EDULISS: a small-molecule database with data-mining and pharmacophore searching capabilities

We present the relational database EDULISS (EDinburgh University Ligand Selection System), which stores structural, physicochemical and pharmacophoric properties of small molecules. The database comprises a collection of over 4 million commercially available compounds from 28 different suppliers. A user-friendly web-based interface for EDULISS (available at http://eduliss.bch.ed.ac.uk/) has been established providing a number of data-mining possibilities. For each compound a single 3D conformer is stored along with over 1600 calculated descriptor values (molecular properties). A very efficient method for unique compound recognition, especially for a large scale database, is demonstrated by making use of small subgroups of the descriptors. Many of the shape and distance descriptors are held as pre-calculated bit strings permitting fast and efficient similarity and pharmacophore searches which can be used to identify families of related compounds for biological testing. Two ligand searching applications are given to demonstrate how EDULISS can be used to extract families of molecules with selected structural and biophysical features

High throughput chemical screening for anti-virulence developmental phenotypes in Trypanosoma brucei

In the bloodstream of mammalian hosts, the sleeping sickness parasite, Trypanosoma brucei, exists as a proliferative slender form or a nonproliferative, transmissible, stumpy form. The transition between these developmental forms is controlled by a density-dependent mechanism that is important for the parasite's infection dynamics, immune evasion via ordered antigenic variation, and disease transmissibility. However, stumpy formation has been lost in most laboratory-adapted trypanosome lines, generating monomorphic parasites that proliferate uncontrolled as slender forms in vitro and in vivo. Nonetheless, these forms are readily amenable to cell culture and high-throughput screening for trypanocidal lead compounds. Here, we have developed and exploited a high-throughput screen for developmental phenotypes using a transgenic monomorphic cell line expressing a reporter under the regulation of gene control signals from the stumpy-specific molecule PAD1. Using a whole-cell fluorescence-based assay to screen over 6,000 small molecules from a kinase-focused compound library, small molecules able to activate stumpy-specific gene expression and proliferation arrest were assayed in a rapid assay format. Independent follow-up validation identified one hit able to induce modest, yet specific, changes in mRNA expression indicative of a partial differentiation to stumpy forms in monomorphs. Further, in pleomorphs this compound induced a stumpy-like phenotype, entailing growth arrest, morphological changes, PAD1 expression, and enhanced differentiation to procyclic forms. This not only provides a potential tool compound for the further understanding of stumpy formation but also demonstrates the use of high-throughput screening in the identification of compounds able to induce specific phenotypes, such as differentiation, in African trypanosomes

Discovery of a new class of inhibitors for the protein arginine deiminase type 4 (PAD4) by structure-based virtual screening

<p>Abstract</p> <p>Background</p> <p>Rheumatoid arthritis (RA) is an autoimmune disease with unknown etiology. Anticitrullinated protein autoantibody has been documented as a highly specific autoantibody associated with RA. Protein arginine deiminase type 4 (PAD4) is the enzyme responsible for catalyzing the conversion of peptidylarginine into peptidylcitrulline. PAD4 is a new therapeutic target for RA treatment. In order to search for inhibitors of PAD4, structure-based virtual screening was performed using LIDAEUS (Ligand discovery at Edinburgh university). Potential inhibitors were screened experimentally by inhibition assays.</p> <p>Results</p> <p>Twenty two of the top-ranked water-soluble compounds were selected for inhibitory screening against PAD4. Three compounds showed significant inhibition of PAD4 and their IC₅₀values were investigated. The structures of the three compounds show no resemblance with previously discovered PAD4 inhibitors, nor with existing drugs for RA treatment.</p> <p>Conclusion</p> <p>Three compounds were discovered as potential inhibitors of PAD4 by virtual screening. The compounds are commercially available and can be used as scaffolds to design more potent inhibitors against PAD4.</p

UFSRAT:Ultra-fast shape recognition with atom types -The discovery of novel bioactive small molecular scaffolds for FKBP12 and 11βHSD1

MOTIVATION:Using molecular similarity to discover bioactive small molecules with novel chemical scaffolds can be computationally demanding. We describe Ultra-fast Shape Recognition with Atom Types (UFSRAT), an efficient algorithm that considers both the 3D distribution (shape) and electrostatics of atoms to score and retrieve molecules capable of making similar interactions to those of the supplied query. RESULTS:Computational optimization and pre-calculation of molecular descriptors enables a query molecule to be run against a database containing 3.8 million molecules and results returned in under 10 seconds on modest hardware. UFSRAT has been used in pipelines to identify bioactive molecules for two clinically relevant drug targets; FK506-Binding Protein 12 and 11β-hydroxysteroid dehydrogenase type 1. In the case of FK506-Binding Protein 12, UFSRAT was used as the first step in a structure-based virtual screening pipeline, yielding many actives, of which the most active shows a KD, app of 281 µM and contains a substructure present in the query compound. Success was also achieved running solely the UFSRAT technique to identify new actives for 11β-hydroxysteroid dehydrogenase type 1, for which the most active displays an IC50 of 67 nM in a cell based assay and contains a substructure radically different to the query. This demonstrates the valuable ability of the UFSRAT algorithm to perform scaffold hops. AVAILABILITY AND IMPLEMENTATION:A web-based implementation of the algorithm is freely available at http://opus.bch.ed.ac.uk/ufsrat/

11β-Hydroxysteroid dehydrogenase type 1 contributes to the balance between 7-keto- and 7-hydroxy-oxysterols in vivo

Abstract11β-Hydroxysteroid dehydrogenase 1 (11βHSD1; EC 1.1.1.146) generates active glucocorticoids from inert 11-keto metabolites. However, it can also metabolize alternative substrates, including 7β-hydroxy- and 7-keto-cholesterol (7βOHC, 7KC). This has been demonstrated in vitro but its consequences in vivo are uncertain. We used genetically modified mice to investigate the contribution of 11βHSD1 to the balance of circulating levels of 7KC and 7βOHC in vivo, and dissected in vitro the kinetics of the interactions between oxysterols and glucocorticoids for metabolism by the mouse enzyme.Circulating levels of 7KC and 7βOHC in mice were 91.3±22.3 and 22.6±5.7nM respectively, increasing to 1240±220 and 406±39nM in ApoE−/− mice receiving atherogenic western diet. Disruption of 11βHSD1 in mice increased (p<0.05) the 7KC/7βOHC ratio in plasma (by 20%) and also in isolated microsomes (2 fold). The 7KC/7βOHC ratio was similarly increased when NADPH generation was restricted by disruption of hexose-6-phosphate dehydrogenase.Reduction and oxidation of 7-oxysterols by murine 11βHSD1 proceeded more slowly and substrate affinity was lower than for glucocorticoids. in vitro 7βOHC was a competitive inhibitor of oxidation of corticosterone (Ki=0.9μM), whereas 7KC only weakly inhibited reduction of 11-dehydrocorticosterone. However, supplementation of 7-oxysterols in cultured cells, secondary to cholesterol loading, preferentially slowed reduction of glucocorticoids, rather than oxidation.Thus, in mouse, 11βHSD1 influenced the abundance and balance of circulating and tissue levels of 7βOHC and 7KC, promoting reduction of 7KC. In health, 7-oxysterols are unlikely to regulate glucocorticoid metabolism. However, in hyperlipidaemia, 7-oxysterols may inhibit glucocorticoid metabolism and modulate signaling through corticosteroid receptors

Development of high performance structure and ligand based virtual screening techniques

Virtual Sreening (VS) is an in silico technique for drug discovery. An overview of VS methods is given and is seen to be approachable from two sides: structure based and ligand based. Structure based virtual screening uses explicit knowledge of the target receptor to suggest candidate receptor-ligand complexes. Ligand based virtual screening can infer required characteristics of binders from known ligands. A consideration for all virtual screening techniques is the amount of computing time required to arrive at a solution. For this reason, techniques of high performance computing have been applied to both the structural and ligand based approaches. A proven structure based virtual screening code LIDAEUS (Ligand Discovery At Edinburgh University) has been ported and parallelised to a massively parallel computing platform, the University of Edinburgh’s IBM Bluegene/l, consisting of 2,048 processor cores. A challenge in achieving scaling to such a large number of processors required implementation of a minimal communication parallel sort algorithm. Parallel efficiencies achieved within this parallelisation exceeded 99%, confirming that a near optimum strategy has been followed and capacity for running the code on a greater number of processors exists. This implementation of the program has been successfully used with a number of protein targets. The development of a new ligand based virtual screening code has been completed. The program UFSRAT (Ultra Fast Shape Recognition with Atom Types) takes the features of known binders and suggests molecules which will be able to make similar interactions. This similarity method is both fast (1 million molecules per hour per processor) and independent of input orientation. Along with UFSRAT, some other methods (VolRAT and UFSRGraph) based on UFSRAT have been developed, addressing different approaches to ligand based virtual screening. UFSRAT as an approach to discovering novel protein-ligand complexes has been validated with the discovery of a number of inhibitors for 11β-Hydroxysteroid Dehydrogenase type 1 and FK binding protein 12

Development of high performance structure and ligand based virtual screening techniques

Virtual Sreening (VS) is an in silico technique for drug discovery. An overview of VS methods is given and is seen to be approachable from two sides: structure based and ligand based. Structure based virtual screening uses explicit knowledge of the target receptor to suggest candidate receptor-ligand complexes. Ligand based virtual screening can infer required characteristics of binders from known ligands. A consideration for all virtual screening techniques is the amount of computing time required to arrive at a solution. For this reason, techniques of high performance computing have been applied to both the structural and ligand based approaches. A proven structure based virtual screening code LIDAEUS (Ligand Discovery At Edinburgh University) has been ported and parallelised to a massively parallel computing platform, the University of Edinburgh’s IBM Bluegene/l, consisting of 2,048 processor cores. A challenge in achieving scaling to such a large number of processors required implementation of a minimal communication parallel sort algorithm. Parallel efficiencies achieved within this parallelisation exceeded 99%, confirming that a near optimum strategy has been followed and capacity for running the code on a greater number of processors exists. This implementation of the program has been successfully used with a number of protein targets. The development of a new ligand based virtual screening code has been completed. The program UFSRAT (Ultra Fast Shape Recognition with Atom Types) takes the features of known binders and suggests molecules which will be able to make similar interactions. This similarity method is both fast (1 million molecules per hour per processor) and independent of input orientation. Along with UFSRAT, some other methods (VolRAT and UFSRGraph) based on UFSRAT have been developed, addressing different approaches to ligand based virtual screening. UFSRAT as an approach to discovering novel protein-ligand complexes has been validated with the discovery of a number of inhibitors for 11β-Hydroxysteroid Dehydrogenase type 1 and FK binding protein 12.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The UFSRAT workflow.

<p>The UFSRAT workflow.</p

Binding data for 11β-HSD1.

<p>Molecules 5, 6, 7 and 8 were retrieved using carbenoxolone as a query molecule supplied to the UFSRAT technique and screened against the EDULISS database. Binding of the top hits was tested using a scintillation proximity assay (SPA) and fluorescence assay (Fluoresc).</p><p>* HEK-293 cells transfected with human 11β-HSD1</p><p># Recombinant 11β-HSD1</p><p>Binding data for 11β-HSD1.</p