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Microsoft powerpoint - big poster.ppt [read-only]
Two Methods for Identifying PDE Inhibitors
Heidi L. Benson, Y. Vivienne Marsh, James F. Blake, John G. Nygaard and Francis X. Sullivan
Back round of
ground of PDEs
br ry Crea
Conduct HTS to identify inhibitors of PDEx using the following two
Phosphodiesterases (PDEs) hydrolyze the second messenger
• Goal is to construct a validation library from the array diversity
molecules cAMP and cGMP to affect a variety of physiological
library that is both representative of each library and diverse for
1.) Virtual HTS of the Validation Library *
processes. Collectively, the literature suggests that discovering
Phosphodiesterases (PDEs) regulate the intracellular levels of
selective inhibitors of the different PDEs may be therapeutically
secondary messengers, cAMP and cGMP, which affects cellular
• Homology modeling
and database docking
method predict which set of
•Selections were made on a plate-by-plate basis. For each
useful. Recently, several selective PDE inhibitors have been
signalling. Eleven families of PDEs have been identified and are
compound, the tanimoto similarity was computed via standard 2D
developed for various medical indications. Homology modeling
classified according to their structure, substrate specificity, tissue
• Conduct HTS on highest scoring libraries
unity fingerprints to every other compound in the diversity library.
and database docking, along with screening subsets of core
expression and their responses to inhibitors. Several PDE
•For each 96-well plate, the average number of nearest neighbors
2.) Physical HTS of the Validation Library
chemical representatives, are predictive methods for focused
inhibitors, such as Viagra (Pfizer), a PDE5 inhibitor for erectile
(within 85% similarity) for each compound was computed on an
screens. These two methods would drive future drug discovery
disfunction, have proven successes in clinical trials and/or are
• Test Validation Library is tested hit rates for complete library
efforts without requiring the of screening of our entire library
already marketed drugs. Other indications for PDE inhibitors
•Plates with the highest inter/intra-plate ratio were chosen. This
(250,000 compounds). We decided to use IMAP™ technology to
include hypertension, congestive heart failure, thrombosis,
• Hit rate calculations select, direct and prioritize additional screening
ratio of nearest neighbors is designed to rank the most
screen for inhibitors against our target PDE to test our theory.
glaucoma, asthma, autoimmune disease and inflammation.
IMAP™ is both a homogeneous and non-radioactive assay
•Nearly 15,000 compounds were chosen to represent the 250,000
Array’s Diversity Library (ADL) contains over 250,000 compounds and
technology. This poster reviews our experience with predictive
is divided into 70 individual libraries according to their core structures.
compounds in Array’s diversity library.
and focused library screens to discover PDE inhibitors.
The Validation Library is a sub-selection of the ADL that contains a representative collection of compounds from each library (~15,000 total).
MP to PDE4
on Flow Cha
IMAPTM (Immobilized Metal Assay for Phosphochemicals) is a non-
•Constructed a homology model of PDEx with Composer, based
radioactive, Fluorescence Polarization, homogeneous assay developed by
on the published coordinates of PDE4B2B (1.77 Å – PDB Code
Molecular Devices. Its proprietary beads are nanoparticles derivatized with
trivalent metal ions that bind to a linear form of phosphates or
•Coordinates for Array Library compounds were generated via
phosphorylated peptides. In the cAMP assay, a low signal is observed when
the substrate (FL-cAMP) cannot bind to the beads. Conversely, a high FP
signal occurs when the product (AMP) binds to the beads.
•Carried out a virtual screen of the Array Validation library with
GOLD (version 2.0) docking program. Compounds that utilized
H-bonds to Gln284 were scored higher. All compounds were
rescored with the Cscore scoring function (Tripos).
•Libraries with the greatest percentage of high scoring compounds
•Final virtual screen highlighted libraries A-J as sources for potential
A recommended reaction assay volume of 20 µL was reduced to 5 µL with minimal signal loss (∆mP of 250 to ~200). Signal was stable for at least 24 hours.
HTS IMAP Assay Condit
S Results of Vir
219 Plates Total:
# Compounds POC Cutoff # HTS Hits HTS Hit Rate
Virtual Library Picks
Full Library HTS Picks
*PDEx Enzyme-partially purified, expressed in Baculovirus, in-house
|---------------- Beckman Coulter FX -----------------|
Beckman Coulter Multimek
Cmpds to 2X
Results from the HTS show that Libraries B and F had the highest hit
rates from the 10 libraries that were chosen from the Virtual Screen.
Plate Num ber
HTS Screen Results
HTS Screen Results
Library Hit Rate
A. In this PDEx screen, we were able to predict and select focused
libraries using the following two methods;
1.)Virtual screening based on homology modeling and database
2.)Validation Library Screening, which involves screening a
representative subset of the diversity library.
B. From the 80,000 compounds selected and screened, each
strategy identified the same highest hit libraries, B and F.
C. Within 1 week of completing HTS, confirmed primary hits
were resynthesized, their activity confirmed, and initial SAR
14 Libraries were chosen for full library HTS due to their hit rates,
interesting structures, and initial SAR observed in the Virtual and the
Validation Library screening methods. Libraries “B” and “F” showed the
highest hit rates in both the Validation screen set and the full library
2012 Originalarbeiten Schwarzl, M; Huber, S; Maechler, H; Steendijk, P; Seiler, S; Truschnig-Wilders, M; Nestelberger, T; Pieske, BM; Post, H, 2012 Left ventricular diastolic dysfunction during acute myocardial infarction: Effect of mild hypothermia. Resuscitation. 2012; 83(12):1503-1510 Prüller, F; Raggam, RB; Posch, V; Almer, G; Truschnig-Wilders, M; Horejsi, R; Möller, R; Weghuber, D;
Guideline on Actinic Keratoses Developed by the Guideline Subcommittee “Actinic Keratoses” of the European Dermatology Forum Subcommittee Members: Prof. Dr. Eggert Stockfleth, Berlin (Germany) Prof. Dr. Lajos Kemény, Szeged (Hungary) Prof. Dr. Bernt Lindelöf, Stockholm (Sweden) Prof. Dr. Lasse Braathen, Bern (Switzerland) Prof. Dr. Martino Neumann, Rotterdam (Netherlands) P