MLPCN Platelet Activation -Dense Granule Release
Keywords: Platelet, activation, granule, secretion, arterial thrombosis, PAR1, SFLLRN, thrombin receptor ..more
BioActive Compounds: 661
Broad Institute MLPCN Platelet Activation Project
Project ID: 2016
Keywords: Platelet, activation, granule, secretion, arterial thrombosis, PAR1, SFLLRN, thrombin receptor
Robert Flaumenhaft, Beth Israel Deaconess Medical Center, firstname.lastname@example.org
John Thomas, NHLBI, ThomasJ@nhlbi.nih.gov
The goal of this project is to identify small molecules that inhibit the activation of platelets by measuring the secretion of ATP-rich dense granules. The aim is to identify inhibitory compounds that act on the diverse mechanisms responsible for platelet activation. Probes demonstrating the specific ability to inhibit platelet activation will be further evaluated as potential antithrombic agents. Those potential probes will fall into the 3 attribute classes in order of priority:
1. Small molecule probes that are dense granule specific (Class 1)
2. Small molecule probes that are granule specific (Class 2)
3. Inhibitors of specific receptors or specific sets of receptors indicating MOA through certain G proteins or adapter proteins (Class 3)
Assay: Dense granule release of platelet-rich plasma (PRP). Expired units of PRP obtained from various blood centers were plated in 384-well white assay plates (Aurora, 00030721) on average of 15,600,000 platelets/well in 20ul. PRP was exposed to 7.5uM compounds from the MLPCN collection or various doses of the positive control, Cilostazol (Sigma #C0737, Lot# 042K4704, BRD-K67017579-001-04-2 ) for 30 minutes prior to addition of the thrombin receptor (Par1) activator SFLLRN (5uM, Bachem, H-8365) and detection reagent CellTiter-Glo (Promega, G755) using a modified protocol, for measurement of ATP released from the dense granules. PBS is used in place of CellTiter-Glo Buffer thus preventing platelet lysis and a high background of ATP. Luminescence measurements are taken 15 minutes after reagent addition.
Outcome: A decrease in the luminescent signal will identify compounds that either inhibit the release of dense granules from the platelets, or inhibit the luciferase enzyme. Normalization of the HTS data across runs and calibration to the positive was performed as described below. The results are reported as % inhibition. Specificity for platelet inhibition will be determined in a secondary assay.
Taken from 2016-01-A01-01 through 2016-01-A01-11
1) Plasma bag(s) from a single donor were emptied into a sterile bottle (250 or 500ml, depending on volume of plasma) in a hood. If multiple bags exist from a single donor (matching barcodes), they were combined as to increase batch volume. Multiple donors' samples could not be pooled due to possible immunological reactions, therefore multiple batches were run daily with each being prepared singly. All information provided on each unit used was recorded (source, donor number,blood type, etc.).
2) Samples were taken to count the number of platelets/ml and checked for activation activity by addition of SFLLRN and CellTiter-Glo.
3) The Thermo MultiDrop Combi in the hood was prepared for dispensing 20ul of plasma per well. As many plates allowable with volume of plasma were filled from a single donor. Batch size ranged from 200ml-700ml. While filling, platelets were kept in homogeneous suspension by gentle agitation.
4) Assay plates were loaded into racks for placement into a Liconic STR240 HRIT incubator set at 30'C, 95% humidity, 5% CO2. The incubator is docked to the screening system. Compound plates have their foil seals pierced off-line. Those plates are loaded into a Liconic STR240 DRIT incubator set to 22'C, 15% humidity.
5) CellTiter-Glo/SFLLRN was prepared for each day to a volume to accommodate the number of assay plates estimated for the day. The CellTiter-Glo Substrate was previously resuspended in 100ml PBS, aliquoted and frozen. An aliquot was thawed and diluted 1:4 with PBS. SFLLRN was previously resuspended in a stocks of 10mM and frozen. An aliquot was thawed and was added to the mixture at 15#M. The Combi on the screening system was prepared for run and primed with the reagent.
6) Screening was performed on an enclosed, contained screening system. The run was initiated by set-up in CBIP (Broad Chemical Biology Informatics Platform) and scheduled with Cellario (HighRes Biosolutions). Staubli arms moved plates from the different instruments on the system. Compounds were pinned into assay plates using a MicroPin (High Res Biosolutions) using a 25nl head calibrated to deliver 50nl.
7) Assay plates were returned to the incubator for a 30 min. incubation.
7) At the completion of incubation, plates moved to the Combi for addition of 10ul CellTiter-Glo/SFLLRN solution per well.
8) Plates were moved to a plate hotel on deck for a 15 min. incubation.
9) At completion of incubation, plates were moved to an Envision 2104 Multilabel Reader (Perkin Elmer) for luminescence detection. The ultra sensitive detection was used, with the 1536 aperture in place, to decrease bleed-through from adjacent wells. Read time is 0.1s/well.
This assay belongs to specific project (2016, MLPCN Platelet Activation) at the Broad Institute of MIT and Harvard
HTS Data Analysis:
Negative control wells (DMSO) were included on every plate.
Two plates containing the positive control at various doses were included in every assay run.
The PubChem_Activity_Score was derived using the follow procedure:
1. Negative controls: The median value of the negative control wells was calculated for each plate.
2. Positive controls: In this screen, some of the positive control plates failed due to automation errors while the compound plates from the same runs did not. In runs where the positive control plates did not fail, the data value at maximum inhibition was consistently 4% of the value of the negative controls. In order to provide a consistent calibration for all runs, we defined the positive control value for each run to be 4% of the median value of the negative control wells in that run.
3. A background-subtracted value was calculated for each well by subtracting the median value of the negative control wells on each plate (from step 1) from the value of each well on that plate.
4. Systematic plate effects were corrected for each run. A plate effect correction matrix was derived by calculating the median value of all non-positive-control wells for each well location (e.g. C07) across all the plates in a run. This correction matrix was then smoothed using an inverse-distance weighted median filter and subtracted from all the plates in the same run resulting in a background-subtracted, plate-effect-corrected value for each well.
5. A background-subtracted positive control value was calculated for each run by subtracting the median value of the negative control wells in that run from the positive control value calculated earlier (step 2). An activity score was derived for each well by dividing the background subtracted, plate effect corrected value (step 4) by the background-subtracted positive control value and multiplying the resulting fraction by 100.
5. The final PubChem_Activity_Score represents the mean of all valid replicate activity scores obtained. Range of -189 to 182.
The PubChem_Activity_Outcome class was assigned as described below:
Activity_Outcome = 1 (inactive)
PubChem_Activity_Score <50 and all replicate activity scores <50.
Activity_Outcome = 2 (active)
PubChem_Activity_Score >=50. Using this cutoff, the PubChem_Activity_Score for the active compounds is greater than the 99.93 percentile of the PubChem_Activity_Outcomeof the negative controls.
Activity_Outcome = 3 (inconclusive)
PubChem_Activity_Score < 50 with at least one replicate activity score >=50.
Activity_Outcome = 4
Data Table (Concise)