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BioAssay: AID 588775

Dose response for HTS for Beta-2AR agonists via FAP method from Powderset1

Chemistry Center/ PI: Vanderbilt Specialty Chemistry Center/Craig Lindsley Chemistry Center Lead: Shaun Stauffer ..more
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 Tested Compounds
 Tested Compounds
All(20)
 
 
Active(20)
 
 
 Tested Substances
 Tested Substances
All(20)
 
 
Active(20)
 
 
AID: 588775
Data Source: NMMLSC (UNMCMD_BA_DOSERESPONSE_POWDERSET1)
BioAssay Type: Confirmatory, Concentration-Response Relationship Observed
Depositor Category: NIH Molecular Libraries Probe Production Network
BioAssay Version:
Deposit Date: 2011-11-04
Modify Date: 2013-03-04

Data Table ( Complete ):           Active    All
Target
BioActive Compounds: 20
Depositor Specified Assays
AIDNameTypeComment
492947qHTS assay of beta-arrestin-biased ligands of beta2-adrenergic receptorconfirmatoryqHTS assay of beta-arrestin-biased ligands of beta2-adrenergic receptor
485366qHTS validation assay of beta-arrestin-biased ligands of beta2-adrenergic receptorconfirmatoryqHTS validation assay of beta-arrestin-biased ligands of beta2-adrenergic receptor
504448Summary of HTS for Non-Canonical Ligands for Beta 2 Adrenergic Receptor InternalizationsummarySummary of HTS for Non-Canonical Ligands for Beta 2 Adrenergic Receptor Internalization
651701Summary of HTS Screening Project for Inhibitors of fluorogen-FAP tag interactionssummary
Description:
University of New Mexico Assay Overview:
Assay Support: R03 MH093192-01
Project Title: HTS for Non-Canonical Ligands for Beta 2 Adrenergic Receptor Internalization
Assay Provider: Jonathan Jarvik, Carnegie Mellon University
Screening Center/ PI: UNMCMD/ Larry Sklar
Lead Biologist: Yang Wu
Chemistry Center/ PI: Vanderbilt Specialty Chemistry Center/Craig Lindsley Chemistry Center Lead: Shaun Stauffer
Assay Implementation: Yang Wu, Phillip Tapia, Terry Foutz, Stephanie Chavez, Dominique Perez, Annette Evangelisti, Anna Waller, Cristian Bologa, Mark Carter

Assay Background and Significance:

G protein-coupled receptors represent the largest family of proteins in the human genome with an estimated number of approximately 800. Because of their central involvement in almost every aspect of human physiology, they also represent the largest target for medical intervention [Lin and Civelli, Annu Med 36 (2004), 204-14]. Today, GPCRs represent the target of approximately 30-40% of all drugs on the market. Indeed, of the 50 top-selling drugs in the United States in 2007, 18 target GPCRs, with combined sales of approximately 25 billion dollars.

Of about 800 GPCRs, 500 are chemosensory, representing the chemokine/chemoattractant GPCRs, and the olfactory and gustatory GPCRs. Although the former have been thoroughly characterized for the most part, members of the latter, particularly the olfactory receptors which may include the important category of pheromones, have had only a small number of ligands identified. The remaining GPCRs, approximately 360, constitute the transmitter GPCRs. Of these, approximately 100 receptors still have no known ligand. Such receptors with no known physiological ligand are referred to as orphan receptors and arose from cloning strategies based on limited homology within almost all GPCRs (predominantly during the 1990's) as well as the sequencing of the human genome (in 2000) [Chung et al, Br J Pharmacol 153 Suppl 1 (2008), S339-46].

The search for endogenous ligands for orphan GPCRs has been challenging. This process has given rise to the field of reverse pharmacology, which uses orphan GPCRs to identify novel ligands, which together often lead to the characterization of new physiological paradigms. Over the last 20 years, this approach has led to the deorphanization of about 300 GPCRs. Many of the ligands were already known and their biology characterized, but their receptor was unknown. But in some of these instances, this process also led to the identification of novel transmitters [Civelli et al., Pharmacol Ther 110 (2006), 525-32].

During the 1990's, approximately 10 GPCRs were deorphanized per year. However, very few have been deorphanized since 2004. In addition, no novel transmitters have been identified since that time [Chung et al, Br J Pharmacol 153 Suppl 1 (2008), S339-46]. Given these facts, the question arises as to whether the remaining orphan GPCRs will be readily deorphanized. One major issue is that the pool of known transmitters for which no receptor is known has been essentially depleted. Since all the possible transmitters have now been matched to GPCRs, the current orphan GPCRs can only bind unknown ligands, for which the identification is also slow and resource intense. This is particularly true given that the concentrations of many transmitters in vivo is exceedingly low, making their identification difficult. It is also possible that the expression of some ligands may be developmentally or environmentally regulated.

Almost all current reverse pharmacological/screening approaches rely on monitoring second messenger levels such as calcium mobilization, cAMP production and transcriptional activation. Thus, successful screening requires knowledge of the pathway for a given receptor, in particular the G protein to which the receptor couples. As the number of heterotrimeric G protein combinations is large, this is not a trivial task.

An alternate approach to measuring signal transduction is the monitoring receptor internalization. Virtually all known GPCRs undergo activation-dependent internalization as a mechanism to reduce cell surface receptor numbers. Internalization does not require G protein coupling. Instead, the activity of one of four G protein receptor kinases (GRKs) is required. In most instances, the binding of an accessory protein, arrestin, is also required. One screening approach that has been developed is the recruitment of GFP-tagged arrestin to either the plasma membrane or intracellular endosomes.

The beta-Arrestin clustering assay, developed by Norak Technologies, requires high resolution imaging, well spread, adherent cells, and extensive image analysis to determine the response to a treatment. Other methods, such a receptor desensitization measurements on non-permeabilized cells rely on measurement of subtle changes in intensity. As described below, the CMU TCNP is developing sensors for GPCR responses that are readily compatible with HTS flow cytometry and multiplexing when the GPCRs are expressed in suspension cell lines.
Protocol
1. Spin down AM2.2-beta2AR cells, discard supernatant, and resuspend in fresh RPMI1640 full medium. Final cell density will be 5x106 cells/mL.
2. Add 5muL serum free RPMI to the assay plate except for columns 11 and 23 by Microflow
3. Add 5 microL of freshly prepared 20 microM ISO in RPMI full media to Column 11 and 23 of all the plates as PCntrls by Microflow
4. Add 100 nanoL of library compounds between 15 nanoM and 33 microM (final concentration) to assay plates by FX.
5. Add 3muL of cells to Columns 1 - 11, 13-23 of the assay plates by Microflow.
6. Shake the plates and put them in 37C incubator for 90mins.
7. Add 3muL 650 nanoM TO1-2p to assay plates by Microflow or Nanoquot to assay plates and read by high-throughput flow cytometers immediately.

Calculation:
IF PUBCHEM_ACTIVITY_SCORE < 50 then PUBCHEM_ACTIVITY_OUTCOME = 1 (or inactive)

IF PUBCHEM_ACTIVITY_SCORE >= 50 then PUBCHEM_ACTIVITY_OUTCOME = 2 (or active)
Result Definitions
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TIDNameDescriptionHistogramTypeUnit
OutcomeThe BioAssay activity outcomeOutcome
ScoreThe BioAssay activity ranking scoreInteger
1ACTIVITY_QUALIFIERQualifier for the value of EC50String
2EC50_MICROM*Effective concentration of half maximal event count as estimated by curve fitFloatμM
3EC50_95CI_LOWLower 95% confidence interval boundary for the EC50 curve fit estimateFloatμM
4EC50_95CI_HIGHUpper 95% confidence interval boundary for the EC50 curve fit estimateFloatμM
5BOTTOMResponse value at the bottom plateauFloat%
6TOPResponse value at the top plateauFloat%
7HILLSLOPEHill slope estimate for the fitted dose response curveFloat
8STD_BOTTOMStandard error for the response value at the bottom plateauFloat%
9STD_TOPStandard error for the response value at the top plateauFloat%
10STD_HILLSLOPEStandard error for the HILL SLOPEFloat
11PERCENT_SPANSpan of dose response fitted Top minus BottomFloat%
12RSQRCorrelation coefficient for the fitted dose response curveFloat
13N_POINTSNumber of data points for each dose response curveInteger
14RESPONSE_0.002_MICROM (0.002μM**)Percent Response with 0.002 micromolar concentration of test compoundFloat%
15RESPONSE_0.005_MICROM (0.005μM**)Percent Response with 0.005 micromolar concentration of test compoundFloat%
16RESPONSE_0.015_MICROM (0.015μM**)Percent Response with 0.015 micromolar concentration of test compoundFloat%
17RESPONSE_0.045_MICROM (0.045μM**)Percent Response with 0.045 micromolar concentration of test compoundFloat%
18RESPONSE_0.136_MICROM (0.136μM**)Percent Response with 0.136 micromolar concentration of test compoundFloat%
19RESPONSE_0.407_MICROM (0.407μM**)Percent Response with 0.407 micromolar concentration of test compoundFloat%
20RESPONSE_1.222_MICROM (1.222μM**)Percent Response with 1.222 micromolar concentration of test compoundFloat%
21RESPONSE_3.667_MICROM (3.667μM**)Percent Response with 3.667 micromolar concentration of test compoundFloat%
22RESPONSE_11.0_MICROM (11μM**)Percent Response with 11.0 micromolar concentration of test compoundFloat%
23RESPONSE_33.0_MICROM (33μM**)Percent Response with 33.0 micromolar concentration of test compoundFloat%

* Activity Concentration. ** Test Concentration.
Additional Information
Grant Number: R03 MH093192-01

Data Table (Concise)
Classification
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