Open Access High Throughput Drug Discovery in the Public Domain: A Mount Everest in the Making

High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry’s best practices for a successful outcome

A Review on Edge Detection Algorithms in Digital Image Processing Applications

Edge detection is one of the major step in Image segmentation, image enhancement, image detection and recognition applications. The main goal of edge detection is that to localize the variation in the intensity of an image to identify the phenomena of physical properties which produced by the capturing device. An edge might be characterized as a set of neighborhood pixels that forms a boundary between two different regions. Detecting the edges is an essential technique for segmenting the image in to various regions based on their discontinuity in the pixels. Edge detection has very important applications in image processing and computer vison. It is broadly used technique and quick feature extraction technique hence used in various feature extraction and feature detection techniques. There exists several methods in the literature for edge detection such as Canny, Prewitt, Sobel, Maar Hildrith, Robert etc. In this paper we have studied and compared Prewitt, Sobel, and Canny detection operators. Our experimental study shows that the canny operator is giving better results for different kinds of images and has numerous advantages than the other operators such as the nature of adaptive, works better for noisy images and providing the sharp edges with low probability of false detection edges

Measuring and statistically testing the size of the effect of a chemical compound on a continuous in-vitro pharmacological response through a new statistical model of response detection limit

This is an Accepted Manuscript of an article published by Taylor & Francis in the Journal of Biopharmaceutical Statistics in June 2015, available online: http://www.tandfonline.com/10.1080/10543406.2014.920871.Biomolecular screening research frequently searches for the chemical compounds that are most likely to make a biochemical or cell-based assay system produce a strong continuous response. Several doses are tested with each compound and it is assumed that, if there is a dose-response relationship, the relationship follows a monotonic curve, usually a version of the median-effect equation. However, the null hypothesis of no relationship cannot be statistically tested using this equation. We used a linearized version of this equation to define a measure of pharmacological effect size, and use this measure to rank the investigated compounds in order of their overall capability to produce strong responses. The null hypothesis that none of the examined doses of a particular compound produced a strong response can be tested with this approach. The proposed approach is based on a new statistical model of the important concept of response detection limit, a concept that is usually neglected in the analysis of dose-response data with continuous responses. The methodology is illustrated with data from a study searching for compounds that neutralize the infection by a human immunodeficiency virus of brain glioblastoma cells

Implementation of a High-Throughput Screen for Identifying Small Molecules to Activate the Keap1-Nrf2-ARE Pathway

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcription factor that induces a battery of cytoprotective genes involved in antioxidant defense through binding to Antioxidant Response Elements (ARE) located in the promoter regions of these genes. To identify Nrf2 activators for the treatment of oxidative/electrophilic stress-induced diseases, the present study developed a high-throughput assay to evaluate Nrf2 activation using AREc32 cells that contain a luciferase gene under the control of ARE promoters. Of the 47,000 compounds screened, 238 (top 0.5% hits) of the chemicals increased the luminescent signal more than 14.4-fold and were re-tested at eleven concentrations in a range of 0.01–30 µM. Of these 238 compounds, 231 (96%) increased the luminescence signal in a concentration-dependent manner. Chemical structure relationship analysis of these 231 compounds indicated enrichment of four chemical scaffolds (diaryl amides and diaryl ureas, oxazoles and thiazoles, pyranones and thiapyranones, and pyridinones and pyridazinones). In addition, 30 of these 231 compounds were highly effective and/or potent in activating Nrf2, with a greater than 80-fold increase in luminescence, or an EC50 lower than 1.6 µM. These top 30 compounds were also screened in Hepa1c1c7 cells for an increase in Nqo1 mRNA, the prototypical Nrf2-target gene. Of these 30 compounds, 17 increased Nqo1 mRNA in a concentration-dependent manner. In conclusion, the present study documents the development, implementation, and validation of a high-throughput screen to identify activators of the Keap1-Nrf2-ARE pathway. Results from this screening identified Nrf2 activators, and provide novel insights into chemical scaffolds that might prevent oxidative/electrophilic stress-induced toxicity and carcinogenesis.Funding: The present study was funded by United States National Institutes of Health grant DK081461. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Compound Ranking Based on a New Mathematical Measure of Effectiveness Using Time Course Data from Cell-Based Assays

The half maximal inhibitory concentration (IC50) has several limitations that make it unsuitable for examining a large number of compounds in cytotoxicity studies, particularly when multiple exposure periods are tested. This article proposes a new approach to measure drug effectiveness, which allows ranking compounds according to their toxic effects on live cells. This effectiveness measure, which combines all exposure times tested, compares the growth rates of a particular cell line in the presence of the compound with its growth rate in the presence of DMSO alone. Our approach allows measuring a wider spectrum of toxicity than the IC50 approach, and allows automatic analyses of a large number of compounds. It can be easily implemented in linear regression software, provides a comparable measure of effectiveness for each investigated compound (both toxic and non-toxic), and allows statistically testing the null hypothesis that a compound is non-toxic versus the alternative that it is toxic. Importantly, our approach allows defining an automated decision rule for deciding whether a compound is significantly toxic. As an illustration, we describe the results of a cell-based study of the cytotoxicity of 24 analogs of novobiocin, a C-terminal inhibitor of heat shock protein 90 (Hsp90); the compounds were ranked in order of cytotoxicity to a panel of 18 cancer cell lines and 1 normal cell line. Our approach may also be a good alternative to computing the half maximal effective concentration (EC50) in studies searching for compounds that promote cell growth

SERUM LUTEINIZING HORMONE AND FOLLICLE STIMULATING HORMONE IN NORMAL CHILDREN AND PATIENTS WITH VARIOUS CLINICAL DISORDERS

Serum concentrations of luteinizing hormone (LH) and follicle stimulating hormone (FSH) were determined in 329 normal children and 185 individuals with endocrinological abnormalities or variations of development. A significant increase of gonadotrophins is noted at the onset of puberty among the boys and at menarche for girls. The values are compared with serum concentrations of LH and FSH in children with abnormalities of sexual development, pituitary malfunction as well as other clinical abnormalities. Comparable levels for age and stage of development were found for premature thelarche, premature adrenarche, cryptorchidism, male pseudohermaphroditism and pubertal gynaecomastia. Hypogonadal individuals (Klinefelter's and Turner's syndrome, pure ovarian dysgenesis and testicular dysgenesis) have markedly elevated values while those with pituitary hypofunction had low values. Patients with sexual prococity tended to have elevated concentrations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73601/1/j.1365-2265.1973.tb00427.x.pd

How small and medium enterprises are using social networks? Evidence from the Algarve region

The evolution of internet created new opportunities for small and medium enterprises (SME), among which are social networks. This work aims at analyzing the potential of these networks for the SME in Algarve, creating a questionnaire for the purpose. The empirical study revealed that some firms have already an integrated business strategy with social networks, as well as a group in the firm responsible for it. Most of their managers consider that social networks enhance performance, but few really measure these results. A categorical principal component analysis identified two dimensions of social networks’ use: social networks for product-client interaction and knowledge; and social networks with potential for marketing. A supplementary analysis (hierarchical clustering) identified three patterns of SME’s involvement in social networks: cluster Social Net Level 1, cluster Social Net Level 2 and cluster Social Net Level 3. These groups validated the results described above, indicating a sustainable methodological approach