The major components of the cartilage extracellular matrix are type II collagen and aggrecan. Matrix metalloproteinase 13 (MMP-13) has been implicated as the protease responsible for collagen degradation in cartilage during osteoarthritis (OA). In the present study, a triple-helical FRET substrate has been utilized for high throughput screening (HTS) of MMP-13 with the MLSCN compound library (n approximately 65,000). Thirty-four compounds from the HTS produced pharmacological dose-response curves. A secondary screen using RP-HPLC validated 25 compounds as MMP-13 inhibitors. Twelve of these compounds were selected for counter-screening with 6 representative MMP family members. Five compounds were found to be broad-spectrum MMP inhibitors, 3 inhibited MMP-13 and one other MMP, and 4 were selective for MMP-13. One of the selective inhibitors was more active against MMP-13 triple-helical peptidase activity compared with single-stranded peptidase activity. Since the THP FRET substrate has distinct conformational features that may interact with MMP secondary binding sites (exosites), novel non-active site-binding inhibitors may be identified via HTS protocols utilizing such assays.
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019 has triggered an ongoing global pandemic whereby infection may result in a lethal severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19). To date, millions of confirmed cases and hundreds of thousands of deaths have been reported worldwide, and there are currently no medical countermeasures available to prevent or treat the disease. The purported development of a vaccine could require at least 1–4 years, while the typical timeline from hit finding to drug registration of an antiviral is >10 years. Thus, repositioning of known drugs can significantly accelerate the development and deployment of therapies for COVID-19. To identify therapeutics that can be repurposed as SARS-CoV-2 antivirals, we developed and initiated a high-throughput cell-based screen that incorporates the essential viral papain-like protease (PLpro) and its peptide cleavage site into a luciferase complementation assay to evaluate the efficacy of known drugs encompassing approximately 15,000 clinical-stage or US Food and Drug Administration (FDA)-approved small molecules. Confirmed inhibitors were also tested to determine their cytotoxic properties. Here, we report the identification of four clinically relevant drugs that exhibit selective inhibition of the SARS-CoV-2 viral PLpro.
Affordable and physiologically relevant three-dimensional (3D) cell-based assays used in high-throughput screening (HTS) are on the rise in early drug discovery. These technologies have been aided by the recent adaptation of novel microplate treatments and spheroid culturing techniques. One such technology involves the use of nanoparticle (NanoShuttle-PL) labeled cells and custom magnetic drives to assist in cell aggregation to ensure rapid 3D structure formation after the cells have been dispensed into microtiter plates. Transitioning this technology from a low-throughput manual benchtop application, as previously published by our lab, into a robotically enabled format achieves orders of magnitude greater throughput but required the development of specialized support hardware. This effort included in-house development, fabrication, and testing of ancillary devices that assist robotic handing and high-precision placement of microtiter plates into an incubator embedded with magnetic drives. Utilizing a “rapid prototyping” approach facilitated by cloud-based computer-aided design software, we built the necessary components using hobby-grade 3D printers with turnaround times that rival those of traditional manufacturing/development practices at a substantially reduced cost. This approach culminated in a first-in-class HTS-compatible 3D system in which we have coupled 3D bioprinting to a fully automated HTS robotic platform utilizing our novel magnetic incubator shelf assemblies.
There is a pressing need to improve approaches for drug discovery related to neuropsychiatric disorders (NSDs). Therapeutic discovery in neuropsychiatric disorders would benefit from screening assays that can measure changes in complex phenotypes linked to disease mechanisms. However, traditional assays that track complex neuronal phenotypes, such as neuronal connectivity, exhibit poor scalability and are not compatible with high-throughput screening (HTS) procedures. Therefore, we created a neuronal phenotypic assay platform that focused on improving the scalability and affordability of neuron-based assays capable of tracking disease-relevant phenotypes. First, using inexpensive laboratory-level automation, we industrialized primary neuronal culture production, which enabled the creation of scalable assays within functioning neural networks. We then developed a panel of phenotypic assays based on culturing of primary neurons from genetically modified mice expressing HTS-compatible reporters that capture disease-relevant phenotypes. We demonstrated that a library of 1,280 compounds was quickly screened against both assays using only a few litters of mice in a typical academic laboratory setting. Finally, we implemented one assay in a fully automated high-throughput academic screening facility, illustrating the scalability of assays designed using this platform. These methodological improvements simplify the creation of highly scalable neuron-based phenotypic assays designed to improve drug discovery in CNS disorders.
Kinases are important drug discovery targets for a wide variety of therapeutic indications; consequently, the measurement of kinase activity remains a common high-throughput screening (HTS) application. Recently, enzyme-coupled luciferase-kinase (LK) format assays have been introduced. This format measures luminescence resulting from metabolism of adenosine triphosphate (ATP) via a luciferin/luciferase-coupled reaction. In the research presented here, 1536-well format time-resolved fluorescence resonance energy transfer (TR-FRET) and LK assays were created to identify novel Rho-associated kinase II (ROCK-II) inhibitors. HTS campaigns for both assays were conducted in this miniaturized format. It was found that both assays were able to consistently reproduce the expected pharmacology of inhibitors known to be specific to ROCK-II (fasudil IC50: 283 ± 27 nM and 336 ± 54 nM for TR-FRET and LK assays, respectively; Y-27632 IC50: 133 ± 7.8 nM and 150 ± 22 nM for TR-FRET and LK assays, respectively). In addition, both assays proved robust for HTS efforts, demonstrating excellent plate Z′ values during the HTS campaign (0.84 ± 0.03; 0.72 ± 0.05 for LK and TR-FRET campaigns, respectively). Both formats identified scaffolds of known and novel ROCK-II inhibitors with similar sensitivity. A comparison of the performance of these 2 assay formats in an HTS campaign was enabled by the existence of a subset of 25,000 compounds found in both our institutional and the Molecular Library Screening Center Network screening files. Analysis of the HTS campaign results based on this subset of common compounds showed that both formats had comparable total hit rates, hit distributions, amount of hit clusters, and format-specific artifact. It can be concluded that both assay formats are suitable for the discovery of ROCK-II inhibitors, and the choice of assay format depends on reagents and/or screening technology available. ( Journal of Biomolecular Screening 2008:17-28)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.