Topological "Shape" in Micellar Dynamics.

For micelles, "shape" is prominent in rheological computations of fluid flow, but this "shape" is often expressed too informally to be useful for rigorous analyses. We formalize topological "shape equivalence" of micelles, both globally and locally, to enable visualization of computational fluid dynamics. Although topological methods in visualization provide significant insights into fluid flows, this opportunity has been limited by the known difficulties in creating representative geometry. We present an agile geometric algorithm to represent the micellar shape for input into fluid flow visualizations. We show that worm-like and cylindrical micelles have formally equivalent shapes, but that visualization accentuates unexplored differences. This global-local paradigm is extensible beyond micelles.

Protocols to Dissolve Amorphous Urate Crystals in Urine.

OBJECTIVE: Amorphous urate crystals can obscure significant findings during a routine urinalysis. There is no standardized protocol to minimize their effect. MATERIALS AND METHODS: We tested 210 urine specimens. Three specimens had high red blood cell (RBC) or white blood cell (WBC) counts. Fifty-six specimens formed amorphous urates. Sediment from these specimens was treated with 50 mM sodium hydroxide (NaOH) at a 1:2 and/or 1:4 dilution. We warmed 22 specimens with crystals at various temperatures. RESULTS: Amorphous urate crystals formed in concentrated urine with an acidic pH. Adding 50 mM NaOH dissolved amorphous urates, revealing the presence of underlying bacteria and yeast, but WBC and RBC counts were grossly decreased. Prewarming unspun specimens to 60°C for 90 seconds dissolved most amorphous urates. CONCLUSION: The protocol to eliminate amorphous urate crystals is to prewarm the specimen before testing. Adding 50 mM NaOH to sediment dissolves amorphous urates to enhance the visibility of bacteria and yeast but has a deleterious effect on WBC and RBC.

The Role of Chemical Heterogeneity in Surfactant Adsorption at Solid-Liquid Interfaces.

Chemical heterogeneity of solid surfaces disrupts the adsorption of surfactants from the bulk liquid. While its presence can hinder the performance of some formulations, bespoke chemical patterning could potentially facilitate controlled adsorption for nanolithography applications. Although some computational studies have investigated the impact of regularly patterned surfaces on surfactant adsorption, in reality, many interesting surfaces are expected to be stochastically disordered and this is an area unexplored via simulations. In this paper, we describe a new algorithm for the generation of randomly disordered chemically heterogeneous surfaces and use it to explore the adsorption behavior of four model nonionic surfactants. Using novel analysis methods, we interrogate both the global surface coverage (adsorption isotherm) and behavior in localized regions. We observe that trends in adsorption characteristics as surfactant size, head/tail ratio, and surface topology are varied and connect these to underlying physical mechanisms. We believe that our methods and approach will prove useful to researchers seeking to tailor surface patterns to calibrate nonionic surfactant adsorption.

Model for the Simulation of the CnEm Nonionic Surfactant Family Derived from Recent Experimental Results.

Using a comprehensive set of recently published experimental results for training and validation, we have developed computational models appropriate for simulations of aqueous solutions of poly(ethylene oxide) alkyl ethers, an important class of micelle-forming nonionic surfactants, usually denoted CnEm. These models are suitable for use in simulations that employ a moderate amount of coarse graining and especially for dissipative particle dynamics (DPD), which we adopt in this work. The experimental data used for training and validation were reported earlier and produced in our laboratory using dynamic light scattering (DLS) measurements performed on 12 members of the CnEm compound family yielding micelle size distribution functions and mass-weighted mean aggregation numbers at each of several surfactant concentrations. The range of compounds and quality of the experimental results were designed to support the development of computational models. An essential feature of this work is that all simulation results were analyzed in a way that is consistent with the experimental data. Proper account is taken of the fact that a broad distribution of micelle sizes exists, so mass-weighted averages (rather than number-weighted averages) over this distribution are required for the proper comparison of simulation and experimental results. The resulting DPD force field reproduces several important trends seen in the experimental critical micelle concentrations and mass-averaged mean aggregation numbers with respect to surfactant characteristics and concentration. We feel it can be used to investigate a number of open questions regarding micelle sizes and shapes and their dependence on surfactant concentration for this important class of nonionic surfactants.

Efficient Algorithm for the Topological Characterization of Worm-like and Branched Micelle Structures from Simulations.

Many surfactant-based formulations are utilized in industry as they produce desirable viscoelastic properties at low concentrations. These properties are due to the presence of worm-like micelles (WLMs), and as a result, understanding the processes that lead to WLM formation is of significant interest. Various experimental techniques have been applied with some success to this problem but can encounter issues probing key microscopic characteristics or the specific regimes of interest. The complementary use of computer simulations could provide an alternate route to accessing their structural and dynamic behavior. However, few computational methods exist for measuring key characteristics of WLMs formed in particle simulations. Further, their mathematical formulations are challenged by WLMs with sharp curvature profiles or density fluctuations along the backbone. Here, we present a new topological algorithm for identifying and characterizing WLMs in particle simulations, which has desirable mathematical properties that address shortcomings in previous techniques. We apply the algorithm to the case of sodium dodecyl sulfate micelles to demonstrate how it can be used to construct a comprehensive topological characterization of the observed structures.

Challenge to Reconcile Experimental Micellar Properties of the CnEm Nonionic Surfactant Family.

We wished to compile a data set of results from the experimental literature to support the development and validation of accurate computational models (force fields) for an important class of micelle-forming nonionic surfactant compounds, the poly(ethylene oxide) alkyl ethers, usually denoted C nE m. However, careful examination of the experimental literature exposed a striking degree of variation in values reported for critical micelle concentrations (cmc) and mean aggregation numbers ( Nagg). This variation was so large that it masked important trends known to exist within this family of molecules, thereby rendering most of the literature data to be of limited utility for force field development. In this work, we describe some reasons for the wide variability in the experimental literature, and we present a set of cmc and aggregation number data for 12 C nE m compounds that we feel is appropriate to use for the construction of and validation of computational models. The cmc values we selected are from the existing experimental literature and represent a carefully chosen and consistent subset that conveys important trends seen by many of the experimental studies. However, for a corresponding and consistent set of weight-averaged aggregation numbers, we needed to perform new dynamic light scattering (DLS) experiments. The results of these experiments were carefully analyzed to obtain not just mean aggregation numbers but also the underlying micelle size distribution functions. Several trends observed in the cmc and Nagg observables are highlighted and serve as challenges for developers of force field and simulation methodology. The analysis of the DLS experiments accounts for the fact that a broad distribution of micelle sizes exists for many of these compounds and that one must be careful to use the appropriate weighted averages (e.g., mass-weighted vs number-weighted averages) in comparing results from different types of experiments and in comparing results from experiments with those from simulations.

Toward a Standard Protocol for Micelle Simulation.

In this paper, we present protocols for simulating micelles using dissipative particle dynamics (and in principle molecular dynamics) that we expect to be appropriate for computing micelle properties for a wide range of surfactant molecules. The protocols address challenges in equilibrating and sampling, specifically when kinetics can be very different with changes in surfactant concentration, and with minor changes in molecular size and structure, even using the same force field parameters. We demonstrate that detection of equilibrium can be automated and is robust, for the molecules in this study and others we have considered. In order to quantify the degree of sampling obtained during simulations, metrics to assess the degree of molecular exchange among micellar material are presented, and the use of correlation times are prescribed to assess sampling and for statistical uncertainty estimates on the relevant simulation observables. We show that the computational challenges facing the measurement of the critical micelle concentration (CMC) are somewhat different for high and low CMC materials. While a specific choice is not recommended here, we demonstrate that various methods give values that are consistent in terms of trends, even if not numerically equivalent.

Does race alter the relationship between Hba1c and glucose in type 2 diabetes?

OBJECTIVE: Hemoglobin Alc (HbAlc) is the standard measurement of glycemic control, and the HbAlc value can be used to estimate average glucose using a formula. Several studies suggest that the relationship between average glucose and HbAlc may be different for Blacks. This project enrolled non-Hispanic black and white individuals with type 2 diabetes and evaluated the relationship between HbAlc and blood glucose. METHOD: 22 black and 29 white adults with type 2 diabetes were included in the analysis. Approximately 42 measurements (fasting and postprandial glucose) were collected over three months and compared to HbAl1 of the third month. The effect of race was evaluated by ANCOVA and X2 analysis testing the slope and intercepts simultaneously for HbA1c and its relationship to fasting glucose and to postprandial glucose. RESULTS: The relationship between HbAlc and glucose was not statistically significantly different between Blacks and Whites (ANCOVA: P = 0.968 for fasting glucose, P = 0.428 for postprandial glucose), allowing us to calculate estimated fasting and postprandial glucose disregarding race. For fasting glucose, the linear regression is FGmgiadl = (18.939 X HbAlc%) - 1.864, R2 = 0.586, P < 0.0001. For postprandial glucose, the linear regression is In(PPG mg,dl) (1.261 X In(HbA1c%)) + 2.555, R2 = 0.614, P < 0.0001. Predicted values for postprandial glucose based on HbA1c were similar to estimated average glucose values reported by ADAG. CONCLUSION: This study reinforces the A1c-Derived Average Glucose (ADAG) group finding that the relationship between HbA1c and glucose is similar in non-Hispanic black and white adults with type 2 diabetes.

Toward fast determination of protein stability maps: experimental and theoretical analysis of mutants of a Nocardiopsis prasina serine protease.

The stability of serine proteases is of major importance for their application in industrial processes. Here we study the determinants of the stability of a Nocardiopsis prasina serine protease using fast residual activity assays, a feature classification algorithm, and structure-based energy calculation algorithms for 121 micropurified mutant enzyme clones containing multiple point mutations. Using a multivariate regression analysis, we deconvolute the data for the mutant clones and find that mutations of residues Asn47 and Pro124 are deleterious to the stability of the enzyme. Both of these residues are situated in loops that are known to be important for the stability of the highly homologous α-lytic protease. Structure-based energy calculations with PEATSA give a good general agreement with the trend of experimentally measured values but also identify a number of clones that the algorithm fails to predict correctly. We discuss the significance of the results in relation to the structure and function of closely related proteases, comment on the optimal experimental design when performing high-throughput experiments for characterizing the determinants of protein stability, and discuss the performance of structure-based energy calculations with complex data sets such as the one presented here.

A collaborative environment for developing and validating predictive tools for protein biophysical characteristics.

The exchange of information between experimentalists and theoreticians is crucial to improving the predictive ability of theoretical methods and hence our understanding of the related biology. However many barriers exist which prevent the flow of information between the two disciplines. Enabling effective collaboration requires that experimentalists can easily apply computational tools to their data, share their data with theoreticians, and that both the experimental data and computational results are accessible to the wider community. We present a prototype collaborative environment for developing and validating predictive tools for protein biophysical characteristics. The environment is built on two central components; a new python-based integration module which allows theoreticians to provide and manage remote access to their programs; and PEATDB, a program for storing and sharing experimental data from protein biophysical characterisation studies. We demonstrate our approach by integrating PEATSA, a web-based service for predicting changes in protein biophysical characteristics, into PEATDB. Furthermore, we illustrate how the resulting environment aids method development using the Potapov dataset of experimentally measured ΔΔGfold values, previously employed to validate and train protein stability prediction algorithms.

Integrated prediction of the effect of mutations on multiple protein characteristics.

Site-directed mutagenesis is routinely used in modern biology to elucidate the functional or biophysical roles of protein residues, and plays an important role in the field of rational protein design. Over the past decade, a number of computational tools have been developed that can predict the effect of point mutations on a protein's biophysical characteristics. However, these programs usually provide predictions for only a single characteristic. Furthermore, online versions of these tools are often impractical to use for examination of large and diverse sets of mutants. We have created a new web application, (http://enzyme.ucd.ie/PEAT_SA), that can simultaneously predict the effect of mutations on stability, ligand affinity and pK(a) values. PEAT-SA also provides an expanded feature-set with respect to other online tools which includes the ability to obtain predictions for multiple mutants in one submission. As a result, researchers who use site-directed mutagenesis can access state-of-the-art protein design methods with a fraction of the effort previously required. The results of benchmarking PEAT-SA on standard test-sets demonstrate that its accuracy for all three prediction types compares well to currently available tools. We illustrate PEAT-SA's potential by using it to investigate the influence of mutations on the activity of Subtilisin BPN'. This example demonstrates how the ability to obtain a wide range of information from one source, that can be combined to obtain deeper insight into the influence of mutations, makes PEAT-SA a valuable service to both experimental and computational biologists.

Microbial antagonists of Escherichia coli O157:H7 on fresh-cut lettuce and spinach.

Fresh-cut lettuce and spinach can become contaminated with pathogens at numerous points from the field to the retail market. Natural microflora present on fresh produce may help reduce the pathogen load. The objective of this study was to isolate natural microflora from fresh-cut iceberg lettuce and baby spinach and to determine whether these bacteria were antagonistic toward Escherichia coli O157:H7. Samples were collected under conditions that mimicked actual practices between production and retail sale. Evidence of naturally occurring microorganisms on fresh lettuce (295 isolates) and spinach (200 isolates) and of possible antagonistic activity toward E. coli O157:H7 was documented. Inhibitory activity by several isolates was due to either acid production or antimicrobial peptides. Bacteria with inhibitory activity were isolated from every step in the processing and handling of the fresh-cut iceberg lettuce and baby spinach.

The role of residue stability in transient protein-protein interactions involved in enzymatic phosphate hydrolysis. A computational study.

Finding why protein-protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so-called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S-LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate "hot spots" for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper "energetic" orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above-mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient PPIs.

Framework-based design of a new all-purpose molecular simulation application: the Adun simulator.

Here we present Adun, a new molecular simulator that represents a paradigm shift in the way scientific programs are developed. The traditional algorithm centric methods of scientific programming can lead to major maintainability and productivity problems when developing large complex programs. These problems have long been recognized by computer scientists; however, the ideas and techniques developed to deal with them have not achieved widespread adoption in the scientific community. Adun is the result of the application of these ideas, including pervasive polymorphism, evolutionary frameworks, and refactoring, to the molecular simulation domain. The simulator itself is underpinned by the Adun Framework, which separates the structure of the program from any underlying algorithms, thus giving a completely reusable design. The aims are twofold. The first is to provide a platform for rapid development and implementation of different simulation types and algorithms. The second is to decrease the learning barrier for new developers by providing a rigorous and well-defined structure. We present some examples on the use of Adun by performing simple free-energy simulations for the adiabatic charging of a single ion, using both free-energy perturbation and the Bennett's method. We also illustrate the power of the design by detailing the ease with which ASEP/MD, an elaborated mean field QM/MM method originally written in FORTRAN 90, was implemented into Adun.