, the optimal product has been obtained 2.8 times higher to compare with no addition. Through the MD simulation analysis, our results reveal that Mn²⁺ can induce structural change in the active site, which enlarges the substrate binding pocket. The simulation results also revealed that the addition of Mn²⁺ resulted in a low RMSD value compared with the absence of Mn²⁺ and helped stabilize the complex. Conclusion: Mn²⁺ could increase the enzymatic activity of Xylanase in the hydrolysis of feruloyl oligosaccharides in wheat bran. The finding could have significant implications for the preparation of feruloyl oligosaccharides from wheat bran.

In silico screening, molecular dynamic simulations, and in vitro activity of selected natural compounds as an inhibitor of Leishmania donovani 3-mercaptopyruvate sulfurtransferase

In Leishmania sp., the enzymes of de novo cysteine biosynthesis pathway require sulfide. Other organisms utilize sulfide through the sulfide reduction pathway, but Leishmania lacks the gene that encodes these enzymes. Hence, the major source of sulfide for Leishmania is believed to be from the action of 3-mercaptopyruvate sulfurtransferase (3MST) on 3-mercapto-pyruvate (3MP). There has been no effort reported in the past to screen inhibitors against L. donovani 3MST (Ld3MST). As a result, this study examines natural compounds that are potent against Ld3MST and validates it by in vitro activity and cytotoxicity tests. Initially, a library of ~ 5000 natural compounds was subjected to molecular docking approach for screening, and the best hit was validated using a long-term molecular dynamic simulation (MD). Among the docking results, quercetine-3-rutinoside (Rutin) was deemed the best hit. The results of the MD indicated that Rutin was highly capable of interacting with the varied active site segments, possibly blocking substrate access. Additionally, promastigotes and amastigotes were tested for Rutin activity and the IC50 was found to be 40.95 and 90.09 μM, respectively. Similarly, the cytotoxicity assay revealed that Rutin was not toxic even at a concentration of 819.00 μM to THP-1 cell lines. Additionally, the Ld3MST was cloned, purified, and evaluated for enzyme activity in the presence of Rutin. Reduction in the enzyme activity (~ 85%) was observed in the presence of ~ 40 μM Rutin. Thus, this study suggests that Rutin may act as a potent inhibitor of Ld3MST. With further in vivo investigations, Rutin could be a small molecule of choice for combating leishmaniasis.

Allosteric Binding Sites of Ab Peptides on the Acetylcholine Synthesizing Enzyme ChAT as Deduced by In Silico Molecular Modeling

The native function of amyloid-β (Aβ) peptides is still unexplored. However, several recent reports suggest a prominent role of Aβ peptides in acetylcholine homeostasis. To clarify this role of Aβ, we have reported that Aβ peptides at physiological concentrations can directly enhance the catalytic efficiency of the key cholinergic enzyme, choline acetyltransferase (ChAT), via an allosteric interaction. In the current study, we further aimed to elucidate the underlying ChAT-Aβ interaction mechanism using in silico molecular docking and dynamics analysis. Docking analysis suggested two most probable binding clusters on ChAT for Aβ40 and three for Aβ42. Most importantly, the docking results were challenged with molecular dynamic studies of 100 ns long simulation in triplicates (100 ns × 3 = 300 ns) and were analyzed for RMSD, RMSF, RoG, H-bond number and distance, SASA, and secondary structure assessment performed together with principal component analysis and the free-energy landscape diagram, which indicated that the ChAT-Aβ complex system was stable throughout the simulation time period with no abrupt motion during the evolution of the simulation across the triplicates, which also validated the robustness of the simulation study. Finally, the free-energy landscape analysis confirmed the docking results and demonstrated that the ChAT-Aβ complexes were energetically stable despite the unstructured nature of C- and N-terminals in Aβ peptides. Overall, this study supports the reported in vitro findings that Aβ peptides, particularly Aβ42, act as endogenous ChAT-Potentiating-Ligand (CPL), and thereby supports the hypothesis that one of the native biological functions of Aβ peptides is the regulation of acetylcholine homeostasis.

Neural tube patterning: from a minimal model for rostrocaudal patterning toward an integrated 3D model

Rostrocaudal patterning of the neural tube is a defining event in vertebrate brain development. This process is driven by morphogen gradients which specify the fate of neural progenitor cells, leading to the partitioning of the tube. Although this is extensively studied experimentally, an integrated view of the genetic circuitry is lacking. Here, we present a minimal gene regulatory model for rostrocaudal patterning, whose tristable topology was determined in a data-driven way. Using this model, we identified the repression of hindbrain fate as promising strategy for the improvement of current protocols for the generation of dopaminergic neurons. Furthermore, we combined our model with an established minimal model for dorsoventral patterning on a realistic 3D neural tube and found that key features of neural tube patterning could be recapitulated. Doing so, we demonstrate how data and models from different sources can be combined to simulate complex in vivo processes.

Survival of Virus Particles in Water Droplets: Hydrophobic Forces and Landauer's Principle

Many small biological objects, such as viruses, survive in a water environment and cannot remain active in dry air without condensation of water vapor. From a physical point of view, these objects belong to the mesoscale, where small thermal fluctuations with the characteristic kinetic energy of k_BT (where k_B is the Boltzmann’s constant and T is the absolute temperature) play a significant role. The self-assembly of viruses, including protein folding and the formation of a protein capsid and lipid bilayer membrane, is controlled by hydrophobic forces (i.e., the repulsing forces between hydrophobic particles and regions of molecules) in a water environment. Hydrophobic forces are entropic, and they are driven by a system’s tendency to attain the maximum disordered state. On the other hand, in information systems, entropic forces are responsible for erasing information, if the energy barrier between two states of a switch is on the order of k_BT, which is referred to as Landauer’s principle. We treated hydrophobic interactions responsible for the self-assembly of viruses as an information-processing mechanism. We further showed a similarity of these submicron-scale processes with the self-assembly in colloidal crystals, droplet clusters, and liquid marbles.

Insight into the Microcosm of the Human Growth Hormone and Its Interactions with Polymers and Copolymers: A Molecular Dynamics Perspective

Therapeutic proteins nowadays have increasingly been applied for their considerable potential in treating a wide variety of diseases. The effectiveness and potency of native therapeutic proteins are limited by various factors (e.g., stability, blood circulation time, specificity). Over the past years, a great deal of effort has been devoted to developing safe and efficient protein delivery systems. Entrapment of protein into polymeric and copolymeric matrices is common among the different types of protein-based drug formulation. However, despite the massive efforts toward developing therapeutic protein delivery in experimental studies and industrial applications, there is relatively little data on the influence of polymers and copolymers on therapeutic proteins at the atomic and molecular levels. Herein, molecular dynamics (MD) simulations are used to study the effects of biocompatible synthetic polymers including methoxy poly(ethylene glycol) (MPEG), poly(lactic acid) (PLA), and poly(lactic acid) copolymers (poly(lactic-co-glycolic acid)) PLGA and MPEG-PLA(PELA)) on the structure and dynamics of the human growth hormone (hGH), and the results are compared with previous experimental findings. Our results indicate that the hGH conformation remains stable both in pure water and in the presence of polymers, and these results are in good agreement with previous experimental data. It is shown that the MPEG chains are self-assembled and folded into a semicrystalline structure; therefore, only a small portion of the protein interacts with the polymer. The other three polymers, however, interact well with the protein and partially cover its surface. Our findings suggest that the use of these polymers for protein encapsulation has the advantage of reducing protein aggregation and thus increasing drug serum half-life. Eventually, we anticipate that the research results will expand the current knowledge about encapsulation mechanisms and the molecular interactions between hGH and the polymers.

Glutenin and Gliadin, a Piece in the Puzzle of their Structural Properties in the Cell Described through Monte Carlo Simulations

Gluten protein crosslinking is a predetermined process where specific intra- and intermolecular disulfide bonds differ depending on the protein and cysteine motif. In this article, all-atom Monte Carlo simulations were used to understand the formation of disulfide bonds in gliadins and low molecular weight glutenin subunits (LMW-GS). The two intrinsically disordered proteins appeared to contain mostly turns and loops and showed "self-avoiding walk" behavior in water. Cysteine residues involved in intramolecular disulfide bonds were located next to hydrophobic peptide sections in the primary sequence. Hydrophobicity of neighboring peptide sections, synthesis chronology, and amino acid chain flexibility were identified as important factors in securing the specificity of intramolecular disulfide bonds formed directly after synthesis. The two LMW-GS cysteine residues that form intermolecular disulfide bonds were positioned next to peptide sections of lower hydrophobicity, and these cysteine residues are more exposed to the cytosolic conditions, which influence the crosslinking behavior. In addition, coarse-grained Monte Carlo simulations revealed that the protein folding is independent of ionic strength. The potential molecular behavior associated with disulfide bonds, as reported here, increases the biological understanding of seed storage protein function and provides opportunities to tailor their functional properties for different applications.

Self-organized emergence of folded protein-like network structures from geometric constraints

The intricate three-dimensional geometries of protein tertiary structures underlie protein function and emerge through a folding process from one-dimensional chains of amino acids. The exact spatial sequence and configuration of amino acids, the biochemical environment and the temporal sequence of distinct interactions yield a complex folding process that cannot yet be easily tracked for all proteins. To gain qualitative insights into the fundamental mechanisms behind the folding dynamics and generic features of the folded structure, we propose a simple model of structure formation that takes into account only fundamental geometric constraints and otherwise assumes randomly paired connections. We find that despite its simplicity, the model results in a network ensemble consistent with key overall features of the ensemble of Protein Residue Networks we obtained from more than 1000 biological protein geometries as available through the Protein Data Base. Specifically, the distribution of the number of interaction neighbors a unit (amino acid) has, the scaling of the structure’s spatial extent with chain length, the eigenvalue spectrum and the scaling of the smallest relaxation time with chain length are all consistent between model and real proteins. These results indicate that geometric constraints alone may already account for a number of generic features of protein tertiary structures.

PET-RAFT and SAXS: High Throughput Tools to Study Compactness and Flexibility of Single-Chain Polymer Nanoparticles

From protein science, it is well understood that ordered folding and 3D structure mainly arises from balanced and noncovalent polar and nonpolar interactions, such as hydrogen bonding. Similarly, it is understood that single-chain polymer nanoparticles (SCNPs) will also compact and become more rigid with greater hydrophobicity and intrachain hydrogen bonding. Here, we couple high throughput photoinduced electron/energy transfer reversible addition-fragmentation chain-transfer (PET-RAFT) polymerization with high throughput small-angle X-ray scattering (SAXS) to characterize a large combinatorial library (>450) of several homopolymers, random heteropolymers, block copolymers, PEG-conjugated polymers, and other polymer-functionalized polymers. Coupling these two high throughput tools enables us to study the major influence(s) for compactness and flexibility in higher breadth than ever before possible. Not surprisingly, we found that many were either highly disordered in solution, in the case of a highly hydrophilic polymer, or insoluble if too hydrophobic. Remarkably, we also found a small group (9/457) of PEG-functionalized random heteropolymers and block copolymers that exhibited compactness and flexibility similar to that of bovine serum albumin (BSA) by dynamic light scattering (DLS), NMR, and SAXS. In general, we found that describing a rough association between compactness and flexibility parameters (R g /R h and Porod Exponent, respectively) with logP, a quantity that describes hydrophobicity, helps to demonstrate and predict material parameters that lead to SCNPs with greater compactness, rigidity, and stability. Future implementation of this combinatorial and high throughput approach for characterizing SCNPs will allow for the creation of detailed design parameters for well-defined macromolecular chemistry.

RMalign: an RNA structural alignment tool based on a novel scoring function RMscore

Background

RNA-protein 3D complex structure prediction is still challenging. Recently, a template-based approach PRIME is proposed in our team to build RNA-protein 3D complex structure models with a higher success rate than computational docking software. However, scoring function of RNA alignment algorithm SARA in PRIME is size-dependent, which limits its ability to detect templates in some cases.

Results

Herein, we developed a novel RNA 3D structural alignment approach RMalign, which is based on a size-independent scoring function RMscore. The parameter in RMscore is then optimized in randomly selected RNA pairs and phase transition points (from dissimilar to similar) are determined in another randomly selected RNA pairs. In tRNA benchmarking, the precision of RMscore is higher than that of SARAscore (0.88 and 0.78, respectively) with phase transition points. In balance-FSCOR benchmarking, RMalign performed as good as ESA-RNA with a non-normalized score measuring RNA structural similarity. In balance-x-FSCOR benchmarking, RMalign achieves much better than a state-of-the-art RNA 3D structural alignment approach SARA due to a size-independent scoring function. Take the advantage of RMalign, we update our RNA-protein modeling approach PRIME to version 2.0. The PRIME2.0 significantly improves about 10% success rate than PRIME.

Conclusion

Based on a size-independent scoring function RMscore, a novel RNA 3D structural alignment approach RMalign is developed and integrated into PRIME2.0, which could be useful for the biological community in modeling protein-RNA interaction.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5631-3) contains supplementary material, which is available to authorized users.

Translocation of non-interacting heteropolymer protein chains in terms of single helical propensity and size

In this work we present an analytical framework to calculate the average translocation time τ required for an ideal proteinogenic polypeptide chain to cross over a small pore on a membrane. Translocation is considered to proceed as a chain of non-interacting amino acid residues of sequence {X_j} diffuses through the pore against an energy barrier Δℱ, set by chain entropy and unfolding-folding energetics. We analyze the effect of sequence heterogeneity on the dynamics of translocation by means of helical propensity of amino acid residues. In our calculations we use sequences of fifteen well-known proteins that are translocated which span two orders of magnitude in size according to the number of residues N. Results show non-symmetric free energy barriers as a consequence of sequence heterogeneity, such asymmetry in energy may be useful in differentiated directions of translocation. For the fifteen polypeptide chains considered we found conditions when sequence heterogeneity has not a significant effect on the time scale of translocation leading to a scaling law τ ∝ N^ν, where ν ∼ 1.6 is an exponent that holds for most ground state energies. We also identify conditions when sequence heterogeneity has a great impact on the time scale of translocation, in consequence, no more scaling laws for τ there exist.

A theoretical and experimental investigation of the effect of sodium dodecyl sulfate on the structural and conformational properties of bovine β-casein

A predicted three-dimensional structure of bovine β-casein was constructed using homology modeling with the aid of MODELLER and I-TASSER programs, with the validity and reliability of the models evaluated according to stereochemical qualities and small angle X-ray scattering. By comparing the results obtained from the two models using the CRYSOL program, an optimal model of the β-casein structure derived from I-TASSER was selected and used in subsequent molecular dynamics (MD) analysis. 300 ns MD simulations of β-casein in water and in the presence of different SDS concentrations at 300 K were performed. The results of the MD simulations indicated that SDS molecules played a dual role in modifying the conformation of β-casein at 300 K. Concentrations of SDS below its CMC (1 mM), at which only the monomer form of SDS was present, induced β-casein to lose its secondary structure by converting helices into random coils; however the conformation of the complex was still comparable with that of native β-casein. In the presence of 10 mM SDS (above its CMC), the helical content of β-casein was increased along with reduced random coils, and the structural rearrangement led to a more compact conformation. The latter change is likely related to the hydrophobic interactions that dominate the binding of the C-terminal region, along with the anchoring of sulfate groups of SDS on the positively charged N-terminal portion via electrostatic attraction. Hydrogen bonding supplemented the SDS-induced stabilization of β-casein. A correlated "necklace and bead" model, in which the micelles nucleate on the protein hydrophobic sites, was proposed for the structure of β-casein-SDS complexes.

Hydrophobic Surface Enhances Electrostatic Interaction in Water

A high dielectric constant is one of the peculiar properties of liquid water, indicating that the electrostatic interaction between charged substances is largely reduced in water. We show by molecular dynamics simulation that the dielectric constant of water is decreased near the hydrophobic surface. We further show that the decrease in the dielectric constant is due to both the decreased water density and the reduced water dipole correlation in the direction perpendicular to the surface. We finally demonstrate that electrostatic interaction in water is actually strengthened near the hydrophobic surface.

Multiple scales and phases in discrete chains with application to folded proteins

Chiral heteropolymers such as large globular proteins can simultaneously support multiple length scales. The interplay between the different scales brings about conformational diversity, determines the phase properties of the polymer chain, and governs the structure of the energy landscape. Most importantly, multiple scales produce complex dynamics that enable proteins to sustain live matter. However, at the moment there is incomplete understanding of how to identify and distinguish the various scales that determine the structure and dynamics of a complex protein. Here we address this impending problem. We develop a methodology with the potential to systematically identify different length scales, in the general case of a linear polymer chain. For this we introduce and analyze the properties of an order parameter that can both reveal the presence of different length scales and can also probe the phase structure. We first develop our concepts in the case of chiral homopolymers. We introduce a variant of Kadanoff's block-spin transformation to coarse grain piecewise linear chains, such as the Cα backbone of a protein. We derive analytically, and then verify numerically, a number of properties that the order parameter can display, in the case of a chiral polymer chain. In particular, we propose that in the case of a chiral heteropolymer the order parameter can reveal traits of several different phases, contingent on the length scale at which it is scrutinized. We confirm that this is the case with crystallographic protein structures in the Protein Data Bank. Thus our results suggest relations between the scales, the phases, and the complexity of folding pathways.

On-chip measurements of protein unfolding from direct observations of micron-scale diffusion

The unfolding process of BSA in solution as a function of pH was studied by microfluidic diffusional sizing device.

Investigations of protein folding, unfolding and stability are critical for the understanding of the molecular basis of biological structure and function. We describe here a microfluidic approach to probe the unfolding of unlabelled protein molecules in microliter volumes. We achieve this objective through the use of a microfluidic platform, which allows the changes in molecular diffusivity upon folding and unfolding to be detected directly. We illustrate this approach by monitoring the unfolding of bovine serum albumin in solution as a function of pH. These results show the viability of probing protein stability on chip in small volumes.

Molecular Dynamic Analysis of Hyaluronic Acid and Phospholipid Interaction in Tribological Surgical Adjuvant Design for Osteoarthritis

Tribological surgical adjuvants constitute a therapeutic discipline made possible by surgical advances in the treatment of damaged articular cartilage beyond palliative care. The purpose of this study is to analyze interactions between hyaluronic acid and phospholipid molecules, and the formation of geometric forms, that play a role in the facilitated lubrication of synovial joint organ systems. The analysis includes an evaluation of the pathologic state to detail conditions that may be encountered by adjuvants during surgical convalescence. The synovial fluid changes in pH, hyaluronic acid polydispersity, and phospholipid concentration associated with osteoarthritis are presented as features that influence the lubricating properties of adjuvant candidates. Molecular dynamic simulation studies are presented, and the Rouse model is deployed, to rationalize low molecular weight hyaluronic acid behavior in an osteoarthritic environment of increased pH and phospholipid concentration. The results indicate that the hyaluronic acid radius of gyration time evolution is both pH- and phospholipid concentration-dependent. Specifically, dipalmitoylphosphatidylcholine induces hydrophobic interactions in the system, causing low molecular weight hyaluronic acid to shrink and at high concentration be absorbed into phospholipid vesicles. Low molecular weight hyaluronic acid appears to be insufficient for use as a tribological surgical adjuvant because an increased pH and phospholipid concentration induces decreased crosslinking that prevents the formation of supramolecular lubricating forms. Dipalmitoylphosphatidylcholine remains an adjuvant candidate for certain clinical situations. The need to reconcile osteoarthritic phenotypes is a prerequisite that should serve as a framework for future adjuvant design and subsequent tribological testing.

Molecular dynamics analysis of the aggregation propensity of polyglutamine segments

Protein misfolding and aggregation is a pathogenic feature shared among at least ten polyglutamine (polyQ) neurodegenerative diseases. While solvent-solution interaction is a key factor driving protein folding and aggregation, the solvation properties of expanded polyQ tracts are not well understood. By using GPU-enabled all-atom molecular dynamics simulations of polyQ monomers in an explicit solvent environment, this study shows that solvent-polyQ interaction propensity decreases as the lengths of polyQ tract increases. This study finds a predominance in long-distance interactions between residues far apart in polyQ sequences with longer polyQ segments, that leads to significant conformational differences. This study also indicates that large loops, comprised of parallel β-structures, appear in long polyQ tracts and present new aggregation building blocks with aggregation driven by long-distance intra-polyQ interactions. Finally, consistent with previous observations using coarse-grain simulations, this study demonstrates that there is a gain in the aggregation propensity with increased polyQ length, and that this gain is correlated with decreasing ability of solvent-polyQ interaction. These results suggest the modulation of solvent-polyQ interactions as a possible therapeutic strategy for treating polyQ diseases.

Characterizing single chain nanoparticles (SCNPs): a critical survey

We provide the results of a critical literature survey on the reported sizes of single chain polymer nanoparticles (SCNPs) employing different techniques.

Thermodynamics of Macromolecular Association in Heterogeneous Crowding Environments: Theoretical and Simulation Studies with a Simplified Model

The cytoplasm of a cell is crowded with many different kinds of macromolecules. The macromolecular crowding affects the thermodynamics and kinetics of biological reactions in a living cell, such as protein folding, association, and diffusion. Theoretical and simulation studies using simplified models focus on the essential features of the crowding effects and provide a basis for analyzing experimental data. In most of the previous studies on the crowding effects, a uniform crowder size is assumed, which is in contrast to the inhomogeneous size distribution of macromolecules in a living cell. Here, we evaluate the free energy changes upon macromolecular association in a cell-like inhomogeneous crowding system via a theory of hard-sphere fluids and free energy calculations using Brownian dynamics trajectories. The inhomogeneous crowding model based on 41 different types of macromolecules represented by spheres with different radii mimics the physiological concentrations of macromolecules in the cytoplasm of Mycoplasma genitalium. The free energy changes of macromolecular association evaluated by the theory and simulations were in good agreement with each other. The crowder size distribution affects both specific and nonspecific molecular associations, suggesting that not only the volume fraction but also the size distribution of macromolecules are important factors for evaluating in vivo crowding effects. This study relates in vitro experiments on macromolecular crowding to in vivo crowding effects by using the theory of hard-sphere fluids with crowder-size heterogeneity.

Scaling Laws in Spatial Network Formation

Geometric constraints impact the formation of a broad range of spatial networks, from amino acid chains folding to proteins structures to rearranging particle aggregates. How the network of interactions dynamically self-organizes in such systems is far from fully understood. Here, we analyze a class of spatial network formation processes by introducing a mapping from geometric to graph-theoretic constraints. Combining stochastic and mean field analyses yields an algebraic scaling law for the extent (graph diameter) of the resulting networks with system size, in contrast to logarithmic scaling known for networks without constraints. Intriguingly, the exponent falls between that of self-avoiding random walks and that of space filling arrangements, consistent with experimentally observed scaling of the radius of gyration of protein tertiary structures with their chain length.

Effects of the linker region on the structure and function of modular GH5 cellulases

The association of glycosyl hydrolases with catalytically inactive modules is a successful evolutionary strategy that is commonly used by biomass-degrading microorganisms to digest plant cell walls. The presence of accessory domains in these enzymes is associated with properties such as higher catalytic efficiency, extension of the catalytic interface and targeting of the enzyme to the proper substrate. However, the importance of the linker region in the synergistic action of the catalytic and accessory domains remains poorly understood. Thus, this study examined how the inter-domain region affects the structure and function of modular GH5 endoglucanases, by using cellulase 5A from Bacillus subtilis (BsCel5A) as a model. BsCel5A variants featuring linkers with different stiffnesses or sizes were designed and extensively characterized, revealing that changes in flexibility or rigidity in this region differentially affect kinetic behavior. Regarding the linker length, we found that precise inter-domain spacing is required to enable efficient hydrolysis because excessively long or short linkers were equally detrimental to catalysis. Together, these findings identify molecular and structural features that may contribute to the rational design of chimeric and multimodular glycosyl hydrolases.

Hydrodynamic Radii of Ranibizumab, Aflibercept and Bevacizumab Measured by Time-Resolved Phosphorescence Anisotropy

PURPOSE

To measure the hydrodynamic radii of intravitreal anti-VEGF drugs ranibizumab, aflibercept and bevacizumab with μs time-resolved phosphorescence anisotropy.

METHODS

Ruthenium-based dye Ru(bpy)2(mcbpy - O - Su - ester)(PF6)2, whose lifetime of several hundred nanoseconds is comparable to the rotational correlation time of these drugs in buffer, was used as a label. The hydrodynamic radii were calculated from the rotational correlation times of the Ru(bpy)2(mcbpy - O - Su - ester)(PF6)2-labelled drugs obtained with time-resolved phosphorescence anisotropy measurements in buffer/glycerol solutions of varying viscosity.

RESULTS

The measured radii of 2.76±0.04 nm for ranibizumab, 3.70±0.03 nm for aflibercept and 4.58±0.01 nm for bevacizumab agree with calculations based on molecular weight and other experimental measurements.

CONCLUSIONS

Time-resolved phosphorescence anisotropy is a relatively simple and straightforward method that allows experimental measurement of the hydrodynamic radius of individual proteins, and is superior to theoretical calculations which cannot give the required accuracy for a particular protein.

Enhanced sampling simulation analysis of the structure of lignin in the THF–water miscibility gap

Using temperature replica-exchange molecular dynamics, we characterize a globule-to-coil transition for a softwood-like lignin biopolymer in a tetrahydrofuran (THF)–water cosolvent system at temperatures at which the cosolvent undergoes a de-mixing transition.

Soft matter food physics--the physics of food and cooking

This review discusses the (soft matter) physics of food. Although food is generally not considered as a typical model system for fundamental (soft matter) physics, a number of basic principles can be found in the interplay between the basic components of foods, water, oil/fat, proteins and carbohydrates. The review starts with the introduction and behavior of food-relevant molecules and discusses food-relevant properties and applications from their fundamental (multiscale) behavior. Typical food aspects from 'hard matter systems', such as chocolates or crystalline fats, to 'soft matter' in emulsions, dough, pasta and meat are covered and can be explained on a molecular basis. An important conclusion is the point that the macroscopic properties and the perception are defined by the molecular interplay on all length and time scales.

A comparative study of structural and conformational properties of casein kinase-1 isoforms: insights from molecular dynamics and principal component analysis

Wnt signaling pathway regulates several developmental processes in human; however recently this pathway has been associated with development of different types of cancers. Casein kinase-1 (CK1) constitutes a family of serine-threonine protein kinase; various members of this family participate in Wnt signal transduction pathway and serve as molecular switch to this pathway. Among the known six isoforms of CK1, in human, at least three isoforms (viz. alpha, delta and epsilon) have been reported as oncogenic. The development of common therapeutics against these kinases is an arduous task; unless we have the detailed information of their tertiary structures and conformational properties. In the present work, the dynamical and conformational properties for each of three isoforms of CK1 are explored through molecular dynamics (MD) simulations. The conformational space distribution of backbone atoms is evaluated using principal component analysis of MD data, which are further validated on the basis of potential energy surface. Based on these analytics, it is suggested that conformational subspace shifts upon binding to ligands and guides the kinase action of CK1 isoforms. Further, this paper as a first effort to concurrently study all the three isoforms of CK1 provides structural basis for development of common anticancer therapeutics against three isoforms of CK1.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks

Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden dynamics within protein interaction networks.

Cells are complex dynamic systems, and a central challenge in modern cell biology is to capture information about interactions between the molecules underlying cellular processes. Proteins rarely act alone; more often they form functional partnerships that can specify the timing and/or location of activity. These partnerships are subject to dynamic changes, and thus protein interactions within complexes undergo continuous transitions. Genetic and biochemical evidence suggest that regulation or depletion of a single protein can alter the stability and activity of an entire protein complex. Experimental approaches that detect interactions within living cells provide critical information for the dynamical system that protein complexes represent; yet complexes are often depicted as static 2-dimensional networks. We have built a system that projects in vivo protein interaction datasets as 3-dimensional virtual protein complexes. By using this method to approximate the diffusion of complex components, we can predict transient conformational states and estimate their abundance in living cells. Our method offers biologists a framework to correlate experimental phenotypes with predicted complex dynamics such as short or long-range effects of a single perturbation to the function of the whole ensemble.

Long range correlations and folding angle with applications to α-helical proteins

The conformational complexity of chain-like macromolecules such as proteins and other linear polymers is much larger than that of point-like atoms and molecules. Unlike particles, chains can bend, twist, and even become knotted. Thus chains might also display a much richer phase structure. Unfortunately, it is not very easy to characterize the phase of a long chain. Essentially, the only known attribute is the radius of gyration. The way how it changes when the degree of polymerization becomes different, and how it evolves when the ambient temperature and solvent properties change, is commonly used to disclose the phase. But in any finite length chain there are corrections to scaling that complicate the detailed analysis of the phase structure. Here we introduce a quantity that we call the folding angle to identify and scrutinize the phase structure, as a complement to the radius of gyration. We argue for a mean-field level relationship between the folding angle and the scaling exponent in the radius of gyration. We then estimate the value of the folding angle in the case of crystallographic α-helical protein structures in the Protein Data Bank. We also show how the experimental value of the folding angle can be obtained computationally, using a semiclassical Born-Oppenheimer description of α-helical chiral chains.

Topology and structural self-organization in folded proteins

Topological methods are indispensable in theoretical studies of particle physics, condensed matter physics, and gravity. These powerful techniques have also been applied to biological physics. For example, knowledge of DNA topology is pivotal to the understanding as to how living cells function. Here, the biophysical repertoire of topological methods is extended, with the aim to understand and characterize the global structure of a folded protein. For this, the elementary concept of winding number of a vector field on a plane is utilized to introduce a topological quantity called the folding index of a crystallographic protein. It is observed that in the case of high resolution protein crystals, the folding index, when evaluated over the entire length of the crystallized protein backbone, has a very clear and strong propensity towards integer values. The observation proposes that the way how a protein folds into its biologically active conformation is a structural self-organization process with a topological facet that relates to the concept of solitons. It is proposed that the folding index has a potential to become a useful tool for the global, topological characterization of the folding pathways.

Effect of heat treatment on wheat dough rheology and wheat protein solubility

In the present study, the influence of moisture content, temperature and time during heat treatment of wheat flour was investigated. Heat treatment was carried out on laboratory scale in a water bath at 50–90 ℃ for times up to 3 h. Flour functionality was evaluated by analysing protein solubility in acetic acid as well as by the formation of bread-like doughs, which were then analysed with dynamic oscillatory and rotational rheometry. Effects during heat treatment were explained on a molecular level using a simplified physical model describing wheat dough as a continuous gluten matrix with starch as filler particles. Heat treatment causes the formation of gluten aggregates resulting in decreased protein solubility and lower network strength of dough. Rheological data also indicate the formation of starch aggregates and modified interactions between gluten and starch. The effects were more pronounced in heat-treated flours with increased moisture content due to a higher mobility of the molecules.

Coexistence of phases in a protein heterodimer

A heterodimer consisting of two or more different kinds of proteins can display an enormous number of distinct molecular architectures. The conformational entropy is an essential ingredient in the Helmholtz free energy and, consequently, these heterodimers can have a very complex phase structure. Here, it is proposed that there is a state of proteins, in which the different components of a heterodimer exist in different phases. For this purpose, the structures in the protein data bank (PDB) have been analyzed, with radius of gyration as the order parameter. Two major classes of heterodimers with their protein components coexisting in different phases have been identified. An example is the PDB structure 3DXC. This is a transcriptionally active dimer. One of the components is an isoform of the intra-cellular domain of the Alzheimer-disease related amyloid precursor protein (AICD), and the other is a nuclear multidomain adaptor protein in the Fe65 family. It is concluded from the radius of gyration that neither of the two components in this dimer is in its own collapsed phase, corresponding to a biologically active protein. The UNRES energy function has been utilized to confirm that, if the two components are separated from each other, each of them collapses. The results presented in this work show that heterodimers whose protein components coexist in different phases, can have intriguing physical properties with potentially important biological consequences.

Comparative modeling and protein-like features of hydrophobic-polar models on a two-dimensional lattice

Lattice models of proteins have been extensively used to study protein thermodynamics, folding dynamics, and evolution. Our study considers two different hydrophobic-polar (HP) models on the 2D square lattice: the purely HP model and a model where a compactness-favoring term is added. We exhaustively enumerate all the possible structures in our models and perform the study of their corresponding folds, HP arrangements in space and shapes. The two models considered differ greatly in their numbers of structures, folds, arrangements, and shapes. Despite their differences, both lattice models have distinctive protein-like features: (1) Shapes are compact in both models, especially when a compactness-favoring energy term is added. (2) The residue composition is independent of the chain length and is very close to 50% hydrophobic in both models, as we observe in real proteins. (3) Comparative modeling works well in both models, particularly in the more compact one. The fact that our models show protein-like features suggests that lattice models incorporate the fundamental physical principles of proteins. Our study supports the use of lattice models to study questions about proteins that require exactness and extensive calculations, such as protein design and evolution, which are often too complex and computationally demanding to be addressed with more detailed models.

Physical limits of cells and proteomes

What are the physical limits to cell behavior? Often, the physical limitations can be dominated by the proteome, the cell's complement of proteins. We combine known protein sizes, stabilities, and rates of folding and diffusion, with the known protein-length distributions P(N) of proteomes (Escherichia coli, yeast, and worm), to formulate distributions and scaling relationships in order to address questions of cell physics. Why do mesophilic cells die around 50 °C? How can the maximal growth-rate temperature (around 37 °C) occur so close to the cell-death temperature? The model shows that the cell's death temperature coincides with a denaturation catastrophe of its proteome. The reason cells can function so well just a few degrees below their death temperature is because proteome denaturation is so cooperative. Why are cells so dense-packed with protein molecules (about 20% by volume)? Cells are packed at a density that maximizes biochemical reaction rates. At lower densities, proteins collide too rarely. At higher densities, proteins diffuse too slowly through the crowded cell. What limits cell sizes and growth rates? Cell growth is limited by rates of protein synthesis, by the folding rates of its slowest proteins, and--for large cells--by the rates of its protein diffusion. Useful insights into cell physics may be obtainable from scaling laws that encapsulate information from protein knowledge bases.

Fractal symmetry of protein interior: what have we learned?

The application of fractal dimension-based constructs to probe the protein interior dates back to the development of the concept of fractal dimension itself. Numerous approaches have been tried and tested over a course of (almost) 30 years with the aim of elucidating the various facets of symmetry of self-similarity prevalent in the protein interior. In the last 5 years especially, there has been a startling upsurge of research that innovatively stretches the limits of fractal-based studies to present an array of unexpected results on the biophysical properties of protein interior. In this article, we introduce readers to the fundamentals of fractals, reviewing the commonality (and the lack of it) between these approaches before exploring the patterns in the results that they produced. Clustering the approaches in major schools of protein self-similarity studies, we describe the evolution of fractal dimension-based methodologies. The genealogy of approaches (and results) presented here portrays a clear picture of the contemporary state of fractal-based studies in the context of the protein interior. To underline the utility of fractal dimension-based measures further, we have performed a correlation dimension analysis on all of the available non-redundant protein structures, both at the level of an individual protein and at the level of structural domains. In this investigation, we were able to separately quantify the self-similar symmetries in spatial correlation patterns amongst peptide-dipole units, charged amino acids, residues with the π-electron cloud and hydrophobic amino acids. The results revealed that electrostatic environments in the interiors of proteins belonging to 'α/α toroid' (all-α class) and 'PLP-dependent transferase-like' domains (α/β class) are highly conducive. In contrast, the interiors of 'zinc finger design' ('designed proteins') and 'knottins' ('small proteins') were identified as folds with the least conducive electrostatic environments. The fold 'conotoxins' (peptides) could be unambiguously identified as one type with the least stability. The same analyses revealed that peptide-dipoles in the α/β class of proteins, in general, are more correlated to each other than are the peptide-dipoles in proteins belonging to the all-α class. Highly favorable electrostatic milieu in the interiors of TIM-barrel, α/β-hydrolase structures could explain their remarkably conserved (evolutionary) stability from a new light. Finally, we point out certain inherent limitations of fractal constructs before attempting to identify the areas and problems where the implementation of fractal dimension-based constructs can be of paramount help to unearth latent information on protein structural properties.

Gauge field theory of chirally folded homopolymers with applications to folded proteins

We combine the principle of gauge invariance with extrinsic string geometry to develop a lattice model that can be employed to theoretically describe properties of chiral, unbranched homopolymers. We find that in its low temperature phase the model is in the same universality class with proteins that are deposited in the Protein Data Bank, in the sense of the compactness index. We apply the model to analyze various statistical aspects of folded proteins. Curiously we find that it can produce results that are a very good good match to the data in the Protein Data Bank.

Structural studies of tri-functional human GART

Human purine de novo synthesis pathway contains several multi-functional enzymes, one of which, tri-functional GART, contains three enzymatic activities in a single polypeptide chain. We have solved structures of two domains bearing separate catalytic functions: glycinamide ribonucleotide synthetase and aminoimidazole ribonucleotide synthetase. Structures are compared with those of homologous enzymes from prokaryotes and analyzed in terms of the catalytic mechanism. We also report small angle X-ray scattering models for the full-length protein. These models are consistent with the enzyme forming a dimer through the middle domain. The protein has an approximate seesaw geometry where terminal enzyme units display high mobility owing to flexible linker segments. This resilient seesaw shape may facilitate internal substrate/product transfer or forwarding to other enzymes in the pathway.

Size, shape, and flexibility of proteins and DNA

Size, shape, and flexibility are the important topological parameters which characterize the functional specificity and different types of interactions in proteins and DNA. The size of proteins and DNA, often measured by the radius of gyration (R(G)), are determined from the coordinates of their respective structures available in Protein Data Bank and Nucleic Acid Data Bank. The mean square radius of gyration obeys Flory's scaling law given by R(G) (2) approximately N(2nu) where N is the number of amino acid residues/nucleotides. The scaling exponent nu reflects the different characteristic features of nonglobular proteins, natively unstructured proteins, and DNA. The asymmetry in the shapes of proteins and DNA are investigated using the asphericity (Delta) parameter and the shape parameter (S), calculated from the eigenvalues of the moment of inertia tensor. The distributions of Delta and S show that most nonglobular proteins and DNA are aspherical and prolate (S>0). Natively unstructured proteins are comparatively spherically symmetrical having both prolate and oblate shapes. The flexibility of these molecules is characterized by the persistence length (l(p)). Persistence length for natively unstructured proteins is determined by fitting the distance distribution function P(r) to the wormlike chain (WLC) model in the limit of r>>R(G). For nonglobular proteins and DNA, l(p) may be computed from the Benoit-Doty approximation for unperturbed radius of gyration of the WLC. The flexibilities of the proteins and DNA increases with the chain length. This is due to an increase in the nonlocal interactions with the increase in N, needed to minimize the conformational fluctuations in the native state. The persistence length of these proteins has not yet been measured directly. Analysis of the two-body contacts for the proteins reveals that the nonglobular proteins are less densely packed compared to the natively unstructured proteins with least side-chain side chain contacts even though side-chain backbone contacts predominate in the two types of proteins.