scholarly journals Development of a Novel High-Throughput Screen and Identification of Small-Molecule Inhibitors of the Gα–RGS17 Protein–Protein Interaction Using AlphaScreen

2011 ◽  
Vol 16 (8) ◽  
pp. 869-877 ◽  
Author(s):  
Duncan I. Mackie ◽  
David L. Roman

In this study, the authors used AlphaScreen technology to develop a high-throughput screening method for interrogating small-molecule libraries for inhibitors of the Gαo–RGS17 interaction. RGS17 is implicated in the growth, proliferation, metastasis, and the migration of prostate and lung cancers. RGS17 is upregulated in lung and prostate tumors up to a 13-fold increase over patient-matched normal tissues. Studies show RGS17 knockdown inhibits colony formation and decreases tumorigenesis in nude mice. The screen in this study uses a measurement of the Gαo–RGS17 protein–protein interaction, with an excellent Z score exceeding 0.73, a signal-to-noise ratio >70, and a screening time of 1100 compounds per hour. The authors screened the NCI Diversity Set II and determined 35 initial hits, of which 16 were confirmed after screening against controls. The 16 compounds exhibited IC50 <10 µM in dose–response experiments. Four exhibited IC50 values <6 µM while inhibiting the Gαo–RGS17 interaction >50% when compared to a biotinylated glutathione-S-transferase control. This report describes the first high-throughput screen for RGS17 inhibitors, as well as a novel paradigm adaptable to many other RGS proteins, which are emerging as attractive drug targets for modulating G-protein-coupled receptor signaling.

2011 ◽  
Vol 17 (3) ◽  
pp. 314-326 ◽  
Author(s):  
Xiaohu Tang ◽  
Kathleen I. Seyb ◽  
Mickey Huang ◽  
Eli R. Schuman ◽  
Ping Shi ◽  
...  

Aberrant protein-protein interactions are attractive drug targets in a variety of neurodegenerative diseases due to the common pathology of accumulation of protein aggregates. In amyotrophic lateral sclerosis, mutations in SOD1 cause the formation of aggregates and inclusions that may sequester other proteins and disrupt cellular processes. It has been demonstrated that mutant SOD1, but not wild-type SOD1, interacts with the axonal transport motor dynein and that this interaction contributes to motor neuron cell death, suggesting that disrupting this interaction may be a potential therapeutic target. However, it can be challenging to configure a high-throughput screening (HTS)–compatible assay to detect inhibitors of a protein-protein interaction. Here we describe the development and challenges of an HTS for small-molecule inhibitors of the mutant SOD1-dynein interaction. We demonstrate that the interaction can be formed by coexpressing the A4V mutant SOD1 and dynein intermediate complex in cells and that this interaction can be disrupted by compounds added to the cell lysates. Finally, we show that some of the compounds identified from a pilot screen to inhibit the protein-protein interaction with this method specifically disrupt the interaction between the dynein complex and mtSOD1 but not the dynein complex itself when applied to live cells.


2009 ◽  
Vol 14 (6) ◽  
pp. 610-619 ◽  
Author(s):  
David L. Roman ◽  
Shodai Ota ◽  
Richard R. Neubig

Intracellular signaling cascades are a series of regulated protein-protein interactions that may provide a number of targets for potential drug discovery. Here, the authors examine the interaction of regulators of G-protein signaling (RGS) proteins with the G-protein Gαo, using a flow cytometry protein interaction assay (FCPIA). FCPIA accurately measures nanomolar binding constants of this protein-protein interaction and has been used in high-throughput screening. This report focuses on 5 RGS proteins (4, 6, 7, 8, and 16). To increase the content of screens, the authors assessed high-throughput screening of these RGS proteins in multiplex, by establishing binding constants of each RGS with Gαo in isolation, and then in a multiplex format with 5 RGS proteins present. To use this methodology as a higher-content multiplex protein-protein interaction screen, they established Z-factor values for RGS proteins in multiplex of 0.73 to 0.92, indicating this method is suitable for screening using FCPIA. To increase throughput, they also compressed a set of 8000 compounds by combining 4 compounds in a single assay well. Subsequent deconvolution of the compounds mixtures verified the identification of active compounds at specific RGS targets in their mixtures using the polyplexed FCPIA method. ( Journal of Biomolecular Screening 2009: 610-619)


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jeremy L. Hitt ◽  
Yuguang C. Li ◽  
Songsheng Tao ◽  
Zhifei Yan ◽  
Yue Gao ◽  
...  

AbstractIn the problem of electrochemical CO2 reduction, the discovery of earth-abundant, efficient, and selective catalysts is essential to enabling technology that can contribute to a carbon-neutral energy cycle. In this study, we adapt an optical high throughput screening method to study multi-metallic catalysts for CO2 electroreduction. We demonstrate the utility of the method by constructing catalytic activity maps of different alloyed elements and use X-ray scattering analysis by the atomic pair distribution function (PDF) method to gain insight into the structures of the most active compositions. Among combinations of four elements (Au, Ag, Cu, Zn), Au6Ag2Cu2 and Au4Zn3Cu3 were identified as the most active compositions in their respective ternaries. These ternary electrocatalysts were more active than any binary combination, and a ca. 5-fold increase in current density at potentials of −0.4 to −0.8 V vs. RHE was obtained for the best ternary catalysts relative to Au prepared by the same method. Tafel plots of electrochemical data for CO2 reduction and hydrogen evolution indicate that the ternary catalysts, despite their higher surface area, are poorer catalysts for the hydrogen evolution reaction than pure Au. This results in high Faradaic efficiency for CO2 reduction to CO.


2019 ◽  
Author(s):  
David Armanious ◽  
Jessica Schuster ◽  
George F. Tollefson ◽  
Anthony Agudelo ◽  
Andrew T. DeWan ◽  
...  

AbstractBackgroundData analysis has become crucial in the post genomic era where the accumulation of genomic information is mounting exponentially. Analyzing protein-protein interactions in the context of the interactome is a powerful approach to understanding disease phenotypes.ResultsWe describe Proteinarium, a multi-sample protein-protein interaction network analysis and visualization tool. Proteinarium can be used to analyze data for samples with dichotomous phenotypes, multiple samples from a single phenotype or a single sample. Then, by similarity clustering, the network-based relations of samples are identified and clusters of related samples are presented as a dendrogram. Each branch of the dendrogram is built based on network similarities of the samples. The protein-protein interaction networks can be analyzed and visualized on any branch of the dendrogram. Proteinarium’s input can be derived from transcriptome analysis, whole exome sequencing data or any high-throughput screening approach. Its strength lies in use of gene lists for each sample as a distinct input which are further analyzed through protein interaction analyses. Proteinarium output includes the gene lists of visualized networks and PPI interaction files where users can analyze the network(s) on other platforms such as Cytoscape. In addition, since the dendrogram is written in Newick tree format, users can visualize it in other software platforms like Dendroscope, ITOL.ConclusionsProteinarium, through the analysis and visualization of PPI networks, allows researchers to make important observations on high throughput data for a variety of research questions. Proteinarium identifies significant clusters of patients based on their shared network similarity for the disease of interest and the associated genes. Proteinarium is a command-line tool written in Java with no external dependencies and it is freely available at https://github.com/Armanious/Proteinarium.


2016 ◽  
Vol 12 (4) ◽  
pp. 1378-1387 ◽  
Author(s):  
Meng-Chen Lu ◽  
Zhen-Wei Yuan ◽  
Yong-Lin Jiang ◽  
Zhi-Yun Chen ◽  
Qi-Dong You ◽  
...  

Protein–protein interactions (PPIs) as drug targets have been gaining growing interest, though developing drug-like small molecule PPI inhibitors remains challenging.


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