One-pot preparation of quercetin using natural deep eutectic solvents

In this study, we have established a green and efficient preparation method of quercetin. Rutin was first extracted from Sophora japonica using natural deep eutectic solvents (NADESs), then hydrolyzed into quercetin by rutin degrading enzyme (RDE) obtained from germinated tartary buckwheat in situ. Rutin solubility tests showed that most of the 11 NADESs increased the solubility of rutin by 67-3116 times compared to water. Thus, NADESs could be prior candidate to extract rutin. Extraction efficiency of rutin varied with different NADESs, and a maximum of 291.57 mg g⁻¹ was achieved in NADES ChGly, which was prepared by mixing choline chloride and glycerol at a molar ratio of 1:1. After that hydrolysis was performed directly in extraction system by adding RDE with degradation rate of up to 8.36 mg min^-1·L^-1. Our findings suggest that preparation of quercetin using NADESs was simple and feasible to operate, environmentally friendly, efficient, and inspired the preparation method of bioactive components from a new perspective.     

Choline-based deep eutectic solvents for enzymatic preparation of biodiesel from soybean oil

In this study, we introduced choline-based deep eutectic solvents (such as choline chloride/glycerol at 1:2 molar ratio) as inexpensive, non-toxic, biodegradable and lipase-compatible solvents for the enzymatic preparation of biodiesel from soybean oil. Through the evaluation of different eutectic solvents and different lipases, as well as the study of reaction parameters (i.e. methanol concentration, Novozym 435 loading and reaction time), we were able to achieve up to 88% triglyceride conversions in 24 h. The enzyme could be reused for at least four times without losing much activity. Our results indicate that new benign eutectic solvents can be used as substitutes of toxic and volatile organic solvents in the enzymatic production of biodiesel from real triglycerides (such as soybean oil).     

Application of a PEG precipitation method for solubility screening: A tool for developing high protein concentration formulations

Previous publications demonstrated that the extrapolated solubility by polyethylene glycol (PEG) precipitation method (Middaugh et al., J Biol Chem 1979; 254:367–370; Juckes, Biochim Biophys Acta 1971; 229:535–546; Foster et al., Biochim Biophys Acta 1973; 317:505; Mahadevan and Hall, AIChE J 1990; 36:1517–1528; Stevenson and Hageman, Pharm Res 1995; 12:1671–1676) has a strong correlation to experimentally measured solubility of proteins. Here, we explored the utility of extrapolated solubility as a method to compare multiple protein drug candidates when nonideality of a highly soluble protein prohibits accurate quantitative solubility prediction. To achieve high efficiency and reduce the amount of protein required, the method is miniaturized to microwell plate format for high‐throughput screening application. In this simplified version of the method, comparative solubility of proteins can be obtained without the need of concentration measurement of the supernatant following the precipitation step in the conventional method. The monoclonal antibodies with the lowest apparent solubilities determined by this method are the most difficult to be concentrated, indicating a good correlation between the prediction and empirical observations. This study also shows that the PEG precipitation method gives results for opalescence prediction that favorably compares to experimentally determined opalescence levels at high concentration. This approach may be useful in detecting proteins with potential solubility and opalescence problems prior to the time‐consuming and expensive development process of high concentration formulation.     

Evaluation of deep eutectic solvents as new media for Candida antarctica B lipase catalyzed reactions

This study aimed at analyzing the advantages and limitations of several deep eutectic solvents (DESs) as ‘green solvents’ for biotransformation using immobilized Candida antarctica lipase B as catalyst. The transesterification of vinyl laurate was chosen as model reaction and the influence of substrate polarity was assessed using alcohols of various chain lengths. Results showed that grinding of immobilized lipase was essential parameters for good lipase activity. Moreover, in our model reaction some hydrogen-bond donor component from the DES can compete with the alcoholysis reaction. Indeed, side reactions were observed with DES based on dicarboxylic acid or ethylene glycol, leading to some limitations of their use. However, the results showed that other DESs such as choline chloride:urea and choline chloride:glycerol could exhibit high activity and selectivity making them promising solvents for lipase-catalyzed reactions. Finally, the best DES's specific activity – and stability up to five days incubation time – were analyzed and compared with conventional organic solvents. Experiments revealed that iCALB is less influenced by the chain length of alcohol in DES than organic solvents and it is preserves its activity with minimally destructive to protein structure.     

A computational approach to the functional screening of genomes

Comparative genomics usually involves managing the functional aspects of genomes, by simply comparing gene-by-gene functions. Following this approach, Mushegian and Koonin proposed a hypothetical minimal genome, Minimal Gene Set (MGS), aiming for a possible oldest ancestor genome. They obtained MGS by comparing the genomes of two simple bacteria and eliminating duplicated or functionally identical genes. The authors raised the fundamental question of whether a hypothetical organism possessing MGS is able to live or not. We attacked this viability problem specifying in silico the metabolic pathways of the MGS-based prokaryote. We then performed a dynamic simulation of cellular metabolic activities in order to check whether the MGS-prokaryote reaches some equilibrium state and produces the necessary biomass. We assumed these two conditions to be necessary for a living organism. Our simulations clearly show that the MGS does not express an organism that is able to live. We then iteratively proceeded with functional replacements in order to obtain a genome composition that gives rise to equilibrium. We ruled out 76 of the original 254 genes in the MGS, because they resulted in duplication from a functional point of view. We also added seven genes not present in the MGS. These genes encode for enzymes involved in critical nodes of the metabolic network. These modifications led to a genome composed of 187 elements expressing a virtually living organism, Virtual Cell (ViCe), that exhibits homeostatic capabilities and produces biomass. Moreover, the steady-state distribution of the concentrations of virtual metabolites that resulted was similar to that experimentally measured in bacteria. We conclude then that ViCe is able to “live in silico.”     

BESSICC, a COSMO-RS based tool for in silico solvent screening of biocatalyzed reactions

Many enzymatic reactions are near-equilibrium reactions. This often limits final yield and hence application of biocatalyzed processes in the industrial production. The most widely applied strategy to overcome this issue is solvent selection. It must be underlined that measuring the equilibrium position experimentally is a difficult and time-consuming procedure and any tool for predicting the solvent effect on the reaction equilibrium can be very valuable. The present work reports on the development of BESSICC, an algorithm to calculate the effect of medium composition on biocatalyzed reactions equilibrium. It is based on COSMO-RS calculation of activity coefficients of all the species in the reaction mixture and minimization of Gibbs free energy of the reaction. Starting from one single experimental measurement of the equilibrium position for a given biocatalyzed reaction it can predict the yield of the reaction in any other solvent or solvent mixture. Predictions are accurate, the errors of prediction are in average below 25% for the esterification of dodecanoic acid with menthol and below 65% for esterification of 1-dodecanoic acid with 1-dodecanol. The best predictions show an error well below 5%.     

New insights offered by a computational model of deep brain stimulation

Deep brain stimulation (DBS) is a standard neurosurgical procedure used to treat motor symptoms in about 5% of patients with Parkinson's disease (PD). Despite the indisputable success of this procedure, the biological mechanisms underlying the clinical benefits of DBS have not yet been fully elucidated. The paper starts with a brief review on the use of DBS to treat PD symptoms. The second section introduces a computational model based on the population density approach and the Izhikevich neuron model. We explain why this model is appropriate for investigating macroscopic network effects and exploring the physiological mechanisms which respond to this treatment strategy (i.e., DBS). Finally, we present new insights into the ways this computational model may help to elucidate the dynamic network effects produced in a cerebral structure when DBS is applied.     

A yeast assay for high throughput screening of natural anti-viral agents

Over the last decade the yeast Saccharomyces cerevisiae has become a popular organism for studying heterologous gene expression and in vivo protein-protein interactions. Many variations of these basic systems have originated over the years. Besides these vast and varied applications of the yeast expression system, S. cerevisiae has also been used extensively in fundamental research as a model simple eukaryote. We have used the S. cerevisiae system to design a high throughput screen for anti-viral agents from natural sources. The design of the assay rests on the ability of the L-A helper virus and the M(1) satellite virus to detect small variations in -1 ribosomal frameshifting. A minor change in frameshifting efficiencies can be detected and clearly shown phenotypically in terms of zones of clearing on an agar plate. Using such a process, we have initiated a high throughput screening process for natural anti-viral agents.     

The application of a high throughput analysis method for the screening of potential biosurfactants from natural sources

The presence of biosurfactants in growth media can be evaluated by a variety of methods, none of which are suitable for high throughput studies. The method described here is based on the effect of meniscus shape on the image of a grid viewed through the wells of a 96-well plate. The efficacy of the method was demonstrated by the selection of a bacterium (producing a biosurfactant able to reduce the surface tension of pure water from 72 to 28.75 mN m^− 1) from a culture collection isolated from aviation fuel-contaminated land. The assay was found to be more sensitive, rapid and easy to perform than other published methods. It does not need specialised equipment or chemicals and excludes the bias which results from the surfactant properties of medium used for bacterial growth.     

Development of a computational model for astronaut reorientation

The ability to model astronaut reorientations computationally provides a simple way to develop and study human motion control strategies. Since the cost of experimenting in microgravity is high, and underwater training can lead to motions inappropriate for microgravity, these techniques allow for motions to be developed and well-understood prior to any microgravity exposure. By including a model of the current space suit, we have the ability to study both intravehicular and extravehicular activities. We present several techniques for rotating about the axes of the body and show that motions performed by the legs create a greater net rotation than those performed by the arms. Adding a space suit to the motions was seen to increase the resistance torque and limit the available range of motion. While rotations about the body axes can be performed in the current space suit, the resulting motions generated a reduced rotation when compared to the unsuited configuration.     

Development of a high-throughput solubility screening assay for use in antibody discovery

Poor solubility is a common challenge encountered during the development of high concentration monoclonal antibody (mAb) formulations, but there are currently no methods that can provide predictive information on high-concentration behavior of mAbs in early discovery. We explored the utility of methodologies used for determining extrapolated solubility as a way to rank-order mAbs based on their relative solubility properties. We devised two approaches to accomplish this: 1) vapor diffusion technique utilized in traditional protein crystallization practice, and 2) polyethylene glycol (PEG)-induced precipitation and quantitation by turbidity. Using a variety of in-house mAbs with known high-concentration behavior, we demonstrated that both approaches exhibited reliable predictability of the relative solubility properties of these mAbs. Optimizing the latter approach, we developed a format that is capable of screening a large panel of mAbs in multiple pH and buffer conditions. This simple, material-saving, high-throughput approach enables the selection of superior molecules and optimal formulation conditions much earlier in the antibody discovery process, prior to time-consuming and material intensive high-concentration studies.     

Synthesis of sequential polydepsipeptides utilizing a new approach for the synthesis of depsipeptides

Sequential polydepsipeptides were synthesized by the depsipeptide active ester method using a new approach for the direct synthesis of N-protected depsipeptide free acids from hydroxy acids. The method uses synthesis of Boc-didepsipeptides by reaction of free hydroxy acids with Boc-amino acid N-hydroxysuccinimide esters catalyzed by 4-dimethylaminopyridine and chain elongation of the free depsipeptides by the reaction with Boc-amino acid N-hydroxysuccinimide esters in an organic solvent system of acetonitrile-tetrahydrofuran. The Boc-depsipeptide free acids were activated as their N-hydroxysuccinimide esters, which were polymerized after removal of the Boc-protecting group.     

A systems biology approach to the blood-aluminium problem: the application and testing of a computational model

Transport and distribution of systemic aluminium are influenced by its interaction with blood. Current understanding is centred upon the role played by the iron transport protein transferrin which has been shown to bind up to 90% of serum total aluminium. We have coined what we have called the blood-aluminium problem which states that the proportion of serum aluminium which, at any one moment in time, is bound by transferrin is more heavily influenced by kinetic constraints than thermodynamic equilibria with the result that the role played by transferrin in the transport and distribution of aluminium is likely to have been over estimated. To begin to solve the blood-aluminium problem and therewith provide a numerical solution to the aforementioned kinetic constraints we have applied and tested a simple computational model of the time-dependency of a putative transferrin ligand (L) binding aluminium to form an Al-L complex with a probability of existence, K(E), between 0% (no complex) and 100% (complex will not dissociate). The model is based upon the principles of a lattice-gas automaton which when ran for K(E) in the range 0.1-98.0% demonstrated the emergence of complex behaviour which could be defined in the terms of a set of parameters (equilibrium value, E(V), equilibrium time, E(T), peak value, P(V), peak time, P(T), area under curve, AUC) the values of which varied in a predictable way with K(E). When K(E) was set to 98% the model predicted that ca. 90% of the total aluminium would be bound by transferrin within ca. 350 simulation timesteps. We have used a systems biology approach to develop a simple model of the time-dependency of the binding of aluminium by transferrin. To use this approach to begin to solve the blood-aluminium problem we shall need to increase the complexity of the model to better reflect the heterogeneity of a biological system such as the blood.     

High throughput solubility determination with application to selection of compounds for fragment screening

The development and application of a high throughput aqueous solubility assay is reported. Measurements for up to 637 compounds can be made in a fully automated experiment. Results from this assay were used to quantify risk of unacceptable solubility as a function of lipophilicity for neutral fragment-like compounds. Assessment of risk of unacceptable solubility was combined with experimental solubility measurement to select compounds for inclusion in a fragment-screening library.     

Development of a cytokine analog with enhanced stability using computational ultrahigh throughput screening

Granulocyte-colony stimulating factor (G-CSF) is used worldwide to prevent neutropenia caused by high-dose chemotherapy. It has limited stability, strict formulation and storage requirements, and because of poor oral absorption must be administered by injection (typically daily). Thus, there is significant interest in developing analogs with improved pharmacological properties. We used our ultrahigh throughput computational screening method to improve the physicochemical characteristics of G-CSF. Improving these properties can make a molecule more robust, enhance its shelf life, or make it more amenable to alternate delivery systems and formulations. It can also affect clinically important features such as pharmacokinetics. Residues in the buried core were selected for optimization to minimize changes to the surface, thereby maintaining the active site and limiting the designed protein's potential for antigenicity. Using a structure that was homology modeled from bovine G-CSF, core designs of 25-34 residues were completed, corresponding to 10(21)-10(28) sequences screened. The optimal sequence from each design was selected for biophysical characterization and experimental testing; each had 10-14 mutations. The designed proteins showed enhanced thermal stabilities of up to 13 degrees C, displayed five-to 10-fold improvements in shelf life, and were biologically active in cell proliferation assays and in a neutropenic mouse model. Pharmacokinetic studies in monkeys showed that subcutaneous injection of the designed analogs results in greater systemic exposure, probably attributable to improved absorption from the subcutaneous compartment. These results show that our computational method can be used to develop improved pharmaceuticals and illustrate its utility as a powerful protein design tool.     

Bacterial model system for screening and determining optimal concentration of anti-caries natural extracts

In general, an antimicrobial test for screening anti-caries natural extracts was performed by measuring the minimum bactericidal concentration (MBC) against the type strains of mutans streptococci. However, it is unclear if the antimicrobial efficiency of natural extracts on the type strains of mutans streptococci is the same on the clinical strains. In this study, we introduced a bacterial model system for the screening of anti-caries and determining the optimal concentration of them to develop oral hygiene products for Korean populations.     

A simulated dye method for flow visualization with a computational model for blood flow

A numerical dye method for the visualization of unsteady three-dimensional flow calculations is introduced by coupling the unsteady convection-diffusion equation to the Navier-Stokes equation for mass and momentum. This system of equations is descretized using a finite volume projection-like algorithm with generalized coordinates and overset grids. A powerful pressure prediction method is used to accelerate the convergence of the Pressure Poisson equation. To demonstrate the visualization technique, blood flow through the aortic arch region and the three main arterial branches is computed using various Womersley numbers. In this technique, parcels of fluid are followed in time as a function of the cardiac cycle without having to track individual particles, which in turn aids us to better understand some important aspects of the three-dimensionality of the developing unsteady flow. Using this numerical dye method we analyze the strength of the cross flow during the cardiac cycle, the relationship between the penetration of blood into the aortic branches from its relative position in the ascending aortic region and the effects of the Womersley parameter. This technique can be very useful in the design and development of stents where the topology of the device would require understanding where the blood emanating from the heart ends up at the end of the cardiac cycle. Moreover, this method could be useful in investigating the influence of flow and geometry on the local introduction of medication.