37 resultados para High-throughput screening

em Aston University Research Archive


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It has been recognised for some time that a full code of amino acid-based recognition of DNA sequences would be useful. Several approaches, which utilise small DNA binding motifs called zinc fingers, are presently employed. None of the current approaches successfully combine a combinatorial approach to the elucidation of a code with a single stage high throughput screening assay. The work outlined here describes the development of a model system for the study of DNA protein interactions and the development of a high throughput assay for detection of such interactions. A zinc finger protein was designed which will bind with high affinity and specificity to a known DNA sequence. For future work it is possible to mutate the region of the zinc finger responsible for the specificity of binding, in order to observe the effect on the DNA / protein interactions. The zinc finger protein was initially synthesised as a His tagged product. It was not possible however to develop a high throughput assay using the His tagged zinc finger protein. The gene encoding the zinc finger protein was altered and the protein synthesised as a Glutathione S-Transferase (GST) fusion product. A successful assay was developed using the GST protein and Scintillation Proximity Assay technology (Amersham Pharmacia Biotech). The scintillation proximity assay is a dynamic assay that allows the DNA protein interactions to be studied in "real time". This assay not only provides a high throughput method of screening zinc finger proteins for potential ligands but also allows the effect of addition of reagents or competitor ligands to be monitored.

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Saturation mutagenesis is a powerful tool in modern protein engineering. This can allow the analysis of potential new properties thus allowing key residues within a protein to be targeted and randomised. However, the creation of large libraries using conventional saturation mutagenesis with degenerate codons (NNN or NNK) has inherent redundancy and disparities in residue representation. In this we describe the combination of ProxiMAX randomisation and CIS display for the use of generating novel peptides. Unlike other methods ProxiMAX randomisation does not require any intricate chemistry but simply utilises synthetic DNA and molecular biology techniques. Designed ‘MAX’ oligonucleotides were ligated, amplified and digested in an iterative cycle. Results show that randomised ‘MAX’ codons can be added sequentially to the base sequence creating a series of randomised non-degenerate codons that can subsequently be inserted into a gene. CIS display (Isogencia, UK) is an in vitro DNA based screening method that creates a genotype to phenotype link between a peptide and the nucleic acid that encodes it. The use of straight forward in vitro transcription/translation and other molecular biology techniques permits ease of use along with flexibility making it a potent screening technique. Using ProxiMAX randomisation in combination with CIS display, the aim is to produce randomised anti-nerve growth factor (NGF) and calcitonin gene-related (CGRP) peptides to demonstrate the high-throughput nature of this combination.

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Bone marrow mesenchymal stem cells (MSCs) promote nerve growth and functional recovery in animal models of spinal cord injury (SCI) to varying levels. The authors have tested high-content screening to examine the effects of MSC-conditioned medium (MSC-CM) on neurite outgrowth from the human neuroblastoma cell line SH-SY5Y and from explants of chick dorsal root ganglia (DRG). These analyses were compared to previously published methods that involved hand-tracing individual neurites. Both methods demonstrated that MSC-CM promoted neurite outgrowth. Each showed the proportion of SH-SY5Y cells with neurites increased by ~200% in MSC-CM within 48 h, and the number of neurites/SH-SY5Y cells was significantly increased in MSC-CM compared with control medium. For high-content screening, the analysis was performed within minutes, testing multiple samples of MSC-CM and in each case measuring >15,000 SH-SY5Y cells. In contrast, the manual measurement of neurite outgrowth from >200 SH-SY5Y cells in a single sample of MSC-CM took at least 1 h. High-content analysis provided additional measures of increased neurite branching in MSC-CM compared with control medium. MSC-CM was also found to stimulate neurite outgrowth in DRG explants using either method. The application of the high-content analysis was less well optimized for measuring neurite outgrowth from DRG explants than from SH-SY5Y cells.

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Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.

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Fluorescent polymers imprinted with various N1-benzylidene pyridine-2-carboxamidrazones were evaluated for their recognition of the original template and cross-reactivity to similar molecules. Dramatic quenching of fluorescence approaching background levels was observed for most cases where the "empty" MIP was re-exposed to its template. Molecules too large to enter the imprinted cavities gave no reduction of fluorescence. Other compounds were found to quench the fluorescence and are assumed to have entered the imprinted cavities. There is also evidence for partial responses which may give some measure of partial binding. The fluorescence response profiles of substrates containing polycyclic aromatics were found to be quite different from those containing flexible substituents. In order to make this approach more suitable for high-throughput screening a method has been validated wherein the extent of substrate-induced fluorescence quenching may be obtained without having to know how much polymer is present. © 2001 Elsevier Science B.V. All rights reserved.

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This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.

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The number of new chemical entities (NCE) is increasing every day after the introduction of combinatorial chemistry and high throughput screening to the drug discovery cycle. One third of these new compounds have aqueous solubility less than 20µg/mL [1]. Therefore, a great deal of interest has been forwarded to the salt formation technique to overcome solubility limitations. This study aims to improve the drug solubility of a Biopharmaceutical Classification System class II (BCS II) model drug (Indomethacin; IND) using basic amino acids (L-arginine, L-lysine and L-histidine) as counterions. Three new salts were prepared using freeze drying method and characterised by FT-IR spectroscopy, proton nuclear magnetic resonance ((1)HNMR), Differential Scanning Calorimetry (DSC) and Thermogravimetric analysis (TGA). The effect of pH on IND solubility was also investigated using pH-solubility profile. Both arginine and lysine formed novel salts with IND, while histidine failed to dissociate the free acid and in turn no salt was formed. Arginine and lysine increased IND solubility by 10,000 and 2296 fold, respectively. An increase in dissolution rate was also observed for the novel salts. Since these new salts have improved IND solubility to that similar to BCS class I drugs, IND salts could be considered for possible waivers of bioequivalence.

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Genetic experiments over the last few decades have identified many regulatory proteins critical for DNA transcription. The dynamics of their transcriptional activities shape the differential expression of the genes they control. Here we describe a simple method, based on the secreted luciferase, to measure the activities of two transcription factors NF?B and HIF. This technique can effectively monitor dynamics of transcriptional events in a population of cells and be up-scaled for high-throughput screening and promoter analysis, making it ideal for data-demanding applications such as mathematical modelling.

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The universally conserved translation elongation factor EF-Tu delivers aminoacyl(aa)-tRNA in the form of an aa-tRNA·EF-Tu·GTP ternary complex (TC) to the ribosome where it binds to the cognate mRNA codon within the ribosomal A-site, leading to formation of a pretranslocation (PRE) complex. Here we describe preparation of QSY9 and Cy5 derivatives of the variant E348C-EF-Tu that are functional in translation elongation. Together with fluorophore derivatives of aa-tRNA and of ribosomal protein L11, located within the GTPase associated center (GAC), these labeled EF-Tus allow development of two new FRET assays that permit the dynamics of distance changes between EF-Tu and both L11 (Tu-L11 assay) and aa-tRNA (Tu-tRNA assay) to be determined during the decoding process. We use these assays to examine: (i) the relative rates of EF-Tu movement away from the GAC and from aa-tRNA during decoding, (ii) the effects of the misreading-inducing antibiotics streptomycin and paromomycin on tRNA selection at the A-site, and (iii) how strengthening the binding of aa-tRNA to EF-Tu affects the rate of EF-Tu movement away from L11 on the ribosome. These FRET assays have the potential to be adapted for high throughput screening of ribosomal antibiotics.

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Reliable, high throughput, in vitro preliminary screening batteries have the potential to greatly accelerate the rate at which regulatory neurotoxicity data is generated. This study evaluated the importance of astrocytes when predicting acute toxic potential using a neuronal screening battery of pure neuronal (NT2.N) and astrocytic (NT2.A) and integrated neuronal/astrocytic (NT2.N/A) cell systems derived from the human NT2.D1 cell line, using biochemical endpoints (mitochondrial membrane potential (MMP) depolarisation and ATP and GSH depletion). Following exposure for 72 h, the known acute human neurotoxicants trimethyltin-chloride, chloroquine and 6-hydroxydopamine were frequently capable of disrupting biochemical processes in all of the cell systems at non-cytotoxic concentrations. Astrocytes provide key metabolic and protective support to neurons during toxic challenge in vivo and generally the astrocyte containing cell systems showed increased tolerance to toxicant insult compared with the NT2.N mono-culture in vitro. Whilst there was no consistent relationship between MMP, ATP and GSH log IC(50) values for the NT2.N/A and NT2.A cell systems, these data did provide preliminary evidence of modulation of the acute neuronal toxic response by astrocytes. In conclusion, the suitability of NT2 neurons and astrocytes as cell systems for acute toxicity screening deserves further investigation.

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The production of sufficient quantities of protein is an essential prelude to a structure determination, but for many viral and human proteins this cannot be achieved using prokaryotic expression systems. Groups in the Structural Proteomics In Europe (SPINE) consortium have developed and implemented high-throughput (HTP) methodologies for cloning, expression screening and protein production in eukaryotic systems. Studies focused on three systems: yeast (Pichia pastoris and Saccharomyces cerevisiae), baculovirus-infected insect cells and transient expression in mammalian cells. Suitable vectors for HTP cloning are described and results from their use in expression screening and protein-production pipelines are reported. Strategies for co-expression, selenomethionine labelling (in all three eukaryotic systems) and control of glycosylation (for secreted proteins in mammalian cells) are assessed. © International Union of Crystallography, 2006.

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Protein crystallization is of strategic and commercial relevance in the post-genomic era because of its pivotal role in structural proteomics projects. Although protein structures are crucial for understanding the function of proteins and to the success of rational drug design and other biotechnology applications, obtaining high quality crystals is a major bottleneck to progress. The major means of obtaining crystals is by massive-scale screening of a target protein solution with numerous crystallizing agents. However, when crystals appear in these screens, one cannot easily know if they are crystals of protein, salt, or any other molecule that happens to be present in the trials. We present here a method based on Attenuated Total Reflection (ATR)-FT-IR imaging that reliably identifies protein crystals through a combination of chemical specificity and the visualizing capability of this approach, thus solving a major hurdle in protein crystallization. ATR-FT-IR imaging was successfully applied to study the crystallization of thaumatin and lysozyme in a high-throughput manner, simultaneously from six different solutions. This approach is fast as it studies protein crystallization in situ and provides an opportunity to examine many different samples under a range of conditions.