1. University of California San Diego
Off-Targets
Philip E. Bourne
University of California San Diego
45 mins including questions
Support Open Access

2. Motivation
When you add a foreign chemical into something as complex as a human being do you really believe that drug is binding to only a single receptor?

3. The Drug Discovery Pipeline
Selective
Collective
Effect

4. Motivation
The truth is we know very little about how the major drugs we take work
We know even less about what side effects they might have
Drug discovery seems to be approached in a very consistent and conventional way
The cost of bringing a drug to market is huge ~$800M
The cost of failure is even higher e.g. Vioxx - $4.85Bn - Hence fail early and cheaply

5. Motivation
The truth is we know very little about how the major drugs we take work – receptors are unknown
We know even less about what side effects they might have - receptors are unknown
Drug discovery seems to be approached in a very consistent and conventional way
The cost of bringing a drug to market is huge ~$800M – drug reuse is a big business
The cost of failure is even higher e.g. Vioxx - $4.85Bn - fail early and cheaply

6. What if…
We can characterize a protein-ligand binding site from a 3D structure (primary site) and search for that site on a proteome wide scale?
We could perhaps find alternative binding sites (off-targets) for existing pharmaceuticals?
We could use it for lead optimization and possible ADME/Tox prediction
Absorption, distribution, metabolism and excretion

7. What Do Off-targets Tell Us?
One of three things:
Nothing
A possible explanation for a side-effect of a drug
A possible repositioning of a drug to treat a completely different condition
Today I will give you examples of both 2 and 3 and illustrate the complexity of the problem

8. Agenda Computational Methodology Side Effects - The Tamoxifen Story
Repositioning an Existing Drug - The TB Story
Salvaging $800M – The Torcetrapib Story

9. Need to Start with a 3D Drug-Receptor Complex - The PDB Contains Many Examples
Generic Name
Other Name
Treatment
PDBid
Lipitor
Atorvastatin
High cholesterol
1HWK, 1HW8…
Testosterone
Osteoporosis
1AFS, 1I9J ..
Taxol
Paclitaxel
Cancer
1JFF, 2HXF, 2HXH
Viagra
Sildenafil citrate
ED, pulmonary arterial hypertension
1TBF, 1UDT, 1XOS..
Digoxin
Lanoxin
Congestive heart failure
1IGJ

10. A Reverse Engineering Approach to Drug Discovery Across Gene Families
Characterize ligand binding
site of primary target
(Geometric Potential)
Identify off-targets by ligand
binding site similarity
(Sequence order independent
profile-profile alignment)
Extract known drugs
or inhibitors of the
primary and/or off-targets
Search for similar small molecules …
Dock molecules to both
primary and off-targets
Statistics analysis
of docking score
correlations
Computational Methodology

11. Characterization of the Ligand Binding Site - The Geometric Potential
Conceptually similar to hydrophobicity
or electrostatic potential that is
dependant on both global and local
environments
Initially assign Ca atom with a value that is the distance to the environmental boundary
Update the value with those of surrounding Ca atoms dependent on distances and orientation – atoms within a 10A radius define i
P distance to environmental boundary; Pi Di and alphai D distance to central atom alpha direction to central atom
Computational Methodology
Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9

12. Discrimination Power of the Geometric Potential
Geometric potential can distinguish binding and non-binding sites
100
Geometric Potential Scale
Computational Methodology
Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9

13. Local Sequence-order Independent Alignment with Maximum-Weight Sub-Graph Algorithm
Structure A
Structure B
L E R
V K D L
L E R
V K D L
Build an associated graph from the graph representations of two structures being compared. Each of the nodes is assigned with a weight from the similarity matrix
The maximum-weight clique corresponds to the optimum alignment of the two structures
Xie and Bourne 2008 PNAS, 105(14) 5441

14. Theodosius Dobzhansky (1900-1975)
Nothing in Biology {including Drug Discovery} Makes Sense Except in the Light of Evolution    
                                
Theodosius Dobzhansky ( )

15. Similarity Matrix of Alignment
Chemical Similarity
Amino acid grouping: (LVIMC), (AGSTP), (FYW), and (EDNQKRH)
Amino acid chemical similarity matrix
Evolutionary Correlation
Amino acid substitution matrix such as BLOSUM45
Similarity score between two sequence profiles
fa, fb are the 20 amino acid target frequencies of profile a and b, respectively
Sa, Sb are the PSSM of profile a and b, respectively
Computational Methodology
Xie and Bourne 2008 PNAS, 105(14) 5441

16. Lead Discovery from Fragment Assembly
Privileged molecular moieties in medicinal chemistry
Structural genomics and high throughput screening generate a large number of protein-fragment complexes
Similar sub-site detection enhances the application of fragment assembly strategies in drug discovery
1HQC: Holliday junction migration motor protein
from Thermus thermophilus
1ZEF: Rio1 atypical serine protein kinase
from A. fulgidus 16

17. Lead Optimization from Conformational Constraints
Same ligand can bind to different proteins, but with different conformations
By recognizing the conformational changes in the binding site, it is possible to improve the binding specificity with conformational constraints placed on the ligand
1ECJ: amido-phosphoribosyltransferase
from E. Coli
1H3D: ATP-phosphoribosyltransferase 17

18. Agenda Computational Methodology
Repositioning an Existing Drug - The TB Story
Side Effects - The Tamoxifen Story
Salvaging $800M – The Torcetrapib Story

19. Tuberculosis (TB) One third of global population infected
Kills 2 million people each year
95% of deaths in developing countries
Anti-TB drugs hardly changed in 40 years
MDR-TB and XDR-TB pose a threat to human health worldwide
Development of novel, effective, and inexpensive drugs is an urgent priority
Repositioning an Existing Drug - The TB Story 19

20. Found.. Evolutionary linkage between:
NAD-binding Rossmann fold
S-adenosylmethionine (SAM)-binding domain of SAM-dependent methyltransferases
Catechol-O-methyl transferase (COMT) is SAM-dependent methyltransferase
Entacapone and tolcapone are used as COMT inhibitors in Parkinson’s disease treatment
Hypothesis:
Further investigation of NAD-binding proteins may uncover a potential new drug target for entacapone and tolcapone
Repositioning an Existing Drug - The TB Story
Repositioning an Existing Drug - The TB Story 20

21. Functional Site Similarity between COMT and ENR
Entacapone and tolcapone docked onto 215 NAD-binding proteins from different species
M.tuberculosis Enoyl-acyl carrier protein reductase ENR (InhA) discovered as potential new drug target
InhA is the primary target of many existing anti-TB drugs but all are very toxic
InhA catalyses the final, rate-determining step in the fatty acid elongation cycle
Alignment of the COMT and InhA binding sites revealed similarities ...
Repositioning an Existing Drug - The TB Story

22. Summary of the TB Story
Entacapone and tolcapone shown to have potential for repositioning
Direct mechanism of action avoids M.tuberculosis resistance mechanisms
Possess excellent safety profiles with few side effects – already on the market
At least some in vivo support
Assay of direct binding of entacapone and tolcapone to InhA under way
Repositioning an Existing Drug - The TB Story 22

23. Agenda Computational Methodology
Repositioning an Existing Drug - The TB Story
Side Effects - The Tamoxifen Story
Salvaging $800M – The Torcetrapib Story

24. Selective Estrogen Receptor Modulators (SERM)
One of the largest classes of drugs
Breast cancer, osteoporosis, birth control etc.
Amine and benzine moiety
Side Effects - The Tamoxifen Story
PLoS Comp. Biol., (11) e217

25. Adverse Effects of SERMs
cardiac abnormalities
thromboembolic
disorders
loss of calcium
homeostatis
?????
ocular toxicities
Side Effects - The Tamoxifen Story
PLoS Comp. Biol., 3(11) e217

26. Structure and Function of SERCA Sacroplasmic Reticulum (SR) Ca2+ ion channel ATPase
Regulating cytosolic calcium levels in cardiac and skeletal muscle
Cytosolic and transmembrane domains
Predicted SERM binding site locates in the TM, inhibiting Ca2+ uptake
Side Effects - The Tamoxifen Story
PLoS Comp. Biol., 3(11) e217

27. The Challenge
Design modified SERMs that bind as strongly to estrogen receptors but do not have strong binding to SERCA, yet maintain other characteristics of the activity profile
Side Effects - The Tamoxifen Story
PLoS Comp. Biol., 3(11) e217

28. Agenda Computational Methodology
Repositioning an Existing Drug - The TB Story
Side Effects - The Tamoxifen Story
Salvaging $800M – The Torcetrapib Story

29. The Torcetrapib Story

30. Cholesteryl Ester Transfer Protein (CETP)
CETP inhibitor X
CETP
LDL
HDL
Bad Cholesterol
Good Cholesterol
collects triglycerides from very low density or low density lipoproteins (VLDL or LDL) and exchanges them for cholesteryl esters from high density lipoproteins (and vice versa)
A long tunnel with two major binding sites. Docking studies suggest that it possible that torcetrapib binds to both of them.
The torcetrapib binding site is unknown. Docking studies show that both sites can bind to trocetrapib with the docking score around -8.0.
The Torcetrapib Story

31. Docking Scores eHits/Autodock
Off-target
PDB Ids
Torcetrapib
Anacetrapib
JTT705
Complex ligand
CETP
2OBD
/ -5.72
/ -8.15
/ -6.65
(PCW)
Retinoid X receptor
1YOW
1ZDT /
-6.74
/ -7.68
-7.35
/ -7.28
-6.95
(POE)
PPAR delta
1Y0S
/ -8.22
/ -7.91
/ -8.36
(331)
PPAR alpha
2P54
/ -6.67
/ -7.27
/ -7.78
(735)
PPAR gamma
1ZEO
/ -7.31
> 0.0 / -8.25
/ -8.11
(C01)
Vitamin D receptor
1IE8
>0.0/ -4.73
>0.0 / -6.25
/ -9.70
(KH1) -7.35
Glucocorticoid Receptor
1NHZ
1P93
/-4.43
/-5.63
/-7.08
/-0.58
/-7.09
/-9.42
Fatty acid
binding protein
2F73
2PY1
2NNQ
>0.0/ -4.33
>0.0/-6.13
/-6.40
>0.0/ -7.81
>0.0/ -6.98
/-7.64
/ -8.49
/-6.33
/6.35
???
T-Cell CD1B
1GZP
/ -7.02
/ -7.15
/ -8.02
(GM2)
IL-10 receptor
1LQS
/ -4.59
/ -6.77
/ -5.95
GM-2 activator
2AG9
/ -6.26
/ -6.98
/ -6.17
??? (MYR) -4.16
(3CA2+) CARDIAC TROPONIN C
1DTL
/-5.83
/-6.71
/-5.79
cytochrome bc1 complex
1PP9 (PEG)
/-6.97
/-9.07
/-6.64
1PP9 (HEM)
/-7.21
/8.79
/-8.94
human cytoglobin
1V5H
/-4.89
/-7.00
/-4.94
The Torcetrapib Story

32. – + + JTT705 Torcetrapib Anacetrapib JTT705 VDR RXR FA RAS ? FABP
PPARα
PPARδ ? ?
PPARγ
High blood
pressure +
JNK/IKK pathway
JNK/NF-KB pathway
Anti-inflammatory
function
Immune response
to infection

33. Docking Scores eHits/Autodock
Off-target
PDB Ids
Torcetrapib
Anacetrapib
JTT705
Complex ligand
CETP
2OBD
/ -5.72
/ -8.15
/ -6.65
(PCW)
Retinoid X receptor
1YOW
1ZDT /
-6.74
/ -7.68
-7.35
/ -7.28
-6.95
(POE)
PPAR delta
1Y0S
/ -8.22
/ -7.91
/ -8.36
(331)
PPAR alpha
2P54
/ -6.67
/ -7.27
/ -7.78
(735)
PPAR gamma
1ZEO
/ -7.31
> 0.0 / -8.25
/ -8.11
(C01)
Vitamin D receptor
1IE8
>0.0/ -4.73
>0.0 / -6.25
/ -9.70
(KH1) -7.35
Glucocorticoid Receptor
1NHZ
1P93
/-4.43
/-5.63
/-7.08
/-0.58
/-7.09
/-9.42
Fatty acid
binding protein
2F73
2PY1
2NNQ
>0.0/ -4.33
>0.0/-6.13
/-6.40
>0.0/ -7.81
>0.0/ -6.98
/-7.64
/ -8.49
/-6.33
/6.35
???
T-Cell CD1B
1GZP
/ -7.02
/ -7.15
/ -8.02
(GM2)
IL-10 receptor
1LQS
/ -4.59
/ -6.77
/ -5.95
GM-2 activator
2AG9
/ -6.26
/ -6.98
/ -6.17
??? (MYR) -4.16
(3CA2+) CARDIAC TROPONIN C
1DTL
/-5.83
/-6.71
/-5.79
cytochrome bc1 complex
1PP9 (PEG)
/-6.97
/-9.07
/-6.64
1PP9 (HEM)
/-7.21
/8.79
/-8.94
human cytoglobin
1V5H
/-4.89
/-7.00
/-4.94

34. – + + JTT705 Torcetrapib Anacetrapib JTT705 VDR RXR FA RAS ? FABP
PPARα
PPARδ ? ?
PPARγ
High blood
pressure +
JNK/IKK pathway
JNK/NF-KB pathway
Anti-inflammatory
function
Immune response
to infection

35. Summary
We have established a protocol to look for off-targets for existing therapeutics and NCEs
Understanding these in the context of pathways would seem to be the next step towards a new understanding
Lots of other opportunities to examine existing drugs

36. Bioinformatics Final Examples..
Donepezil for treating Alzheimer’s shows positive effects against other neurological disorders
Orlistat used to treat obesity has proven effective against certain cancer types
Ritonavir used to treat AIDS effective against TB
Nelfinavir used to treat AIDS effective against different types of cancers

37. Acknowledgements Lei Xie Li Xie Jian Wang Sarah Kinnings
Nancy Buchmeier
Support Open Access