scholarly journals Polyplexed Flow Cytometry Protein Interaction Assay: A Novel High-Throughput Screening Paradigm for RGS Protein Inhibitors

2009 ◽  
Vol 14 (6) ◽  
pp. 610-619 ◽  
Author(s):  
David L. Roman ◽  
Shodai Ota ◽  
Richard R. Neubig
Keyword(s):  
Flow Cytometry ◽  
G Protein ◽  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Intracellular Signaling ◽  
High Throughput Screening ◽  
Binding Constants ◽  
Rgs Proteins ◽  
Protein Protein Interaction

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)

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
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interaction ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Screening Method ◽  
Fold Increase ◽  
Rgs Proteins ◽  
High Throughput Screen ◽  
Protein Protein Interaction

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.

scholarly journals Proteinarium: Multi-Sample Protein-Protein Interaction Analysis and Visualization Tool

2019 ◽  
Author(s):  
David Armanious ◽  
Jessica Schuster ◽  
George F. Tollefson ◽  
Anthony Agudelo ◽  
Andrew T. DeWan ◽  
...  
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
High Throughput Screening ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Visualization Tool ◽  
Sequencing Data ◽  
Protein Protein Interaction ◽  
Ppi Networks

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.

scholarly journals Combining Unique Multiplex Gateway Cloning and Bimolecular Fluorescence Complementation (BiFC) for High-Throughput Screening of Protein–Protein Interactions

2016 ◽  
Vol 21 (10) ◽  
pp. 1100-1111 ◽  
Author(s):  
Adriana Lepur ◽  
Lucija Kovačević ◽  
Robert Belužić ◽  
Oliver Vugrek
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
High Throughput Screening ◽  
Cellular Localization ◽  
Interaction Analysis ◽  
Bimolecular Fluorescence Complementation ◽  
Galectin 3 ◽  
Fluorescence Complementation ◽  
Bimolecular Fluorescence

Protein interaction networks are the basis for human metabolic and signaling systems. Interaction studies often use bimolecular fluorescence complementation (BiFC) to reveal the formation and cellular localization of protein complexes. However, large-scale studies were either far from native conditions in human cells or limited by laborious restriction/ligation cloning techniques. Here, we describe a new tool for protein interaction screening based on Gateway-compatible BiFC vectors. We made a set of four new vectors that permit fusion of candidate proteins to the N or C fragment of Venus in all fusion positions. We have validated the vectors and confirmed self-association of AHCY, AHCYL1, and galectin-3. In a high-throughput BiFC screen, we identified new AHCY interaction partners: galectin-3 and PUS7L. We also describe additional steps in protein interaction analysis, applied for AHCY–galectin-3 interaction. First, we classified the interaction in intracellular vesicles using CellCognition, machine learning free software. Then we identified the vesicles as endosomal pathway compartments, in line with known galectin-3 trafficking route. This offers a platform to rapidly identify and localize new protein interactions inside living cells, a prerequisite to validate in silico interactome data, and ultimately decode complex protein networks.

scholarly journals A High-Throughput Screening Method for Small-Molecule Inhibitors of the Aberrant Mutant SOD1 and Dynein Complex Interaction

2011 ◽  
Vol 17 (3) ◽  
pp. 314-326 ◽  
Author(s):  
Xiaohu Tang ◽  
Kathleen I. Seyb ◽  
Mickey Huang ◽  
Eli R. Schuman ◽  
Ping Shi ◽  
...  
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interaction ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Small Molecule Inhibitors ◽  
Screening Method ◽  
Live Cells ◽  
Mutant Sod1 ◽  
Protein Protein Interaction

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.

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