Discovery of novel cathepsin S inhibitors by pharmacophore-based virtual high-throughput screening

The cysteine protease cathepsin S (CatS) is involved in the pathogenesis of autoimmune disorders, atherosclerosis, and obesity. Therefore, it represents a promising pharmacological target for drug development. We generated ligand-based and structure-based pharmacophore models for noncovalent and covalent CatS inhibitors to perform virtual high-throughput screening of chemical databases in order to discover novel scaffolds for CatS inhibitors. An in vitro evaluation of the resulting 15 structures revealed seven CatS inhibitors with kinetic constants in the low micromolar range. These compounds can be subjected to further chemical modifications to obtain drugs for the treatment of autoimmune disorders and atherosclerosis.

Discovery of novel Agonists and antagonists of the free fatty acid receptor 1 (FFAR1) using virtual screening

The G-protein-coupled receptor free fatty acid receptor 1 (FFAR1), previously named GPR40, is a possible novel target for the treatment of type 2 diabetes. In an attempt to identify new ligands for this receptor, we performed virtual screening (VS) based on two-dimensional (2D) similarity, three-dimensional (3D) pharmacophore searches, and docking studies by using the structure of known agonists and our model of the ligand binding site, which was validated by mutagenesis. VS of a database of 2.6 million compounds followed by extraction of structural neighbors of functionally confirmed hits resulted in identification of 15 compounds active at FFAR1 either as full agonists, partial agonists, or pure antagonists. Site-directed mutagenesis and docking studies revealed different patterns of ligand-receptor interactions and provided important information on the role of specific amino acids in binding and activation of FFAR1.

AT(1) receptor ligands: virtual-screening-based design with TOPP descriptors, synthesis, and biological evaluation of pyrrolidine derivatives

As a continuing effort to establish the structure-activity relationships (SARs) within the series of the angiotensin II antagonists (sartans), a pharmacophoric model was built by using novel TOPP 3D descriptors. Statistical values were satisfactory (PC4: r(2)=0.96, q(2) ((5) (random) (groups))=0.84; SDEP=0.26) and encouraged the synthesis and consequent biological evaluation of a series of new pyrrolidine derivatives. SAR together with a combined 3D quantitative SAR and high-throughput virtual screening showed that the newly synthesized 1-acyl-N-(biphenyl-4-ylmethyl)pyrrolidine-2-carboxamides may represent an interesting starting point for the design of new antihypertensive agents. In particular, biological tests performed on CHO-hAT(1) cells stably expressing the human AT(1) receptor showed that the length of the acyl chain is crucial for the receptor interaction and that the valeric chain is the optimal one.

MPO Inhibitors Selected by Virtual Screening

The hemeprotein myeloperoxidase (MPO) participates in innate immune defense through its ability to generate potent microbicidal oxidants. However, these oxidants are also key mediators of the tissue damage associated with many inflammatory diseases. Thus, there is considerable interest in developing therapeutically useful MPO inhibitors. Here, we used structure-based drug design (SBDD) and ligand-based drug design (LBDD) to select for potentially new and selective MPO inhibitors. A pharmacophore model was developed based on the crystal structure of human MPO in complex with salicylhydroxamic acid (SHA), a known inhibitor of the enzyme. The pharmacophore model was used to screen the ZINC database for potential ligands, which were further filtered on the basis of their physical-chemical properties and docking score. The filtered compounds were visually inspected, and nine were purchased for experimental studies. Surprisingly, almost all of the selected compounds belonged to the aromatic hydrazide class, which had been previously described as MPO inhibitors. The compounds selected by virtual screening were shown to inhibit the chlorinating activity of MPO; the top four compounds displayed IC(50) values ranging from 1.0 to 2.8 mM. MPO inactivation by the most effective compound was shown to be irreversible. Overall, our results show that SBDD and LBDD may be useful for the rational development of new MPO inhibitors.

The discovery of new 11beta-hydroxysteroid dehydrogenase type 1 inhibitors by common feature pharmacophore modeling and virtual screening

11beta-Hydroxysteroid dehydrogenase (11beta-HSD) enzymes catalyze the conversion of biologically inactive 11-ketosteroids into their active 11beta-hydroxy derivatives and vice versa. Inhibition of 11beta-HSD1 has considerable therapeutic potential for glucocorticoid-associated diseases including obesity, diabetes, wound healing, and muscle atrophy. Because inhibition of related enzymes such as 11beta-HSD2 and 17beta-HSDs causes sodium retention and hypertension or interferes with sex steroid hormone metabolism, respectively, highly selective 11beta-HSD1 inhibitors are required for successful therapy. Here, we employed the software package Catalyst to develop ligand-based multifeature pharmacophore models for 11beta-HSD1 inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed several selective inhibitors. Efficient inhibition of recombinant human 11beta-HSD1 in intact transfected cells as well as endogenous enzyme in mouse 3T3-L1 adipocytes and C2C12 myotubes was demonstrated for compound 27, which was able to block subsequent cortisol-dependent activation of glucocorticoid receptors with only minor direct effects on the receptor itself. Our results suggest that inhibitor-based pharmacophore models for 11beta-HSD1 in combination with suitable cell-based activity assays, including such for related enzymes, can be used for the identification of selective and potent inhibitors.

Accelerated discovery of novel benzodiazepine ligands by experiment-guided virtual screening.

High throughput discovery of ligand scaffolds for target proteins can accelerate development of leads and drug candidates enormously. Here we describe an innovative workflow for the discovery of high affinity ligands for the benzodiazepine-binding site on the so far not crystallized mammalian GABAA receptors. The procedure includes chemical biology techniques that may be generally applied to other proteins. Prerequisites are a ligand that can be chemically modified with cysteine-reactive groups, knowledge of amino acid residues contributing to the drug-binding pocket, and crystal structures either of proteins homologous to the target protein or, better, of the target itself. Part of the protocol is virtual screening that without additional rounds of optimization in many cases results only in low affinity ligands, even when a target protein has been crystallized. Here we show how the integration of functional data into structure-based screening dramatically improves the performance of the virtual screening. Thus, lead compounds with 14 different scaffolds were identified on the basis of an updated structural model of the diazepam-bound state of the GABAA receptor. Some of these compounds show considerable preference for the α3β2γ2 GABAA receptor subtype.

Typical accuracy and quality control of a process for creating CT-Based virtual bone models

A pragmatic method for assessing the accuracy and precision of a given processing pipeline required for converting computed tomography (CT) image data of bones into representative three dimensional (3D) models of bone shapes is proposed. The method is based on coprocessing a control object with known geometry which enables the assessment of the quality of resulting 3D models. At three stages of the conversion process, distance measurements were obtained and statistically evaluated. For this study, 31 CT datasets were processed. The final 3D model of the control object contained an average deviation from reference values of −1.07±0.52 mm standard deviation (SD) for edge distances and −0.647±0.43 mm SD for parallel side distances of the control object. Coprocessing a reference object enables the assessment of the accuracy and precision of a given processing pipeline for creating CTbased 3D bone models and is suitable for detecting most systematic or human errors when processing a CT-scan. Typical errors have about the same size as the scan resolution.

Toward the Discovery of Vaccine Adjuvants: Coupling In Silico Screening and In Vitro Analysis of Antagonist Binding to Human and Mouse CCR4 Receptors

Background: Adjuvants enhance or modify an immune response that is made to an antigen. An antagonist of the chemokine CCR4 receptor can display adjuvant-like properties by diminishing the ability of CD4+CD25+ regulatory T cells (Tregs) to down-regulate immune responses. Methodology: Here, we have used protein modelling to create a plausible chemokine receptor model with the aim of using virtual screening to identify potential small molecule chemokine antagonists. A combination of homology modelling and molecular docking was used to create a model of the CCR4 receptor in order to investigate potential lead compounds that display antagonistic properties. Three-dimensional structure-based virtual screening of the CCR4 receptor identified 116 small molecules that were calculated to have a high affinity for the receptor; these were tested experimentally for CCR4 antagonism. Fifteen of these small molecules were shown to inhibit specifically CCR4-mediated cellmigration, including that of CCR4(+) Tregs. Significance: Our CCR4 antagonists act as adjuvants augmenting human T cell proliferation in an in vitro immune response model and compound SP50 increases T cell and antibody responses in vivo when combined with vaccine antigens of Mycobacterium tuberculosis and Plasmodium yoelii in mice.

Resource usage monitoring for KVM based virtual machines

Realization of cloud computing has been possible due to availability of virtualization technologies on commodity platforms. Measuring resource usage on the virtualized servers is difficult because of the fact that the performance counters used for resource accounting are not virtualized. Hence, many of the prevalent virtualization technologies like Xen, VMware, KVM etc., use host specific CPU usage monitoring, which is coarse grained. In this paper, we present a performance monitoring tool for KVM based virtualized machines, which measures the CPU overhead incurred by the hypervisor on behalf of the virtual machine along-with the CPU usage of virtual machine itself. This fine-grained resource usage information, provided by the above tool, can be used for diverse situations like resource provisioning to support performance associated QoS requirements, identification of bottlenecks during VM placements, resource profiling of applications in cloud environments, etc. We demonstrate a use case of this tool by measuring the performance of web-servers hosted on a KVM based virtualized server.

A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.

New symmetrical dinucleating ligand based assembly of bridged dicopper(II) and dizinc(II) centers: Synthesis, structure, spectroscopy, magnetic properties and glycoside hydrolysis

Two dinuclear copper(II) complexes Li(H2O)(3)(CH3OH)](4)Cu2Br4]Cu-2(cpdp)(mu-O2CCH3)](4)(OH)(2) (1), Cu (H2O)(4)]Cu-2(cpdp)(mu-O2CC6H5)](2)Cl-2 center dot 5H(2)O (2), and a dinuclear zinc(II) complex Zn-2(cpdp)(mu-O2CCH3)] (3) have been synthesized using pyridine and benzoate functionality based new symmetrical dinucleating ligand, N, N'-Bis2-carboxybenzomethyl]-N, N'-Bis2-pyridylmethyl]-1,3-diaminopropan-2-ol (H(3)cpdp). Complexes 1, 2 and 3 have been synthesized by carrying out reaction of the ligand H3cpdp with stoichiometric amounts of Cu-2(O2CCH3)(4)(H2O)(2)], CuCl2 center dot 2H(2)O/C6H5COONa, and Zn(CH3COO)(2)center dot 2H(2)O, respectively, in methanol in the presence of NaOH at ambient temperature. Characterizations of the complexes have been done using various analytical techniques including single crystal X-ray structure determination. The X-ray crystal structure analyses reveal that the copper(II) ions in complexes 1 and 2 are in a distorted square pyramidal geometry with Cu-Cu separation of 3.455(8) angstrom and 3.492(1)angstrom, respectively. The DFT optimized structure of complex 3 indicates that two zinc(II) ions are in a distorted square pyramidal geometry with Zn-Zn separation of 3.492(8)angstrom. UV-Vis and mass spectrometric analyses of the complexes confirm their dimeric nature in solution. Furthermore, H-1 and C-13 NMR spectroscopic investigations authenticate the integrity of complex 3 in solution. Variable-temperature (2-300 K) magnetic susceptibility measurements show the presence of antiferromagnetic interactions between the copper centers, with J = -26.0 cm(-1) and -23.9 cm(-1) ((H) over cap = -2JS(1)S(2)) in complexes 1 and 2, respectively. In addition, glycosidase-like activity of the complexes has been investigated in aqueous solution at pH similar to 10.5 by UV-Vis spectrophotometric technique using p-nitrophenyl-alpha-D-glucopyranoside (4) and p-nitrophenyl-beta-D-glucopyranoside (5) as model substrates. (C) 2015 Elsevier B.V. All rights reserved.

Advanced breast cancer incidence following population-based mammographic screening

Background: Breast cancer mortality is declining in many Western countries. If mammography screening contributed to decreases in mortality, then decreases in advanced breast cancer incidence should also be noticeable.
Patients and methods: We assessed incidence trends of advanced breast cancer in areas where mammography screening is practiced for at least 7 years with 60% minimum participation and where population-based registration of advanced breast cancer existed. Through a systematic Medline search, we identified relevant published data for Australia, Italy, Norway, Switzerland, The Netherlands, UK and the USA. Data from cancer registries in Northern Ireland, Scotland, the USA (Surveillance, Epidemiology and End Results (SEER), and Connecticut), and Tasmania (Australia) were available for the study. Criterion for advanced cancer was the tumour size, and if not available, spread to regional/distant sites.
Results: Age-adjusted annual percent changes (APCs) were stable or increasing in ten areas (APCs of -0.5% to 1.7%). In four areas (Firenze, the Netherlands, SEER and Connecticut) there were transient downward trends followed by increases back to pre-screening rates.
Conclusions: In areas with widespread sustained mammographic screening, trends in advanced breast cancer incidence do not support a substantial role for screening in the decrease in mortality.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.