A comparative study of available software for high-accuracy homology modeling: from sequence alignments to structural models

An open question in protein homology modeling is, how well do current modeling packages satisfy the dual criteria of quality of results and practical ease of use? To address this question objectively, we examined homology‐built models of a variety of therapeutically relevant proteins. The sequence identities across these proteins range from 19% to 76%. A novel metric, the difference alignment index (DAI), is developed to aid in quantifying the quality of local sequence alignments. The DAI is also used to construct the relative sequence alignment (RSA), a new representation of global sequence alignment that facilitates comparison of sequence alignments from different methods. Comparisons of the sequence alignments in terms of the RSA and alignment methodologies are made to better understand the advantages and caveats of each method. All sequence alignments and corresponding 3D models are compared to their respective structure‐based alignments and crystal structures. A variety of protein modeling software was used. We find that at sequence identities >40%, all packages give similar (and satisfactory) results; at lower sequence identities (<25%), the sequence alignments generated by Profit and Prime, which incorporate structural information in their sequence alignment, stand out from the rest. Moreover, the model generated by Prime in this low sequence identity region is noted to be superior to the rest. Additionally, we note that DSModeler and MOE, which generate reasonable models for sequence identities >25%, are significantly more functional and easier to use when compared with the other structure‐building software.     

Scale Interactions and Regional Climate: Examples from the Susquehanna River Basin

One of the most difficult problems faced by climatologists is how to translate global climate model (GCM) output into regional- and local-scale information that health and environmental effects researchers can use. It will be decades before GCMs will be able to resolve scales small enough for most effects research, so climatologists have developed climate downscaling methods to bridge the gap between the global and local scales. There are two main streams of climate downscaling research. First, high-resolution, limited-area climate models can be embedded in the coarse-scale GCMs, producing much finer resolution climate data. Second, empirical downscaling techniques develop transfer functions linking the large-scale atmospheric circulation generated by the GCMs to surface data. Examples of both types of downscaling, aimed at improving projections of future climate in the Susquehanna River Basin (the Mid-Atlantic Region of the United States), are presented. A third case is also described in which an even higher-resolution nested atmospheric model is being developed and linked to a hydrologic model system, with the ultimate goal of simulating the environmental response to climate forcing at all time and space scales.     

Effect of dilution on sedimentational separation of bacteria from blood

Bacteria must be separated from septic whole blood in preparation for rapid antibiotic susceptibility tests. This work improves upon past work isolating bacteria from whole blood by exploring an important experimental factor: Whole blood dilution. Herein, we use the continuity equation to model red blood cell sedimentation and show that overall spinning time decreases as the blood is diluted. We found that the bacteria can also be captured more efficiently from diluted blood, up to approximately 68 ± 8% recovery (95% confidence interval). However, diluting blood both requires and creates extra fluid that end users must handle; an optimal dilution, which maximizes bacteria recovery and minimizes waste, was found to scale with the square root of the whole blood hematocrit. This work also explores a hypothesis that plasma backflow, which occurs as red cells move radially outward, causes bacterial enrichment in the supernatant plasma with an impact proportional to the plasma backflow velocity. Bacteria experiments carried out with diluted blood demonstrate such bacterial enrichment, but not in the hypothesized manner as enrichment occurred only in undiluted blood samples at physiological hematocrit.     

Insights from the molecular docking analysis of colistin with the PmrA protein model from Acinetobacter baumannii

Acinetobacter baumannii (AB) is one of the most common causes of nosocomial infections. Therefore, it is of interest to design and develop drugs against Acinetobacter baumannii. A strain of AB showing MIC 32 µg/ml against colistin was isolated from a hospital environment in Iran. Hence, we document data to glean insights from the molecular docking analysis of colistin with the PmrA protein from this bacterium.     

Modeling pilus structures from sparse data

Bacterial Type II secretion systems (T2SS) and type IV pili (T4P) biogenesis machineries share the ability to assemble thin filaments from pilin protein subunits in the plasma membrane. Here we describe in detail the calculation strategy that served to determine a detailed atomic model of the T2SS pilus from Klebsiella oxytoca (Campos et al., PNAS 2010). The strategy is based on molecular modeling with generalized distance restraints and experimental validation (salt bridge charge inversion; double cysteine substitution and crosslinking). It does not require directly fitting structures into an envelope obtained from electron microscopy, but relies on lower resolution information, in particular the symmetry parameters of the helix forming the pilus. We validate the strategy with T4P where either a higher resolution structure is available (for the gonococcal (GC) pilus from Neisseria gonorrhoeae), or where we can compare our results to additional experimental data (for Vibrio cholerae TCP). The models are of sufficient precision to compare the architecture of the different pili in detail.     

Xylanase from the psychrophilic yeast Cryptococcus adeliae

A xylanase belonging to family 10 is produced by Cryptococcus adeliae, an Antarctic yeast that exhibits optimal growth at low temperature. The mature glycosylated xylanase secreted by C. adeliae is composed of 338 amino acid residues and 26 ± 3 osidic residues, and shares 84% identity with its mesophilic counterpart from C. albidus. The xylanase from C. adeliae is less thermostable than its mesophilic homologue when the residual activities are compared, and this difference was confirmed by differential scanning calorimetry experiments. In the range 0°–20°C, the cold-adapted xylanase displays a lower activation energy and a higher catalytic efficiency. All these observations suggest a less compact, more flexible molecular structure. Analysis of computerized molecular models built up for both psychrophilic and mesophilic xylanases indicates that the adaptation to cold consists of discrete changes in the tridimensional structure: of 53 substitutions, 22 are presumably involved in the adaptation process. These changes lead mainly to a less compact hydrophobic packing, to the loss of one salt bridge, and to a destabilization of the macrodipoles of the helices. Received: April 20, 1999 / Accepted: January 13, 2000     

Prediction of enteric methane emissions from cattle

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.     

Modeling of protein refolding from inclusion bodies

Overexpression of foreign proteins in Escherichia coli often leads to the formation of inclusion bodies （IBs）, which becomes the major bottleneck in the preparation of recombinant proteins and their applications. In the present study, 36 proteins from IBs were refolded using a simple refolding method. Refolding yields of these proteins were defined as the percentage of soluble pro- teins following dilution refoiding in the amount of denatured proteins in the samples before diluting into refolding buffer. Furthermore, a mathematical model was deduced to evaluate the role of biochemical proper- ties in the protein refolding. Our results indicated that under the experimental conditions, isoelectric point of proteins might be mostly contributing to the high effi- cacy of protein refolding since the increment of one unit resulted in a decrease of 14.83% in the refolding yield. Other important mediators were components of protein secondary structure and the molecular weight （R2= 0.98, P = 0.000, F-test）. Six proteins with low efficiency in the protein refolding possessed relatively low isoelectric points. Furthermore, refolding yields of six additional proteins from IBs were predicted and further validated by refolding the proteins under the same conditions. Therefore, the model of protein refold- ing developed here could be used to predict the refold- ing yields of proteins from IBs through a simple method. Our study will be suggestive to optimize the methods for protein refoiding from IBs according to their intrinsic properties.     

Circadian clock effects on cellular proliferation: Insights from theory and experiments

Oscillations of the cellular circadian clock have emerged as an important regulator of many physiological processes, both in health and in disease. One such process, cellular proliferation, is being increasingly recognized to be affected by the circadian clock. Here, we review how a combination of experimental and theoretical work has furthered our understanding of the way circadian clocks couple to the cell cycle and play a role in tissue homeostasis and cancer. Finally, we discuss recently introduced methods for modeling coupling of clocks based on techniques from survival analysis and machine learning and highlight their potential importance for future studies.     

Binding isotherms for soluble immobilized affinity ligands from spectral titration

The method of spectral titration has been applied to binding equilibria between proteins and soluble immobilized ligands and evaluated using the interaction between Cibacron blue-dextran conjugates and lysozyme. The method is both simple and rapid and provides a convenient screening technique for characterization of soluble adsorbents designed for use in aqueous two-phase affinity extraction or as liquid-phase models for affinity chromatography systems. The results indicate that regardless of ligand density a constant 28% of the total coupled dye is available for high-affinity protein binding at saturation. The dissociation constant for the dye-protein interaction, however, decreases with dye loading. The potential for kinetic investigations has been demonstrated using a stopped-flow apparatus. The results indicate that a simple rate equation is inadequate to describe the data for lysozyme binding to dye-dextran conjugates. A modified model, which better describes the data, was developed by including a second rate limiting process, the transition from stacked to unstacked dye ligands on the dextran backbone. This effect could have practical significance for protein binding kinetics in affinity chromatography, especially in high-performance liquid affinity chromatography applications where mass transfer is rapid. (c) 1992 John Wiley & Sons, Inc.     

The generation of curved clathrin coats from flat plaques

Flat clathrin lattices or 'plaques' are commonly believed to be the precursors to clathrin-coated buds and vesicles. The sequence of steps carrying the flat hexagonal lattice into a highly curved polyhedral cage with exactly 12 pentagons remains elusive, however, and the large numbers of disrupted interclathrin connections in previously proposed conversion pathways make these scenarios rather unlikely. The recent notion that clathrin can make controlled small conformational transitions opens new avenues. Simulations with a self-assembling clathrin model suggest that localized conformational changes in a plaque can create sufficiently strong stresses for a dome-like fragment to break apart. The released fragment, which is strongly curved but still hexagonal, may subsequently grow into a cage by recruiting free triskelia from the cytoplasm, thus building all 12 pentagonal faces without recourse to complex topological changes. The critical assembly concentration in a slightly acidic in vitro solution is used to estimate the binding energy of a cage at 25-40 k(B) T/clathrin.     

Structural studies of shikimate 5-dehydrogenase from Mycobacterium tuberculosis

Tuberculosis (TB) remains the leading cause of mortality due to a single bacterial pathogen, Mycobacterium tuberculosis. The reemergence of TB as a potential public health threat, the high susceptibility of human immunodeficiency virus-infected persons to the disease, the proliferation of multi-drug-resistant strains (MDR-TB) and, more recently, of extensively drug resistant isolates (XDR-TB) have created a need for the development of new antimycobacterial agents. Amongst the several proteins and/or enzymes to be studied as potential targets to develop novel drugs against M. tuberculosis, the enzymes of the shikimate pathway are attractive targets because they are essential in algae, higher plants, bacteria, and fungi, but absent from mammals. The mycobacterial shikimate pathway leads to the biosynthesis of chorismate, which is a precursor of aromatic amino acids, naphthoquinones, menaquinones, and mycobactins. Here we report the structural studies by homology modeling and circular dichroism spectroscopy of the shikimate dehydrogenase from M. tuberculosis (MtSDH), which catalyses the fourth step of the shikimate pathway. Our structural models show that the MtSDH has similar structure to other shikimate dehydrogenase structures previously reported either in presence or absence of NADP, despite the low amino acid sequence identity. The circular dichroism spectra corroborate the secondary structure content observed in the MtSDH models developed. The enzyme was stable up to 50 degrees C presenting a cooperative unfolding profile with the midpoint of the unfolding temperature value of approximately 63-64 degrees C, as observed in the unfolding experiment followed by circular dichroism. Our MtSDH structural models and circular dichroism data showed small conformational changes induced by NADP binding. We hope that the data presented here will assist the rational design of antitubercular agents.     

Homology modeling of an antifungal metabolite plipastatin synthase from the Bacillus subtilis 168

Lipopeptides have a widespread role in different pathways of Bacillus subtilis; they can act as antagonists, spreader and immunostimulators. Plipastatin, an antifungal antibiotic, is one of the most important lipopeptide nonribosomly produced by Bacillus subtilis. Plipastatin has strong fungitoxic activity and involve in inhibition of phospholipase A2 and biofilm formation. For better understanding of the molecule and pathway by which lipopeptide plipastatin is synthesized, we present a computationally predicted structure of plipastatin using homology modeling. Primary and secondary structure analysis suggested that ppsD is a hydrophilic protein containing a significant proportion of alpha helices, and subcellular localization predictions suggested it is a cytoplasmic protein. The tertiary structure of protein (plipastatin synthase subunit D) was predicted by homology modeling. The results suggest a flexible structure which is also an important characteristic of active enzymes enabling them to bind various cofactors and substrates for proper functioning. Validation of 3D structure was done using Ramachandran plot ProsA-web and QMEAN score.This predicted information will help in better understanding of mechanisms underlying plipastatin synthase subunit D synthesis. Plipastatin can be used as an inhibitor of various fungal diseases in plants.     

Biofuel production from microalgae as feedstock: current status and potential

Algal biofuel has become an attractive alternative of petroleum-based fuels in the past decade. Microalgae have been proposed as a feedstock to produce biodiesel, since they are capable of mitigating CO₂ emission and accumulating lipids with high productivity. This article is an overview of the updated status of biofuels, especially biodiesel production from microalgae including fundamental research, culture selection and engineering process development; it summarizes research on mathematical and life cycle modeling on algae growth and biomass production; and it updates global efforts of research and development and commercialization attempts. The major challenges are also discussed.     

Bio-oil from photosynthetic microalgae: Case study

Microalgae possess the potential to produce bio-oils, carbohydrates, protein, amino acids and other value added products, each of which increase its value as a crop. Unfortunately, proven systems do not yet exist for commercial scale production. System designs have generally not adequately accounted for water and energy use at scale, as well as byproduct markets, and thus yielded systems that are both unaffordable and unsustainable. We address energy and water use by presenting a straightforward microalga-to-bio-oil production process and then characterize system performance using steady-state water and energy balances. Practical limitations to commercial production of bio-oils from photosynthetic microalgae are proposed and conclusions drawn regarding system potential for assumed biomass productivities. As this is a theoretical analysis of a generic process and in practice many of the bottlenecks presented remain to be solved, it is our intent that the analysis framework presented herein can be applied to future systems that propose such solutions.     

Glucose transport from mother to fetus—A theoretical study

The factors that affect and govern the glucose transfer from maternal blood to the fetus are not completely deciphered. We present a steady state, one dimensional mathematical simulation which integrates the main mechanisms that have been shown to exist: metabolic consumption of the placenta, simple and facilitated diffusion via the two membranes of the microvillous and simple diffusion within the placenta. The model uses all available physiologic data we could collect. Numerical results indicate that the most crucial factor in determining the fetal glucose concentration is the facilitated diffusion process at the basal membrane or, more specifically: the permeability of the basal membrane and the density of the transporter GLUT1 on its faces. The gradient between the maternal and the fetal glucose concentration is important as is the metabolic consumption of the placenta. The diffusion within the placenta and the conditions that prevail at the apical microvillous plasma membrane are much less significant. Intrasyncytial concentration of glucose is close to that of maternal blood. The adjustment of the fetal glucose concentration to abrupt changes of its surrounding is estimated to be quite rapid hence for all practical purposes this steady state model can serve as a reasonable approximation. Parameters that await experimental determination are identified.     

Systematic interpolation method predicts protein chromatographic elution from batch isotherm data without a detailed mechanistic isotherm model

Predicting protein elution for overloaded ion exchange columns requires models capable of describing protein binding over broad ranges of protein and salt concentrations. Although approximate mechanistic models are available, they do not always have the accuracy needed for precise predictions. The aim of this work is to develop a method to predict protein chromatographic behavior from batch isotherm data without relying on a mechanistic model. The method uses a systematic empirical interpolation (EI) scheme coupled with a lumped kinetic model with rate parameters determined from HETP measurements for non‐binding conditions, to numerically predict the column behavior. For two experimental systems considered in this work, predictions based on the EI scheme are in excellent agreement with experimental elution profiles under highly overloaded conditions without using any adjustable parameters. A qualitative study of the sensitivity of predicting protein elution profiles to the precision, granularity, and extent of the batch adsorption data shows that the EI scheme is relatively insensitive to the properties of the dataset used, requiring only that the experimental ranges of protein and salt concentrations overlap those under which the protein actually elutes from the column and possess a ±10% measurement precision.     

Solute exclusion from cellulose in packed columns: process modeling and analysis

In this investigation, process modeling and analysis were used to explore the behavior of solute exclusion from cellulose in packed columns. The study focused on modeling the effects of dispersion, mass transport, and pore diffusion. Three mathematical models were used to predict the behavior of the columns: an equilibrium model, a mass transfer model, and a combined mass transfer and pore diffusion model. Computer implementations of these models were tested against experimental conditions where cellulose particle size and solution velocity were used to either amplify or minimize dispersion or skewness in the elution curves. For small cellulose particles (200-300 mesh), all three models accurately predicted the shape of the elution curve and the particle porosity. For larger particles (45-60 mesh), the mass transfer model and the combined mass and pore diffusion model best represented the behavior of the column. At high solution velocities (0.63 cm(3) min(-1)) and large particles, only the combined mass transfer and pore diffusion model accurately represent the column behavior. Sensitivity analysis revealed that the mass transfer coefficient had little effect on the elution curves for the range of values (10(-6)-10(-3) cm s(-1)) calculated from the experimental data. The combined mass transfer and pore diffusion model presented in this article can be used to design solute exclusion measurement experiments for the larger cellulose particles found in a commercial cellulose-to-ethanol plant.