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

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

Development of a Cell-Based High-Throughput Assay to Screen for Inhibitors of Organic Anion Transporting Polypeptides 1B1 and 1B3

The two organic anion transporting polypeptides (OATPs) 1B1 and 1B3 are expressed at the sinusoidal membrane of hepatocytes. They have a broad and overlapping substrate specificity and transport many endobiotics and drugs. Specific inhibitors are required to determine the contribution of each OATP to the hepatocellular uptake of common substrates. We have developed a cell-based high-throughput assay to screen chemical libraries in order to identify such inhibitors for OATP1B1 and OATP1B3. We have used OATP1B1- or OATP1B3-expressing Chinese Hamster Ovary cells on 96-well plates and determined uptake of fluorescein-methotrexate (FMTX). We validated the assay with known inhibitors and screened the well characterized Prestwick library of 1120 drugs. Along with several known OATP inhibitors including rifampicin, cyclosporine A and mifepristone we identified some new inhibitors. For inhibitors that seemed to be able to distinguish between OATP1B1- and OATP1B3-mediated FMTX uptake IC50 values were determined. Estropipate (estrone-3-sulfate stabilized with piperazine) was the most selective OATP1B1 inhibitor (IC50 = 0.06 μM vs. 19.3 μM for OATP1B3). Ursolic acid was the most selective OATP1B3 inhibitor (IC50 = 2.3 μM vs. 12.5 μM for OATP1B1). In conclusion, this cell-based assay should allow us to identify even more specific inhibitors by screening larger chemical libraries

Bioactivity Profiling of Plant Biodiversity of Panama by High Throughput Screening

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.We report relative bioactivities of extracts prepared from a large collection of plants from three national parks in Panama. Over 181 plants were collected, taxonomically identified and their detannified dichloromethane (DCM)-methanolic extracts were used for profiling selected bioactivities. Assays were performed to evaluate the antioxidant activity of the extracts for Antioxidant Response Element (ARE) induction, total non-enzymatic antioxidant potential, anti-inflammatory and anticancer properties. The high throughput analysis of 280 extracts resulted in identification of 57.5% of the extracts that could induce ARE at one or more concentrations tested, 93.5% that harbored total antioxidant capacity, and 2.1% of the extracts that showed lung cancer cell line-specific cytotoxicity. Data from our profiling experiments indicate that a large number of extracts could be a source for further isolation and chemical identification of compounds that could serve as leads for discovery of antioxidant, anticancer and anti-inflammatory agents to prevent or treat complex diseases like cancer and neurodegenerative disorders

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

Collaborative Innovation in Drug Discovery : Strategies for Public and Private Partnerships

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