Transcript Diversity Analysis - ACS Division of Chemical Information

GAUDI
Jordi Mestres & Tudor Oprea
Chemotargets & Sunset Molecular
Drug Reprofiling Symposium
ACS Boston, 19 August 2007
Copyright © Tudor I. Oprea, 2007. All rights reserved
The NIH Roadmap: Some Numbers
NIH Roadmap Initiative
Molecular Libraries Initiative
4 Chemical Synthesis
Centers
MLSCN (9+1)
9 external centers
1 NIH intramural
20 x 10 = 200 assays
PubChem
(NLM)
ECCR (6) Predictive
Exploratory ADMET
Centers
(8)
CombiChem
Parallel synthesis
DOS
4 centers + DPI
100k–500k compounds
SAR matrix
250-300 thousand
small molecules
Hundreds of HTS Assays
Slide modified from Alex Tropsha (UNC)
OUTPUT:
Chemical
Probes
Beyond traditional drug discovery:
Off Target Profiling
8,0
O
N
O
O
7,5
N
NO2
1
N
H
O
F
7,0
pIC50
O
H+
N
6,5
6,0
N
O
5,5
O
5,0
5-HT7
5-HT6
5-HT5A
5-HT3
5-HT2A
5-HT1A
Poulain et al. J. Med. Chem. 2001, 44, 3391
M2
Receptor List
M1
H2
D5
D4
D3
D2
D1
a1
A3
ORL1
d
N
k
2
m
F
The Molecular Pharmacopoeia
Drug Targets & Dis-ease
•
Literature estimates the number of drug targets between 5,000 (high
estimate) to 500 (targets hit by current drugs)
– Definition: A target is a macro-molecular structure (defined by at least a
molecular mass) that undergoes a specific interaction with therapeutics
(chemicals administered to treat or diagnose a disease). The target-drug
interaction results in clinical effect(s).
– Imming, Sinning & Meyer considered the ’intended’ (not side-effect)
targets for drugs; validation in knock-out models - a plus; receptor
(ant)agonism, enzyme inhibition were also considered proof; 1-3
targets/drug were considered [was this OK?!].
– Overington, Al-Lazikani & Hopkins considered protein targets for FDAapproved drugs only (~1200 drugs from the Orange Book). They did make
allowances for ”non-intended” drug targets for, e.g., ritonavir – an HIVprotease inhibitor given in combination with other such inhibitors because
it slows down their metabolism via CYP3A4 inhibition (thus CYP3A4 was
considered a drug target for ritonavir). [this was better].
•
Part of the problem: there is no “right” definition for health (e.g, free
from dis-ease). In the case of sickness, do we “cure”, do we “treat”
patients, or do we heal them?
*) P. Imming, C. Sinning, A. Meyer, Nature Rev. Drug Discov 2006, 5: 821-834
*) J. Overington, B. Al-Lazikani, A.L. Hopkins, Nature Rev. Drug Discov 2006, 5: 993-996
Aspirin – the “first drug”
O
O
O
•
COX-1; Prostaglandin G/H synthase 1
•
COX-2; Prostaglandin G/H synthase 2
Acts as suicide inhibitor; is there a COX-3???
O
•
Platelet glycoprotein IIb of IIb/IIIa complex, or
antigen CD41
Acts as competitive antagonist (μM inhibitor)
(used as Baby Aspirin as antiaggregant)
•
Phospholipase A2 (PDB code 1OXR)
Acts as competitive antagonist (μM inhibitor)
History: Felix Hoffmann was believed to have developed
aspirin for F. Bayer & Co., to help his rheumatic father. Arthur
Eichengrün claimed in 1949 that the work had been done
under his direction.
Walter Sneader analyzed archival data from Bayer, as well as
published material and concluded that Eichengrün's claim is
valid. Acetylsalicylic acid was synthesised under Eichengrün's
direction, and it would not have been introduced in 1899
without his intervention
W. Sneader, British Medical Journal 2000, 321:1591–1594
Aripiprazole – a “dirty drug” example
O
•
•
N
•
•
•
O
•
•
•
•
N
•
N
•
•
Cl
Cl
Target
D2
D3
D4
5HT1A
5HT2A
5HT2C
5HT7
alpha1AR
H1
Meas Value
Activity
Ki
0.34 nM
partial agonist
Ki
0.8 nM
antagonist
Ki
44 nM
antagonist
Ki
1.7 nM
partial agonist
Ki
3.4 nM
antagonist
Ki
15 nM
antagonist
Ki
39 nM
antagonist
Ki
57 nM
antagonist
Ki
61 nM
antagonist
5HT reuptake Ki
98 nM
antagonist
Aripiprazole is an antipsychotic and neuroleptic with
efficacy in schizophrenia and bipolar disorder. Its
mechanism of action is unknown (as per FDA label),
although the above activities were observed in vitro.
Tamoxifen – a “clean drug” example
•
OH
CYP2D6, 2B6
2C9, 2C19, 3A
CH3
H3C
N
O
CH3
H3C
CH3
O
TAM
N
CH3 •
4OHTAM
CYP3A4/5
•
CYP3A4/5
OH
•
CYP2D6
CH3
H3C
O
CH3
H3C
NH
N-desmethylTAM
Desta, Z et al JPET 2004, 310:1062-1075
O
Endoxifen
NH
•
•
Estrogen receptor – intended
drug target. TAM & metabolites
antagonize dimer formation; ERα
monomer + TAM can act as
agonist (NFkB, AP-1)
ERRγ (estrogen-related
response receptors, also class 3
NHRs) – 4OHTAM, antagonist
Anti-Target (?): GPR30 (estrogen
GPCR) – 4-OH TAM, agonist
Anti-Target: Emopamil binding
protein; 3β-hydroxysteroid-Δ7-8
isomerase; cholestenol deltaisomerase (TAM, inhibitor)
Anti-Target: Type I sigma
receptor (TAM & metabolites,
antagonists)
Anti-Target (?): PXR; Pregnane X
receptor; Orphan nuclear
receptor PXR (activator)
Tamoxifen is the gold standard “antiestrogen” therapy, used as the first line therapy in
Estrogen positive breast cancers. Although its mechanism of action is “known” (as per FDA
label), TAM has in vitro nM affinity to the above targets (except PXR; N/A).
Amantadine – a “simple drug” example
•
D1 dopamine receptor agonist
•
D2 dopamine receptor agonist
•
N-methyl D-aspartate receptor subtype 2D (Glutamate
[NMDA] receptor subunit epsilon 4) - antagonist at the
Phencyclidine binding site
NH2
Used in Parkinson’s disease
•
Antiviral against Influenza A virus by interfering with the
viral M2 membrane ion channel; appears effective on all
Influenza A viral strains
•
Antiviral against feline immunodeficiency virus
Used as antiviral
•
Side effect 1: hERG (probably). Demonstrated to produce
QT-prolongation (with risk for congenital long QT patients)
•
Side effect 2: anticholinergic-like effects (dry mouth,
urinary retention, and constipation) – do not appear to be
mediated by direct binding to cholinergic receptors
Drug Targets Revisited
•
Imming, Sinning & Meyer counted 218 drug targets; Overington, AlLazikani, & Hopkins suggest 186 small-molecule targets
– Discrepancy: Drug targets, as counted by these authors, do not consider
unique protein classes, and do not capture each high-affinity target.
•
An analysis of 988 drugs (WOMBAT-PK database) shows 410 unique
drug targets, of which 299 are human:
–
•
From WOMBAT: 68 additional targets, of which 43 are human, are
reported in the medicinal chemistry literature, with affinity higher than 10
nM for 171 launched drugs:
–
•
•
•
190 enzymes; 68 GPCRs; 55 ion channels; 21 transporters; 18 NHRs; 44
’proteins’; 7 ’other’ receptors; and 6 nucleic acids
47 enzymes; 11 receptors (9 GPCRs, 2 NHRs); 4 ion channels; and 6
proteins.
In total, 498 targets, of which 342 are human, were found
How many Drug Targets? And how many small molecules can we develop
to therapeutically manipulate them?
Part of the difficulty: there is no unique, standardised source to capture
information related to small molecules (including drugs) and the
macromolecules (proteins, nucleic acids) that interact with them.
Chemical and Target Spaces
covered in WOMBAT
•
A total of 163,134 unique molecules annotated to 576 targets
•
•
Enzymes: 411
G protein-coupled receptors: 120
Nuclear receptors: 29
Integrins: 7
Ion channels: 6
Transporters: 3
•
containing 152,158 IC50 values and 107,617 Ki values.
•
How can one visualize, classify, and analyze this Chemo-Target
Space?
•
•
•
•
WOMBAT Heatmap
WOMBAT Descriptors Space
WOMBAT Bioactivity Space
Chemical and Target Spaces
of DRUGS covered in WOMBAT
• A total of 803 unique drugs annotated to 268 targets:
•
Enzymes: 166
•
G protein-coupled receptors: 73
•
Nuclear receptors: 19
•
Integrins: 3
•
Ion channels: 4
•
Transporters: 3
• containing 3,320 IC50 values and 3,047 Ki values.
WOMBAT Bioactivity Space
WOMBAT Drugs Descriptor Space
WOMBAT Drugs Bioactivity Space
WOMBAT Drugs Heatmap
WOMBAT Drugs: Fused 5-6 Rings Space
WOMBAT Drugs: Fused 5-6 Rings Descriptors
WOMBAT Drugs: Fused 5-6 Rings Scaffolds
WOMBAT “5-6” Drug: Thalidomide PK
WOMBAT “5-6” Drug: Thalidomide Bioactivity
Drug profiling: Graph Framework of Pergolide
Drug profiling: Annotations for Pergolide
D1
D2
D3
5-HT1A
Drug profiling: 322 drugs x 199 targets
D1
D2
D3
5-HT1A
5-HT1D
*


*
*

Not reported in literature
Micromolar affinities confirmed
* Reference annotated molecule present in Wombat
Conclusions
• GAUDI is a tool that mines target and chemical space
simultaneously, given the hierarchical classification that is
(or can be) inherent to known targets.
• GAUDI is annotated with in vitro data only. However, the
use of scaffold mapping enables the user to “jump” from
one target space to another, and make high-level
connections, that are otherwise hidden
• GAUDI is designed to move beyond the “traditional query”
of (sub)structure / target / text search
• Though current data do not explain the withdrawal
symptoms for PERGOLIDE, the opioid activities suggested
with GAUDI show a previously unkown activity for this drug
Acknowledgments
• WOMBAT Team: Maria Mracec, Marius Olah, Lili
Ostopovici, Ramona Rad, Alina Bora, Nicoleta
Hadaruga, Ramona Moldovan, Dan Hadaruga
(Romanian Academy Institute of Chemistry,
Timisoara, Romania)
• GAUDI was developed by Innova Consulting,
Santander, Spain http://innovayconsulting.com/