The Role of Biopathways in Drug Repositioning and Determining Side Effects

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The Role of Biopathways in Drug Repositioning
and Determining Side Effects

• Philip E. Bourne
• University of California San Diego
• pbourne_at_ucsd.edu

Support Open Access
BioPathways 2008
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What We Know What We Dont Know

• We know how to do functional annotation of
  proteins
• We know little about biopathways
• A side effect of our annotation work relates to
  drug repositioning
• That work highlights our need to explore pathways
  this is what I hope to show today and perhaps
  get you interested

proteome.sdsc.edu
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What Motivates Us

• The truth is we know very little about how the
  major drugs we take work most drugs bind to a
  variety of targets with varying affinity
• 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 800M
• The cost of failure is even higher e.g. Vioxx -
  4.85Bn - Hence fail early and cheaply

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What Has Evolution Taught Us?

• Global 3D similarity and sequence similarity do
  not tell the whole story
• Perhaps a ligand binding site is what has passed
  from generation to generation while virtually all
  other aspects of the protein have changed?

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What Has Evolution Taught Us About Drug
Discovery?

• If that were true and evolutionarily related
  ligand binding sites could be found, they
  presumably would exist across very diverse gene
  families
• From the perspective of drug discovery such sites
  would have significant implications

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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

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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 how pathways come into play

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Agenda

• Computational Methodology
• Side Effects - The Tamoxifen Story
• Repositioning an Existing Drug - The TB Story
• Salvaging 800M The Torcetrapib Story
• The need to introduce pathway analysis

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Need to Start with a 3D Drug-Receptor Complex -
The PDB Contains Many Examples
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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
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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

Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl
4)S9
Computational Methodology
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Discrimination Power of the Geometric Potential

• Geometric potential can distinguish binding and
  non-binding sites

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Geometric Potential Scale
Computational Methodology
Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl
4)S9
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Boundary Accuracy of Ligand Binding Site
Prediction

• 90 of the binding sites can be identified with
  above 50 sensitivity
• The specificity of 70 binding sites identified
  is above 90

Computational Methodology
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So Far

• Geometric potential dependant on local
  environment of a residue relative to other
  residues and the environmental boundary
• Geometric potential reasonably good at
  discriminating between ligand binding sites and
  non-ligand binding sites
• Boundary of the binding site reasonably well
  defined
• How to compare sites ???

Computational Methodology
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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
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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
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So What is the Potential of this Methodology?
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Finding Secondary Binding Sites for Major
Pharmaceuticals

• Scan known binding sites for major
  pharmaceuticals bound to their receptors against
  the human and other druggable proteomes
• Try and correlate strong hits with known data
  from the literature, databases, clinical trials
  etc. and now pathways to provide molecular
  evidence of secondary effects

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Agenda

• Computational Methodology
• Repositioning an Existing Drug - The TB Story
• Side Effects - The Tamoxifen Story
• Salvaging 800M The Torcetrapib Story
• The need to introduce pathway analysis

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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
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Hypothesis Drawn from the Study of Evolution

• We were looking for connections (evolutionary
  linkages) across fold and functional space
  through an all-by-all comparison of ligand
  binding sites

Repositioning an Existing Drug - The TB Story
Repositioning an Existing Drug - The TB Story
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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 Parkinsons 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
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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
• 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
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Binding Site Similarity between COMT and ENR
Repositioning an Existing Drug - The TB Story
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In Vivo Studies

• Quantitative and microplate assays of Mtb agree
• Entacapone - 80 growth inhibition with 62 ug/ml
  100 inhibition with 2x the dose
• Tolcapone similar results

Courtesy Nancy Buchmeier
Repositioning an Existing Drug - The TB Story
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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 ENR under way

Repositioning an Existing Drug - The TB Story
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Agenda

• Computational Methodology
• Repositioning an Existing Drug - The TB Story
• Side Effects - The Tamoxifen Story
• Salvaging 800M The Torcetrapib Story
• The need to introduce pathway analysis

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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., 2007 3(11) e217
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Adverse Effects of SERMs
cardiac abnormalities
loss of calcium homeostatis
thromboembolic disorders
?????
ocular toxicities
Side Effects - The Tamoxifen Story
PLoS Comp. Biol., 3(11) e217
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Ligand Binding Site Similarity Search On a
Proteome Scale
SERCA
ERa

• Searching human proteins covering 38 of the
  drugable genome against SERM binding site
• Matching Sacroplasmic Reticulum (SR) Ca2 ion
  channel ATPase (SERCA) TG1 inhibitor site
• ERa ranked top with p-valuelt0.0001 from reversed
  search against SERCA

Side Effects - The Tamoxifen Story
PLoS Comp. Biol., 3(11) e217
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Structure and Function of SERCA

• 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
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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
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Agenda

• Computational Methodology
• Repositioning an Existing Drug - The TB Story
• Side Effects - The Tamoxifen Story
• Salvaging 800M The Torcetrapib Story
• The need to introduce pathway analysis

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Consider in any of these cases there are likely
multiple secondary sites
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Cholesteryl Ester Transfer Protein (CETP)
CETP inhibitor
X
CETP
HDL
LDL
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 -11.0.

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Docking Scores eHits/Autodock
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EP distributions in binding pockets
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Docking Scores eHits/Autodock
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Torcetrapib
Anacetrapib
JTT705
JTT705
VDR

RXR
FA

RAS
FABP
?
PPARa
PPARd
?
?
PPAR?
High blood pressure

JNK/IKK pathway JNK/NF-KB pathway
Anti-inflammatory function
Immune response to infection
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Docking Scores eHits/Autodock
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Torcetrapib
Anacetrapib
JTT705
JTT705
VDR

RXR
FA

RAS
FABP
?
PPARa
PPARd
?
?
PPAR?
High blood pressure

JNK/IKK pathway JNK/NF-KB pathway
Anti-inflammatory function
Immune response to infection
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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

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Bioinformatics Final Examples..

• Donepezil for treating Alzheimers 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

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Acknowledgements
Eric Scheeff Lei Xie Li Xie Jian Wang Sarah
Kinnings Nancy Buchmeier
Support Open Access
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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
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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
from E. Coli
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Renin-angiotensin system (RAS)
Angiotensinogen

Hydrolyzation
Renin
Angiotensin I
Peptide cleavage

ACE
Angiotensin II


Aldosterone secretion
High blood pressure
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JTT705
Torcetrapib
Anacetrapib
JTT705
Anacetrapib
X
GCR
Cytochrome bc1 complex
excessive activation
X
?
Hypertension
Inhibition of NF-KB
Cardiac hypertrophy, hypertension
Q cycle
anti-cancer and anti-inflammatory
ATP generation, cell repair, cell death
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Torcetrapib
Anacetrapib
JTT705
Torcetrapib
T-cell CD1B
Cardiac TnC
X
Ca2
X
CD1Bantigen
Troponin conformation change
Immune response to infection
Heart muscle contraction
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Summary Estimated Capitalized Costs for New
Chemical Entities (NCEs) Entering Each Phase

• Estimated costs for a drug withdrawal
• 60.0 millions
• Phase III is most costly fail fast, fail cheap

M. Dickson J. P. Gagnon, Nature Review Drug
Discovery 3(2004) p417-429
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Implications on Drug Development

• Taking account of both target and off-target for
  lead optimization
• Drug delivery and administration regime

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Improved Performance of Alignment Quality and
Search Sensitivity and Specificity
RMSD distribution of the aligned common
fragments of ligands from 247 test cases showing
four scores amino acid grouping, chemical
similarity, substitution matrix and
profile-profile.
.
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2D small molecule similarity between existing and
potential ENR inhibitors
Entacapone
Tolcapone
ZAM p0.205
AYM p0.065
Density
Density
Tanimoto Coefficient
Tanimoto Coefficient
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Docking existing and potential InhA inhibitors
onto COMT and InhA
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Correlation of binding affinity profiles between
COMT and InhA

• Tolcapone-like molecules

Control Docking Score
COMT Docking Score
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Binding pose analysis of potential InhA
inhibitors with InhA
Asp110
Asp115
15.25Å
14.53Å
Glu210
11.54Å
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Comparison of surface electrostatic potential
between COMT and InhA functional sites

• Electrostatic potentials of COMT and InhA
  calculated using APBS
• Predicted binding poses of entacapone and
  tolcapone inserted into proteins
• Qualitative similarities between COMT and InhA
  functional sites observed
• In both cases, nitrite groups of entacapone and
  tolcapone associated with positively charged
  region of active site

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Comparison of surface electrostatic potential
between COMT and InhA functional sites
COMT
InhA
Entacapone
Tolcapone
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Advantage to Using Ligand Site Similarity

• Poor correlation between structure and activity
• Infinite chemical space

Small molecule
Similarity
. Not adequately reflecting functional
relationship . Not directly addressing drug
design problem
Protein Sequence/Structure
Similarity
. Build closer structure- function
relationships . Limit chemical space through
co-evolution
Protein Functional Site
Similarity
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Correlation of Binding Affinity Profiles between
COMT and ENR

• Entacapone-like molecules

Control Docking Score
COMT Docking Score
Linear regression
2 identical sites
Repositioning an Existing Drug - The TB Story