Philip E. Bourne
University of California San Diego pbourne@ucsd.edu
http://www.sdsc.edu/pb/Talks/
HUPO San Diego Feb. 2009

• 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

• 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

• 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 and NCEs?
• We could use it for lead optimization and possible ADME/Tox prediction

• One of three things:
1. Nothing
2. A possible explanation for a side-effect of a drug
3. 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

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

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

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

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 C a atom with a value that is the distance to the environmental boundary
• Update the value with those of surrounding C a atoms dependent on distances and orientation – atoms within a
10A radius define i
GP

P
  neighbors
Di
Pi

1 .
0
 cos( a i )

1 .
0
2 .
0
Computational Methodology Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9

Discrimination Power of the Geometric
Potential
4
3.5
binding site non-binding site
3
2.5
2
1.5
1
0.5
0
0
11 22 33 44 55 66 77 88 99
Geometric Potential
100 0
Geometric Potential Scale
• Geometric potential can distinguish binding and non-binding sites
Computational Methodology Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9

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

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

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 d
  i f a i
S b i   i f b i
S a i f a
, f b are the 20 amino acid target frequencies of profile and b , respectively a
S a
, S b are the PSSM of profile a and b , respectively
Computational Methodology Xie and Bourne 2008 PNAS , 105(14) 5441

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

• Evolutionary linkage between:
– NAD-binding Rossmann fold
– S-adenosylmethionine (SAM)-binding domain of SAMdependent methyltransferases
• CatecholO -methyl transferase (COMT) is SAMdependent 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

• Entacapone and tolcapone docked onto 215 NADbinding proteins from different species
• M.tuberculosis
Enoyl-acyl carrier protein reductase ENR
(InhA) discovered as potential new drug target
• ENR is the primary target of many existing anti-TB drugs but all are very toxic
• ENR catalyses the final, rate-determining step in the fatty acid elongation cycle
• Alignment of the COMT and ENR binding sites revealed similarities ...
Repositioning an Existing Drug - 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
• In vivo support
• Assay of direct binding of entacapone and tolcapone to ENR reveals promising leads with no chemical relationship to existing drugs
Repositioning an Existing Drug - The TB Story
PLoS Comp Biol Under Review

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

• 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.
, 2007 3(11) e217

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

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

• 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

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

The Torcetrapib Story
PLoS Comp Biol Under Minor Revision

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 torcetrapib with the docking score around -8.0.
The Torcetrapib Story
PLoS Comp Biol Under Minor Revision

VDR
–
RAS
JTT705
High blood pressure
Torcetrapib Anacetrapib JTT705
+
RXR
PPAR α
PPAR δ
PPAR γ
+
FA
?
?
FABP
?
Anti-inflammatory function
JNK/IKK pathway
JNK/NFK B pathway
Immune response to infection
PLoS Comp Biol Under Minor Revision

• 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

• 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

Lei Xie
Li Xie
Jian Wang
Sarah Kinnings