Predicting properties of intrinsically unstructured proteins

There is increasing evidence that intrinsically unstructured proteins or protein domains have important biological functions. These types of proteins may be productively analyzed using polymer theory developed to predict global physical properties of polymers. In these theories molecular detail is “coarse grained” out of the models, and replaced with a small number of parameters that characterize the polymer. This reduction in complexity allows extremely large systems to be studied. In the case of simulations, the time scales accessible also increase significantly. Here we discuss the application of polymer theory to unstructured proteins, and consider how to classify proteins within a polymer framework. We then review polymer theory that is relevant to predicting functionally important properties, such as radius of gyration, height of a polymer brush and force required to compress a polymer brush.     

Nanoconfined polymers: modelling and simulation approaches

In this article, application of molecular simulation methods for studying molecular pictures of nanoconfined polymers is reviewed and discussed. The simulation methods, covering a range from atomistic to systematically parameterised coarse-grained models, employed in the literature to study nanoconfined polymers are reviewed and their results are compared together. The effect of polymer–surface interactions, surface curvature and surface area on the alteration of polymer structure and dynamics from the unperturbed (bulk) polymer properties are discussed. The length scales over which the surface influences the polymer structure and dynamics and the magnitude of surface effect on dynamics deceleration in the interphase are addressed in terms of different local and global chain properties.     

Recent advances in maximum entropy biasing techniques for molecular dynamics

ABSTRACT

This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in molecular simulation by minimally modifying the thermodynamic ensemble. This is especially important where force fields are approximate, such as when employing coarse-grain models, or where high accuracy is required, such as when attempting to mimic a multiscale self-assembly process. The authors review here the experiment directed simulation (EDS) and experiment directed metadynamics (EDM) methods that allow matching averages and distributions in simulations, respectively. Important system-specific considerations are discussed such as using enhanced sampling simultaneously, the role of pressure, treating uncertainty, and implementations of these methods. Recent examples of EDS and EDM are reviewed including applications to ab initio molecular dynamics of water, incorporating environmental fluctuations inside of a macromolecular protein complex, improving RNA force fields, and the combination of enhanced sampling with minimal biasing to model peptides     

Advances in the mechanical modeling of filamentous actin and its cross-linked networks on multiple scales

The protein actin is a part of the cytoskeleton and, therefore, responsible for the mechanical properties of the cells. Starting with the single molecule up to the final structure, actin creates a hierarchical structure of several levels exhibiting a remarkable behavior. The hierarchy spans several length scales and limitations in computational power; therefore, there is a call for different mechanical modeling approaches for the different scales. On the molecular level, we may consider each atom in molecular dynamics simulations. Actin forms filaments by combining the molecules into a double helix. In a model, we replace molecular subdomains using coarse-graining methods, allowing the investigation of larger systems of several atoms. These models on the nanoscale inform continuum mechanical models of large filaments, which are based on worm-like chain models for polymers. Assemblies of actin filaments are connected with cross-linker proteins. Models with discrete filaments, so-called Mikado models, allow us to investigate the dependence of the properties of networks on the parameters of the constituents. Microstructurally motivated continuum models of the networks provide insights into larger systems containing cross-linked actin networks. Modeling of such systems helps to gain insight into the processes on such small scales. On the other hand, they call for verification and hence trigger the improvement of established experiments and the development of new methods.     

Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties.     

Extensiometric determination of the rheological properties of the epidermis of growing tomato fruit.

This paper examines the rheological properties of the fruit epidermis of tomato (Lycopersicon esculentum L.). This research was conducted because previous work had demonstrated that the rate of tomato fruit growth is determined by the interaction of tissue pressure and epidermal properties. A constant-load (or 'creep') extensiometer was employed in these experiments and the results interpreted using a model which describes creep retardation using a limited number of rheological elements, one of which appears analogous to plant growth and is of similar magnitude to fruit growth rate in vivo. The effects of pH, applied force and boiling upon the individual components of the model have been examined and indicate that several elements are strongly pH-dependent and that this dependency is eliminated by boiling. These results suggest that enzyme activity (plausibly that of one or more expansins) reduces the viscosity of the cell wall over a wide range of time scales. Further consideration of the creep of tomato epidermis in terms of models developed to describe the behaviour of artificial polymers suggests that the types of molecular event described by each rheological element can tentatively be identified and that pH-dependent enzyme activity facilitates both conformer rotation and macromolecular movement within the plant cell wall. These interpretations ascribe considerable importance to the time scale over which creep occurs.     

Structure prediction and network analysis of chitinases from the Cape sundew,Drosera capensis

BackgroundCarnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms.MethodsUsing comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology.ResultsHere, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparative and de novo structure prediction followed by molecular dynamics simulation to produce models of the mature forms of these proteins in aqueous solution. Protein structure network analysis of these and other plant chitinases reveal characteristic features of the two major chitinase families.General significanceThis work demonstrates how computational techniques can facilitate quickly moving from raw sequence data to refined structural models and comparative analysis, and to select promising candidates for subsequent biochemical characterization. This capability is increasingly important given the large and growing body of data from high-throughput genome sequencing, which makes experimental characterization of every target impractical.     

Bioinspired polymers that control intracellular drug delivery

One of the important characteristics of biological systems is their ability to change important properties in response to small environmental signals. The molecular mechanisms that biological molecules utilize to sense and respond provide interesting models for the development of “smart” polymeric biomaterials with biomimetic properties. An important example of this is the protein coat of viruses, which contains peptide units that facilitate the trafficking of the virus into the cell via endocytosis, then out of the endosome into the cytoplasm, and from there into the nucleus. We have designed a family of synthetic polymers whose compositions have been designed to mimic specific peptides on viral coats that facilitate endosomal escape. Our biomimetic polymers are responsive to the lowered pH within endosomes, leading to disruption of the endosomal membrane and release of important biomolecular drugs such as DNA, RNA, peptides and proteins to the cytoplasm before they are trafficked to lysosomes and degraded by lysosomal enzymes. In this article, we review our work on the design, synthesis and action of such smart, pH-sensitive polymers.     

Informatics for peptide retention properties in proteomic LC-MS

Retention times in HPLC yield valuable information for the identification of various analytes and the prediction of peptide retention is useful for the identification of peptides/proteins in LC-MS-based proteomics. Informatics methods such as artificial neural networks and support vector machines capable of solving nonlinear problems made possible the accurate modeling of quantitative structure-retention relationships of peptides (including large polymers) up to 5 kDa to which classical linear models cannot be applied, as well as the proteome-wide prediction of peptide retention. Proteome-wide retention prediction and accurate mass-information facilitate the identification of peptides in complex proteomic samples. In this review, we address recent developments in solid informatics methods and their application to peptide-retention properties in 'bottom-up' shotgun proteomics. We also describe future prospects for the standardization and application of retention times.     

Simulation of diffusion of O 2 and CO 2 in amorphous poly(ethylene terephthalate) and related alkylene and isomeric polyesters

The diffusion of small molecules through polymers is important in many areas of polymer science, such as gas barrier and separation membrane materials, polymeric foams, and in the processing and properties of polymers. Molecular simulation techniques have been applied to study the diffusion of oxygen and carbon dioxide as small molecule penetrants in models of bulk amorphous poly(ethylene terephthalate) (PET) and related alkylene and isomeric polyesters. A bulk amorphous configuration with periodic boundary conditions made into a unit cell whose dimensions were determined for each of the simulated polyesters in the cell having the experimental density. The diffusion coefficients for O 2 and CO 2 were determined via NVE molecular dynamics simulations using the Dreiding 2.21 molecular mechanics force field over a range of temperatures (300, 500 and 600 K) using up to 3 ns simulation time. We have focussed on the influence of the temperature, polymer dynamics, number of CH 2 groups, density and free volume distribution on the diffusion properties. Correlation of diffusion coefficients with free volume and number of CH 2 groups was found.     

Assessing and refining molecular dynamics simulations of proteins with nuclear magnetic resonance data

The sophistication of the force fields, algorithms and hardware used for molecular dynamics (MD) simulations of proteins is continuously increasing. No matter how advanced the methodology, however, it is essential to evaluate the appropriateness of the structures sampled in a simulation by comparison with quantitative experimental data. Solution nuclear magnetic resonance (NMR) data are particularly useful for checking the quality of protein simulations, as they provide both structural and dynamic information on a variety of temporal and spatial scales. Here, various features and implications of using NMR data to validate and bias MD simulations are outlined, including an overview of the different types of NMR data that report directly on structural properties and of relevant simulation techniques. The focus throughout is on how to properly account for conformational averaging, particularly within the context of the assumptions inherent in the relationships that link NMR data to structural properties.     

Mesoscale Modelling

Abstract

Increasingly, industrial materials are being designed to have structure on length scales of tens to thousands of nanometers. These structures are crucial to achieving a particular desired material property. Such structures, however, may depend on the underlying chemistry of the material for their existence. For example, a thousandfold increase in the ionic conductivity of a polymer blend may only occur in a narrow region of a hugely complex phase diagram, the location' of which region can be expected to depend on the molecular chemistry and physics from the monomer scale to the coil size.

Traditional Computational Chemistry has proved incapable of dealing with the length and time scales involved in the formation of these ‘Mesoscale’ structures. On the other hand, traditional Computational Physics has proved incapable of consistently incorporating the necessary chemical detail for modelling real industrial materials. In this paper we present two novel methods which successfully address both the chemistry and the physics of mesophase formation. The methods, described in detail, are MesoDyn and Dissipative Particle Dynamics (DPD).

Unlike phenomenological theories of materials, such as the Landau models which one finds in much of the computational physics literature, the two models mentioned incorporate molecular geometry and connectivity explicitly. We discuss each of the methods briefly.

We then give an overview of how these methods are being used in industry to optimise materials and processes. We discuss previous simulation results for triblock Pluronic surfactants in solution studied with MesoDyn, and for diblock copolymers studied with DPD, where the known experimental changes in morphology from micellar to hexagonal to bicontinuous to lamellar have been successfully reproduced. We also present new results for several systems, including binary and ternary blends, where the third component in the latter system is a diblock copolymer, which acts as a compatibiliser. We discuss the effects of changing solvent character on the material properties of these systems, as well as the effects of an externally imposed shear flow.     

Film forming microbial biopolymers for commercial applications—A review

Abstract

Microorganisms synthesize intracellular, structural and extracellular polymers also referred to as biopolymers for their function and survival. These biopolymers play specific roles as energy reserve materials, protective agents, aid in cell functioning, the establishment of symbiosis, osmotic adaptation and support the microbial genera to function, adapt, multiply and survive efficiently under changing environmental conditions. Viscosifying, gelling and film forming properties of these have been exploited for specific significant applications in food and allied industries. Intensive research activities and recent achievements in relevant and important research fields of global interest regarding film forming microbial biopolymers is the subject of this review. Microbial polymers such as pullulan, kefiran, bacterial cellulose (BC), gellan and levan are placed under the category of exopolysaccharides (EPS) and have several other functional properties including film formation, which can be used for various applications in food and allied industries. In addition to EPS, innumerable bacterial genera are found to synthesis carbon energy reserves in their cells known as polyhydroxyalkanoates (PHAs), microbial polyesters, which can be extruded into films with excellent moisture and oxygen barrier properties. Blow moldable biopolymers like PHA along with polylactic acid (PLA) synthesized chemically in vitro using lactic acid (LA), which is produced by LA bacteria through fermentation, are projected as biodegradable polymers of the future for packaging applications. Designing and creating of new property based on requirements through controlled synthesis can lead to improvement in properties of existing polysaccharides and create novel biopolymers of great commercial interest and value for wider applications. Incorporation of antimicrobials such as bacteriocins or silver and copper nanoparticles can enhance the functionality of polymer films especially in food packaging applications either in the form of coatings or wrappings. Use of EPS in combinations to obtain desired properties can be evaluated to increase the application range. Controlled release of active compounds, bioactive protection and resistance to water can be investigated while developing new technologies to improve the film properties of active packaging and coatings. An holistic approach may be adopted in developing an economical and biodegradable packaging material with acceptable properties. An interdisciplinary approach with new innovations can lead to the development of new composites of these biopolymers to enhance the application range. This current review focuses on linking and consolidation of recent research activities on the production and applications of film forming microbial polymers like EPS, PHA and PLA for commercial applications.     

Visualization of energetics and conformations from molecular computer simulations

The quantity of data generated from molecular dynamics simulations and energy minimizations of macromolecules is overwhelming. It is an arduous task to extract the relevant and interesting information from the numerous coordinate sets produced. To help solve this problem, the authors have developed a method to aid the visualization of the relevant information from the simulations. This approach combines animation of the results on a high performance graphics device, such as the PS300, with colour-coded atoms based on changes in energy or conformation. The method will be illustrated using as examples: the molecular mechanics minimization of a nonapeptide, the molecular dynamics simulation of the protein myoglobin, including the analysis of the motion of helices during a 300ps trajectory, and changes in sugar puckering that occur during the molecular dynamics simulation of a DNA oligomer. The method is also applicable for analysing energy components and conformational properties of a fixed conformation.     

Esculentosides: Insights into the potential health benefits,mechanisms of action and molecular targets

BackgroundEsculentosides and related phytolaccosides form a group of oleanene-type saponins isolated from plants of the Phytolaccaceae family, essentially Phytolacca esculenta, P. americana and P. acinosa. This chemical family offers a diversity of glycosylated compounds, including molecules with a mono-, di- or tri-saccharide unit at position C-3, and with or without a glucose residue at position C-28. The esculentosides, which derive essentially from the sapogenin jaligonic acid or its 30-methyl ester phytolaccagenin, exhibit anti-inflammatory, antifungal and anticancer activities.PurposeThe objective of the review was to identify the 26 esculentosides (ES) and phytolaccosides known to date, including 16 monodesmosidic and 10 bidesmosidic saponins, and to review their pharmacological properties and molecular targets.MethodologyThe retrieval of potentially relevant studies was done by systematically searching of scientific databases like Google Scholar and PubMed in January-May 2020. The main keywords used as search terms were related to esculentosides, phytolaccosides and Phytolaccaceae. The systematic search retrieved about 110 papers that were potentially relevant and after an abstract-based selection, 68 studies were analyzed in details and discussed.ResultsThe structural relationship between the compounds and their sapogenin precursors has been studied. In addition, the pharmacological properties of the main ES, such as ES-A, -B and -H, have been analyzed to highlight their mode of action and potential targets. ES-A is a potent inhibitor of the release of cytokines and this anti-inflammatory activity contributes to the anticancer effects observed in vitro and in vivo. Potential molecular targets of ES-A/B include the enzymes cyclooxygenase 2 (COX-2) and casein kinase 2 (CK2). In addition, the targeting of the protein high-mobility group box 1 (HGMB1) by ES-A/B is proposed, based on molecular modeling and the structural analogy with the related saponin glycyrrhizin, a potent HGMB1 alarmin inhibitor.ConclusionMore work is needed to properly characterize the molecular targets but otherwise compounds like ES-A and ES-H emerge as potent anti-inflammatory and anticancer agents and ES-B as an antifungal agent. A preclinical development of these three compounds should be considered.     

Molecular dynamics simulation of proteins under high pressure: Structure,function and thermodynamics

BackgroundMolecular dynamics (MD) simulation is well-recognized as a powerful tool to investigate protein structure, function, and thermodynamics. MD simulation is also used to investigate high pressure effects on proteins. For conducting better MD simulation under high pressure, the main issues to be addressed are: (i) protein force fields and water models were originally developed to reproduce experimental properties obtained at ambient pressure; and (ii) the timescale to observe the pressure effect is often much longer than that of conventional MD simulations.Scope of reviewFirst, we describe recent developments in MD simulation methodologies for studying the high-pressure structure and dynamics of protein molecules. These developments include force fields for proteins and water molecules, and enhanced simulation techniques. Then, we summarize recent studies of MD simulations of proteins in water under high pressure.Major conclusionsRecent MD simulations of proteins in solution under pressure have reproduced various phenomena identified by experiments using high pressure, such as hydration, water penetration, conformational change, helix stabilization, and molecular stiffening.General significanceMD simulations demonstrate differences in the properties of proteins and water molecules between ambient and high-pressure conditions. Comparing the results obtained by MD calculations with those obtained experimentally could reveal the mechanism by which biological molecular machines work well in collaboration with water molecules.     

Molecular simulation of polymers with a SAFT-γ Mie approach

ABSTRACT

We review the group contribution Statistical Associating Fluid Theory with Mie interaction potentials (SAFT-γ Mie) approach for building coarse-grained models for molecular simulation of polymeric systems. In this top-down method, force field parameters for coarse-grained polymer models can be derived from thermodynamic information on constituent monomer units using the SAFT-γ Mie equation of state (EoS). This strategy can facilitate high-throughput computational screening of polymeric materials, with a corresponding states correlation expediting the force field fitting. Accurate and transferable non-bonded parameters linked to macroscopic thermodynamic data allow for calculation of properties beyond those obtainable from the EoS alone. To overcome limitations of SAFT-γ Mie regarding polymer chain stiffness and branching, hybrid top-down/bottom-up approaches have combined non-bonded parameters from SAFT-γ Mie with bond-stretching and angle-bending potentials from higher-resolution force fields. Our review critically evaluates the performance of recent SAFT-γ Mie polymer models, highlighting the strengths and weaknesses in the context of other equation of state and coarse-graining methods.     

Molecular dynamics of water in the neighborhood of aquaporins

Present knowledge obtained by molecular dynamics (MD) simulation studies regarding the dynamics of water, both in the vicinity of biological membranes and within the proteinaceous water channels, also known as aquaporins (AQPs), is reviewed. A brief general summary of the water models most extensively employed in MD simulations (SPC, SPC/E, TIP3P, TIP4P), indicating their most relevant pros and cons, is likewise provided. Structural considerations of water are also discussed, based on different order parameters, which can be extracted from MD simulations as well as from experiments. Secondly, the behaviour of water in the neighbourhood of membranes by means of molecular dynamics simulations is addressed. Consequently, the comparison with previous experimental evidence is pointed out. In living cells, water is transported across the plasma membrane through the lipid bilayer and the aforementioned AQPs, which motivates this review to focus mostly on MD simulation studies of water within AQPs. Relevant contributions explaining peculiar properties of these channels are discussed, such as selectivity and gating. Water models used in these studies are also summarised. Finally, based on the information presented here, further MD studies are encouraged.     

Complex rheological properties of a water-soluble extract from the fronds of the black tree fern, Cyathea medullaris

A water-soluble extract was obtained from the fronds of a New Zealand native black tree fern (Cyathea medullaris or Mamaku in Māori). The extract exhibited complex rheological behavior. Newtonian, shear-thinning, shear-thickening, thixotropic, antithixotropic, and viscoelastic behaviors were observed depending on polymer concentration, shear rate, and shear history. The extract also displayed rod-climbing and self-siphoning properties typical of viscoelastic fluids. Such complex rheological properties have been reported in synthetic or chemically modified polymers but are less frequent in unmodified biopolymers. Although Mamaku extract obtained from the pith of the fern has been traditionally used by the Māori in New Zealand for treating wounds and diarrhea among other ailments, this material has never been characterized before. This study reports on the chemical composition of the extract and on its viscoelastic properties through rotational and oscillatory rheological measurements. Explanations of the mechanism behind the rheological properties were based on transient network models for associating polymers.