Global expression mapping of mammalian genomes

he aim of genome projects is to decipher all the information contained within the DNA of an organism and to study the way this information is processed in physiological processes. It is believed that more than 95% of the information content of the mammalian genome is represented in the protein coding sequences that make up only approximately 2% of the DNA sequence. Consequently much effort is being invested in the study of coding sequences in the form of cDNA analysis. This thesis is concerned with the development of a new strategy for a highly parallel approach to analyse entire cDNA libraries. The strategy is based upon generating sufficient sequence information to identify uniquely more than 100,000 cDNA clones by hybridisation with short oligonucleotides, typically 7 - 10 mers. Each oligonucleotide is hybridised to all cDNA clones in parallel and under stringent conditions positively identifies a subset (3 - 10%) of clones. Oligonucleotides are designed in such a way that each will positively identify a different subset of clones and statistical simulations estimate that approximately 200 such hybridisation events are required to identify uniquely upto 100,000 cDNA sequences. Such a fingerprint can be generated from many cDNA libraries constructed from different tissue mRNAs and will not only lead to the identification of most sequecnes expressed from the genome but also indicate the level of expression by determining the number of times any given sequence is represented across different cDNA libraries. A human foetal brain cDNA library has been constructed and 100,000 clones arrayed into microtitre plates and on nylon membranes. All the required technological developments have been carried out successfully and are presented. In excess of 200 oligonucleotide hybridisations have been performed on a subset of 32,000 cDNA clones and 1,000 sequenced control clones. A detailed analysis of the data on the control clones is presented and the implications for cDNA fingerprinting discussed

A Three-Hybrid Approach to Scanning the Proteome for Targets of Small Molecule Kinase Inhibitors

AbstractIn this study, we explored the application of a yeast three-hybrid (Y3H)-based compound/protein display system to scanning the proteome for targets of kinase inhibitors. Various known cyclin-dependent kinase (CDK) inhibitors, including purine and indenopyrazole analogs, were displayed in the form of methotrexate-based hybrid ligands and deployed in cDNA library or yeast cell array-based screening formats. For all inhibitors, known cell cycle CDKs as well as novel candidate CDK-like and/or CDK-unrelated kinase targets could be identified, many of which were independently confirmed using secondary enzyme assays and affinity chromatography. The Y3H system described here may prove generally useful in the discovery of candidate drug targets

Massive X-ray screening reveals two allosteric drug binding sites of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of repurposing drug libraries containing 5953 individual compounds against the SARS-CoV-2 main protease (Mpro), which is a potent drug target as it is essential for the virus replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. Interestingly, two compounds bind outside the active site to the native dimer interface in close proximity to the S1 binding pocket. Another compound binds in a cleft between the catalytic and dimerization domain of Mpro. Neither binding site is related to the enzymatic active site and both represent attractive targets for drug development against SARS-CoV-2. This X-ray screening approach thus has the potential to help deliver an approved drug on an accelerated time-scale for this and future pandemics

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

An Algorithm for Clustering cDNAs for Gene Expression Analysis

We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. A similarity graph is defined and clusters in that graph correspond to highly connected subgraphs. A polynomial algorithm to compute them efficiently is presented. Our algorithm produces a clustering with some provably good properties. The application that motivated this study was gene expression analysis, where a collection of cDNAs must be clustered based on their oligonucleotide fingerprints. The algorithm has been tested intensively on simulated libraries and was shown to outperform extant methods. It demonstrated robustness to high noise levels. In a blind test on real cDNA fingerprint data the algorithm obtained very good results. Utilizing the results of the algorithm would have saved over 70% of the cDNA sequencing cost on that data set. 1 Introduction Cluster analysis seeks grouping of data elements into subsets, so that elements in the same subset are in some sense more cl..