The Investigation of the Effects of Polyelectrolyte Attributes on Complex Coacervate Properties using High-Throughput Formulation and Characterization Techniques

2005 ◽  
Vol 894 ◽  
Author(s):  
Robert Lochhead ◽  
Lisa R. Huisinga ◽  
Christina Edwards ◽  
Anthony Hill

AbstractFormulators of complex mixtures have long known that the characteristics of their final formulation and the position of “equilibrium” often depends critically upon the order of addition of ingredients and the precise processing conditions under which the formulation was made. The large variety of possible outcomes derive from the many eigenstates that are available to each composition of a complex mixture due to the fact that the bonds between the component molecules are weak physical bonds and therefore a potential multitude of nanostructures can be formed. This is especially true of systems comprising polyelectrolytes and oppositely charged surfactants in the semi-dilute regime, because both polyelectrolyte conformation and surfactant micellar association structures are strongly influenced by the ionic environment of the polymer and surfactant molecules. This is especially important for 2-in-1 shampoos that depend upon the spontaneous creation of a polyelectrolyte/surfactant coacervate to deposit active conditioning, styling or antidandruff ingredients during the shampoo process. The investigation of the effects of order of addition requires exanimation of a myriad of samples and it is virtually impossible by conventional techniques. This task is ideally suited to investigation by a combinatorial approach aimed at the generation of libraries of pseudo-phase diagrams. In this study we developed a high-throughput screening method to generate phase diagrams over a large range of concentrations for cationic polysaccharide interaction with anionic surfactant in the presence and absence of dissolved electrolyte. Using a liquid handling system for sample preparation, we are able to analyze nearly 1000 samples per day, making the above goals of understanding electrolyte effects and coacervate structure-property relationships attainable.

2013 ◽  
Vol 15 (9) ◽  
pp. 475-482 ◽  
Author(s):  
Alexandra C. Rinkenauer ◽  
Antje Vollrath ◽  
Anja Schallon ◽  
Lutz Tauhardt ◽  
Kristian Kempe ◽  
...  

2021 ◽  
Author(s):  
Emmanuel Ren ◽  
François-Xavier Coudert

<div> <div> <div> <p>Nanoporous framework materials are a promising class of materials for energy-efficient technology of xenon/krypton separation by physisorption. Many studies on Xe/Kr separation by adsorption have fo- cused on the determination of structure/property relationships, the description of theoretical limits of performance, and the identification of top-performing materials. Here, we provided a study based on high-throughput screening of the adsorption of Xe, Kr, and Xe/Kr mixtures in 12,020 experimental MOFs materials, in order to provide a better comprehension of the thermodynamics behind Xe/Kr separation in nanoporous materials and the microscopic origins of Xe/Kr selectivity at both low and ambient pressure. </p> </div> </div> </div>


2021 ◽  
Author(s):  
Emmanuel Ren ◽  
François-Xavier Coudert

<div> <div> <div> <p>Nanoporous framework materials are a promising class of materials for energy-efficient technology of xenon/krypton separation by physisorption. Many studies on Xe/Kr separation by adsorption have fo- cused on the determination of structure/property relationships, the description of theoretical limits of performance, and the identification of top-performing materials. Here, we provided a study based on high-throughput screening of the adsorption of Xe, Kr, and Xe/Kr mixtures in 12,020 experimental MOFs materials, in order to provide a better comprehension of the thermodynamics behind Xe/Kr separation in nanoporous materials and the microscopic origins of Xe/Kr selectivity at both low and ambient pressure. </p> </div> </div> </div>


2019 ◽  
Author(s):  
Huifang Xu ◽  
Weinan Liang ◽  
Linlin Ning ◽  
Yuanyuan Jiang ◽  
Wenxia Yang ◽  
...  

P450 fatty acid decarboxylases (FADCs) have recently been attracting considerable attention owing to their one-step direct production of industrially important 1-alkenes from biologically abundant feedstock free fatty acids under mild conditions. However, attempts to improve the catalytic activity of FADCs have met with little success. Protein engineering has been limited to selected residues and small mutant libraries due to lack of an effective high-throughput screening (HTS) method. Here, we devise a catalase-deficient <i>Escherichia coli</i> host strain and report an HTS approach based on colorimetric detection of H<sub>2</sub>O<sub>2</sub>-consumption activity of FADCs. Directed evolution enabled by this method has led to effective identification for the first time of improved FADC variants for medium-chain 1-alkene production from both DNA shuffling and random mutagenesis libraries. Advantageously, this screening method can be extended to other enzymes that stoichiometrically utilize H<sub>2</sub>O<sub>2</sub> as co-substrate.


2011 ◽  
Vol 16 (8) ◽  
pp. 869-877 ◽  
Author(s):  
Duncan I. Mackie ◽  
David L. Roman

In this study, the authors used AlphaScreen technology to develop a high-throughput screening method for interrogating small-molecule libraries for inhibitors of the Gαo–RGS17 interaction. RGS17 is implicated in the growth, proliferation, metastasis, and the migration of prostate and lung cancers. RGS17 is upregulated in lung and prostate tumors up to a 13-fold increase over patient-matched normal tissues. Studies show RGS17 knockdown inhibits colony formation and decreases tumorigenesis in nude mice. The screen in this study uses a measurement of the Gαo–RGS17 protein–protein interaction, with an excellent Z score exceeding 0.73, a signal-to-noise ratio >70, and a screening time of 1100 compounds per hour. The authors screened the NCI Diversity Set II and determined 35 initial hits, of which 16 were confirmed after screening against controls. The 16 compounds exhibited IC50 <10 µM in dose–response experiments. Four exhibited IC50 values <6 µM while inhibiting the Gαo–RGS17 interaction >50% when compared to a biotinylated glutathione-S-transferase control. This report describes the first high-throughput screen for RGS17 inhibitors, as well as a novel paradigm adaptable to many other RGS proteins, which are emerging as attractive drug targets for modulating G-protein-coupled receptor signaling.


2020 ◽  
Author(s):  
Yuru Wang ◽  
Christopher D Katanski ◽  
Christopher Watkins ◽  
Jessica N Pan ◽  
Qing Dai ◽  
...  

Abstract AlkB is a DNA/RNA repair enzyme that removes base alkylations such as N1-methyladenosine (m1A) or N3-methylcytosine (m3C) from DNA and RNA. The AlkB enzyme has been used as a critical tool to facilitate tRNA sequencing and identification of mRNA modifications. As a tool, AlkB mutants with better reactivity and new functionalities are highly desired; however, previous identification of such AlkB mutants was based on the classical approach of targeted mutagenesis. Here, we introduce a high-throughput screening method to evaluate libraries of AlkB variants for demethylation activity on RNA and DNA substrates. This method is based on a fluorogenic RNA aptamer with an internal modified RNA/DNA residue which can block reverse transcription or introduce mutations leading to loss of fluorescence inherent in the cDNA product. Demethylation by an AlkB variant eliminates the blockage or mutation thereby restores the fluorescence signals. We applied our screening method to sites D135 and R210 in the Escherichia coli AlkB protein and identified a variant with improved activity beyond a previously known hyperactive mutant toward N1-methylguanosine (m1G) in RNA. We also applied our method to O6-methylguanosine (O6mG) modified DNA substrates and identified candidate AlkB variants with demethylating activity. Our study provides a high-throughput screening method for in vitro evolution of any demethylase enzyme.


2021 ◽  
Vol 22 (6) ◽  
pp. 3041
Author(s):  
Gheorghita Menghiu ◽  
Vasile Ostafe ◽  
Radivoje Prodanović ◽  
Rainer Fischer ◽  
Raluca Ostafe

Chitinases catalyze the degradation of chitin, a polymer of N-acetylglucosamine found in crustacean shells, insect cuticles, and fungal cell walls. There is great interest in the development of improved chitinases to address the environmental burden of chitin waste from the food processing industry as well as the potential medical, agricultural, and industrial uses of partially deacetylated chitin (chitosan) and its products (chito-oligosaccharides). The depolymerization of chitin can be achieved using chemical and physical treatments, but an enzymatic process would be more environmentally friendly and more sustainable. However, chitinases are slow-acting enzymes, limiting their biotechnological exploitation, although this can be overcome by molecular evolution approaches to enhance the features required for specific applications. The two main goals of this study were the development of a high-throughput screening system for chitinase activity (which could be extrapolated to other hydrolytic enzymes), and the deployment of this new method to select improved chitinase variants. We therefore cloned and expressed the Bacillus licheniformis DSM8785 chitinase A (chiA) gene in Escherichia coli BL21 (DE3) cells and generated a mutant library by error-prone PCR. We then developed a screening method based on fluorescence-activated cell sorting (FACS) using the model substrate 4-methylumbelliferyl β-d-N,N′,N″-triacetyl chitotrioside to identify improved enzymes. We prevented cross-talk between emulsion compartments caused by the hydrophobicity of 4-methylumbelliferone, the fluorescent product of the enzymatic reaction, by incorporating cyclodextrins into the aqueous phases. We also addressed the toxicity of long-term chiA expression in E. coli by limiting the reaction time. We identified 12 mutants containing 2–8 mutations per gene resulting in up to twofold higher activity than wild-type ChiA.


2009 ◽  
Vol 46 (3) ◽  
pp. 345-349 ◽  
Author(s):  
Bo Wang ◽  
Xiaoling Tang ◽  
Gangfeng Ren ◽  
Ji Liu ◽  
Hongwei Yu

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