The Application of DiverseSolutions (DVS) in the Establishment and Validation of a Target Class-Directed Chemistry Space
Eugene L. Stewart*, Peter J. Brown†, James A. Bentley§,Timothy M. Willson‡
*Computational and Structural Sciences, †Metabolic Center of Excellence for Drug Discovery,‡Discovery Medicinal Chemistry§Molecular Discovery Research Information TechnologyGlaxoSmithKline, Five Moore Drive, Research Triangle Park, NC, 27709
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors
– The Process of NR Descriptor and Compound Selection Using Those Descriptors
Descriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs
– Use of an NR descriptor space in the determination of the druggability of the NR super-family
– Results and Conclusions
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors– The Process of NR Descriptor and Compound
Selection Using Those DescriptorsDescriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs
– Use of an NR descriptor space in the determination of the druggability of the NR super-family
– Results and Conclusions
Nuclear Receptor Signaling
NucleusCytoplasm
dihydrotestosterone
estradiol
progesterone
aldosteronecortisol
calcitriol
thyroid hormone
retinoic acid
HO OH
OHO
O
OHO
O
OHO
H
O
O
H
OH
OHH
OH
HO
H
O
CO2HHO I
II
NH2
OHHO
H OH
CO2H
NuclearReceptor
“Classical” Steroid Receptors “Orphan” Receptors
GR corticosteroneMR aldosteronePR progesteroneAR DHTER() estradiolTR triiodothyronineRAR() retinoic acidVDR 1,25-(OH)2-D3
EcR ecdysone
RXR (,) 9-cis retinoic acidPPAR (,) fatty acidsLXR (,) oxysterolsFXR bile acidsSF1 (,) oxysterols CAR androstanesROR (,) cholesterolRevErb (,) hemeHNF4 (,) —NGFIB (,) —PNR —TR2 (,) —COUP (,) —Tlx —ERR (,) —
CN DNADNA LigandLigand
Nuclear Hormone Receptors (NRs)
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors
– The Process of NR Descriptor and Compound Selection Using Those Descriptors
Descriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs
– Use of an NR descriptor space in the determination of the druggability of the NR super-family
– Results and Conclusions
Methodology for Descriptor Analysis
Training Setfor Target
Class
Calculate PossibleDescriptors for
Training Set
Form DescriptorSpace for Target Class
Is Library VirtualCombinatorial
Library?
NoIs CompoundActive for
Target?Biological Screening
Yes
Eliminate Compound
No
Virtual Library1) Combinatorial2) Cmpds to be Acquired
Existing Library1) Corporate2) Other
Virtual Screening:1) Nearest Neighbor Analysis2) Activity-seeded Cluster Analysis
CompoundsRepresentative of
Target Class Ligands
Yes
Biased TargetedArray Selection
Synthesize BiasedLibrary
Theory of Targeted Compound Selection
Universe of Compounds(Virtual or Real)
Universe of Compounds(Virtual or Real)
Target Ligands
Target Receptor Ligands
Chemistries/Compound Collections
Chemistries/Compound Collections
Set of Quality TargetLigand Descriptors
Training Set ofTarget Ligands
Drug-like Molecules(WDI or MDDR)
Drug-like Molecules(WDI or MDDR)
Training Set ofTarget Ligands
Reality of Targeted Compound Selection
“Classical” Steroid Receptors “Orphan” Receptors
GR corticosteroneMR aldosteronePR progesteroneAR DHTER() estradiolTR triiodothyronineRAR() retinoic acidVDR 1,25-(OH)2-D3
EcR ecdysone
RXR (,) 9-cis retinoic acidPPAR (,) fatty acidsLXR (,) oxysterolsFXR bile acidsSF1 (,) oxysterols CAR androstanes ROR (,) cholesterolRevErb (,) hemeHNF4 (,) —NGFIB (,) —PNR —TR2 (,) —COUP (,) —Tlx —ERR (,) —
907 knownNR ligandsfrom WDI
CN DNADNA LigandLigand
Nuclear Hormone Receptors (NRs)
Targeted Descriptor Selection for NRs
NR900(907 cmpds)
WDI(42,608 cmpds)
WDI(42,608 cmpds)
NR900(907 cmpds)
DiverseSolutions (DVS)
Apply Basis Setof Descriptors
52 Standard 2D and3D BCUT Metrics
SAVOL MolecularVolume
5 Descriptors measure:1) Charge2) Polarizability3) Molecular Shape & Size
Select Descriptors for aDescriptor Space such that:1) Maximize dimensionality2) Minimize axes correlation3) Separate WDI and NR900
DiverseSolutions selected the following descriptors as axes to define 5D NR descriptor space:
BCUT: diagonal = Gasteiger-Huckel chargesoff-diagonal = inverse atomic distance
BCUT: diagonal = H-bond donor abilityoff-diagonal = Burden’s numbers
BCUT: diagonal = tabulated polarizabilitiesoff-diagonal = Burden’s numbers
BCUT: diagonal = tabulated polarizabilitiesoff-diagonal = inverse atomic distance
SAVOL molecular volume
NR Descriptor Selection
World Drug IndexNR900
Normalized BCUT lowest eignevalueDiagonal: Gasteiger-Huckel ChargesOff-diagonal: inverse distance
Nor
mal
ized
SA
VO
LM
olec
ular
Vol
ume
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors
– The Process of NR Descriptor and Compound Selection Using Those Descriptors
Descriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs
– Use of an NR descriptor space in the determination of the druggability of the NR super-family
– Results and Conclusions
Methodology for Descriptor Analysis
Training Setfor Target
Class
Calculate PossibleDescriptors for
Training Set
Form DescriptorSpace for Target Class
Is Library VirtualCombinatorial
Library?
NoIs CompoundActive for
Target?Biological Screening
Yes
Eliminate Compound
No
Virtual Library1) Combinatorial2) Cmpds to be Acquired
Existing Library1) Corporate2) Other
Virtual Screening:1) Nearest Neighbor Analysis2) Activity-seeded Cluster Analysis
CompoundsRepresentative of
Target Class Ligands
Yes
Biased TargetedArray Selection
Synthesize BiasedLibrary
Virtual Screening with NR Descriptor Space
VirtualScreen
Descriptor A
Des
crip
tor
B
Descriptor A
Des
crip
tor
B
CompoundDatabase
Calculate NR Descriptorsand Apply Descriptor Space Select Compounds
This database could be:• Corporate collection• Virtual libraries• Compounds to be purchased
The virtual screen may consist of oneof the following:• A nearest neighbor analysis• A set of clusters defined by the training set
Locate database compounds in theneighborhood of the training setcompounds
Biological ScreenBiological screening of the selectedcompounds has two purposes:• Find progressable hits to be followed up through chemistry• Gain more knowledge about the characteristics of NR ligands
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors
– The Process of NR Descriptor and Compound Selection Using Those Descriptors
Descriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs– Use of an NR descriptor space in the determination
of the druggability of the NR super-family
– Results and Conclusions
Methodology for Descriptor Analysis
Training Setfor Target
Class
Calculate PossibleDescriptors for
Training Set
Form DescriptorSpace for Target Class
Is Library VirtualCombinatorial
Library?
NoIs CompoundActive for
Target?Biological Screening
Yes
Eliminate Compound
No
Virtual Library1) Combinatorial2) Cmpds to be Acquired
Existing Library1) Corporate2) Other
Virtual Screening:1) Nearest Neighbor Analysis2) Activity-seeded Cluster Analysis
CompoundsRepresentative of
Target Class Ligands
Yes
Biased TargetedArray Selection
Synthesize BiasedLibrary
Question: How do we test this strategy?
Answer: Compare the results of screening our NR targeted sets with a random or diverse set of compounds– Selected a NR targeted set using NR descriptors
8,000 compound selected from GSK liquid collection
– Selected a representative, diverse set24,000 compounds selected as a diverse set of solids and liquids from all GSK sites
11% of this set is contained in NR Space
Targeted Screening Validation
Screened both the diverse and targeted set against a panel of 6 orphan NR assays
Compared curve data for diverse vs targeted compounds
Considered only those compounds with a pEC50 > 6.0 as hits
Only two screens generated curve data that was comparable under this criteria for both sets
Targeted Screening Validation
Comparative Screening Results
Two receptors yielded hits from both sets which enabled a comparison of hit rates
Methodology for Descriptor Analysis
Training Setfor Target
Class
Calculate PossibleDescriptors for
Training Set
Form DescriptorSpace for Target Class
Is Library VirtualCombinatorial
Library?
NoIs CompoundActive for
Target?Biological Screening
Yes
Eliminate Compound
No
Virtual Library1) Combinatorial2) Cmpds to be Acquired
Existing Library1) Corporate2) Other
Virtual Screening:1) Nearest Neighbor Analysis2) Activity-seeded Cluster Analysis
CompoundsRepresentative of
Target Class Ligands
Yes
Biased TargetedArray Selection
Synthesize BiasedLibrary
Results and Conclusions– By utilizing a targeted approach to library design and
compound selection, we have improved our hit rates in orphan NR assays by 2-fold over random or diverse compound selection
– NR targeted collections that are in the range of 40 - 60% effective give good coverage of an NR descriptor space while still exploring “uncharted” regions of that space
– Screening compound collections with better coverage of NR descriptor space results in improved hit rates
A Set of Descriptors for NR Ligands
A Set of Descriptors for NR Ligands
Topics– An Introduction to Nuclear Receptors (NR) as a
System of Receptors
– The Process of NR Descriptor and Compound Selection Using Those Descriptors
Descriptor Selection
Selection of NR Targeted Compound Collections
– Validation of Descriptors for NRs
– Use of an NR descriptor space in the determination of the druggability of the NR super-family
– Results and Conclusions
Druggability of The Nuclear Receptome
How many of the remaining orphan receptors are chemically tractable?
Data from GSK ligand screening experiment– 16 orphan receptors
– 10,000 compounds
– Cell-based assay
– LBD-Gal4 chimera format
10K NR Probe Set
Selected using molecular descriptors derived from known NR chemotypes– Analyzed >23,000 public and proprietary NR ligands– Activity-seeded clusters to maximize chemical diversity – Set composed of 5000 externally purchased compounds and
5000 GSK proprietary compounds– Low overlap with GSK screening collection (1.5 million
compounds)
Multiple hits identified on control receptors– PPAR – LXR
Receptor Screens
Selected 16 orphan NRs not previously screened at GSK in cells– COUP-TF1, COUP-TF2, COUP-TF3, DAX, GCNF, PNR, LRH1,
RevErbA, ROR, ROR, ROR, SHP, SF1, TLX, TR2, TR4
Screen format– LBD-Gal4 chimeras and UAS-tk-Luc reporter in BacMam viruses1
– Transduced multiple cell types with BacMam viruses– Selected cells with optimal receptor expression to allow identification of
agonists and inverse agonists– Screened the 10K probe set at 1.0 M in duplicate
Followed up all hits (however weak) with chemical analog synthesis
Ran experiment over 18 month period– Total budget = 2 conventional HTS
1M. Boudjelal et al Biotecnol. Annu. Rev. 2005 11 1387
Results to Date
Receptors with hits* Receptors with no hits– COUP-TF1– COUP-TF2– COUP-TF3– DAX– GCNF– LRH1– PNR– RevErbA– ROR– ROR– ROR– SHP– SF1– TLX– TR2– TR4
* Hits with structure-activity across a small series of analogs
Conclusion
Remaining orphan receptors show low chemical tractability in LBD-Gal4 format
Some hits identified in cell-free FRET assays– LRH1– SF1– ROR– RevErbA
However demonstration of robust cellular activity has been difficult– Many of the receptors are constitutively active– Some are constitutive repressors– LBD-Gal4 chimera may not be the optimal assay format
Triangle of Tractability
Chemical Tractability compiled from GSK screening results
ARARCARCARERERPRPR
LXRLXRPPARPPAR
PXRPXR
GRGRMR MR RARRARRXRRXRFXRFXRTRTR
LRH1LRH1ERRERRSF1SF1RORROR
RevErbRevErb
TLXTLXSHPSHP
TR2/4TR2/4GCNFGCNFNGFIBNGFIBCOUPCOUPHNF4HNF4PNRPNRDAXDAX
HIGH
LOW
Acknowledgements
NR Chemistry– Sharon Boggs– Peter Brown– Richard Caldwell– Esther Chao– Jon Collins– Patrick Maloney– Barry Shearer– Phil Turnbull
Informatics– Deborah Jones-Hertzog
CASS– Mike Cory– Felix DeAnda
NR Screening/Biology – Richard Buckholz– Steve Blanchard– Lisa Miller– Linda Moore– Derek Parks– Mike Watson– Bruce Wisely
Compound Acquisition– David Langley
Compound Services– Brenda Ray