NOVEL%20PARADIGMS%20FOR%20DRUG%20DISCOVERY

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NOVEL PARADIGMS FOR DRUG DISCOVERY SHOTGUN
COMPUTATIONAL MULTITARGET SCREENING RAM
SAMUDRALA ASSOCIATE PROFESSOR UNIVERSITY OF
WASHINGTON NIH DIRECTORS PIONEER AWARD
2010 How does the genome of an organism
specify its behaviour and characteristics? How
can we use this information to improve human
health and quality of life?
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GENOME SEQUENCE TO PROTEIN AND PROTEOME
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SHOTGUN MULTITARGET DOCKING WITH DYNAMICS
herpes, malaria, dengue hepatitis C, dental
caries HIV, HBRV, XMRV
CLINICAL STUDIES/APPLICATION
M Lagunoff (UW), W Van Woorhis (UW), S Michael
(FCGU), J Mittler/J Mullins (UW), G Wong/A
Mason/L Tyrell (U Alberta), W Chantratita/P
Palittapongarnpim (Thailand)
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INHIBITION OF ALL REPRESENTATIVE HERPES PROTEASES
Predicted
Observed Function is inactivated. protease
ligand KD lt µM protease dimer KD lt µM
Jenwitheesuk/Myszka
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INHIBITION OF ALL HERPESVIRUSES
Viral load
Fold inhibition
Lagunoff
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MALARIA INHIBITOR DISCOVERY
Jenwitheesuk/ Van Voorhis/Rivas/Chong/Weismann
Trends in Pharmacological Sciences, 2010.
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MALARIA INHIBITOR DISCOVERY
COMPARISON OF APPROACHES
Multitarget computational protocol 2,344
compounds simulation 16
top predictions
experiment 6 ED50 1 µM
High throughput protocol 1 2,687 compounds
high throughput
screen 19 ED50 1 µM
High throughput protocol 2 2,160 compounds
high throughput
screen 36 ED50 1 µM
Computational protocol 1 241,000 compounds
simulation 84 top
predictions
experiment 4 ED50 10 µM
In comparison to other approaches, including
experimental high throughput screens, our
multitarget docking with dynamics protocol
combining theory and experiment is more efficient
and accurate.
Computational protocol 1 355,000 compounds
simulation 100 top
predictions
experiment 1 ED50 10 µM
Jenwitheesuk/Van Voorhis/Rivas
Trends in Pharmacological Sciences, 2010.
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DENGUE INHIBITOR DISCOVERY
Jenwitheesuk/Michael
PLoS Neglected Tropical Diseases, 2010.
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SHOTGUN MULTITARGET DOCKING WITH DYNAMICS
ALL KNOWN DRUGS (5,000 FROM FDA)

ALL TARGETS WITH KNOWN STRUCTURE (5,000-10,000)
MACHINE LEARNING
Docking with dynamics Fragment based Multitargetin
g Use of existing drugs Drug/target maching
learning matrix PK/ADME/bioavailability/toxicity/e
tc. Biophysics knowledge iteration Fast track
to clinic (paradigm shift) Cocktails/NCEs/optimisa
tion Translative atomic ? clinic
herpes, malaria, dengue HIV, HBRV,
XMRV hepatitis C, dental caries
CLINICAL STUDIES/APPLICATION
M Lagunoff (UW), W Van Woorhis (UW), S Michael
(FCGU), J Mittler/J Mullins (UW), G Wong/A
Mason/L Tyrell (U Alberta), W Chantratita/P
Palittapongarnpim (Thailand)
DISCOVER NOVEL OFFLABEL USES OF MAJOR THERAPEUTIC
VALUE
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CONCLUSION High risk endeavour is successful if
one or more diseases currently without an
effective treatment can be treated completely.
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ACKNOWLEDGEMENTS

• Rob Braiser
• Renee Ireton
• Shu Feng
• Sarunya Suebtragoon
• Shing-Chung Ngan
• Shyamala Iyer
• Siriphan Manocheewa
• Somsak Phattarasukol
• Tianyun Liu
• Vanessa Steinhilb
• Vania Wang
• Yi-Ling Cheng
• Zach Frazier

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ACKNOWLEDGEMENTS

• Budget
• US1 million/year total costs

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PROSPECTIVE PRELIMINARY VERIFICATION
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HERPESVIRUS PROTEASE DRUG OPPORTUNITY

• All these three viruses cause life-threatening
  diseases in immunocompromised patients.
• HSV drugs alone represent a gt 2 billion dollar
  yearly market and growing at a 10 rate. Nearly
  90 million people worldwide are infected with the
  genital herpes virus, and about 25 million of
  them suffer frequent outbreaks of painful
  blisters and sores.
• CMV is a major cause of mortality in transplant
  patients, and drugs against it represent a 300
  million dollar yearly market.
• Acylovir and related drugs are all nucleoside
  analogues/inhibitors whose patents will soon
  expire. Our protease inhibitor is a novel type of
  anti-herpes agent that may be used in combination
  therapy.
• The inhibitor has been evaluated in mouse models
  of cancer and found to very nontoxic. Inhibitor
  can be modified.
• Topical applications are therefore possible with
  a high likelihood of success.

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PLATFORM OPPORTUNITY
Partner with Biotech, Pharma to work on their
libraries of compounds, targets, diseases (be a
hired gun, share revenue). Apply platform a set
of first world diseases with potential for large
revenue, patent findings, and license the
findings out. Platform may be applied as a
separate company or as a SRA with UW (similar to
Pioneer Award budget). Keep drug/target
interaction matrix a trade secret. License new
uses OR license modifications of those drugs OR
both. Update above list as new drugs and new
targets are identified, so a constant set of hits
and leads will be available for patenting and
licensing. ???
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BUSINESS ACTIVITIES

• Have WA corporation 3D Therapeutics, Inc.
  Nominal CEO Jason North.
• Board currently includes Perry Fell (cofounder of
  Seattle Genetics) and Sonya Erickson (Cooley).
• Scientists include Michael Lagunoff, Wesley van
  Voorhis, Roger Bumgarner, and Ram Samudrala.
• License for first generation platform and
  hits/leads somewhat negotiated with the UW.
• Patents
• Michael SF, Isern S, Garry R, Costin J,
  Jenwithesuk E, Samudrala R. Optimized dengue
  virus entry inhibitory peptide (DN81).
  Priority/filing date July 13, 2007.
• Jenwitheesuk E, Lagunoff M, Van Voorhis W,
  Samudrala R. Compositions and methods for
  predicting inhibitors of protein targets.
  Priority/filing date July 6, 2007.

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ADVANTAGES OF OUR APPROACHES
Probabily of success is higher Multitarget
inhibition Mechanism of action is known Use of
preapproved drugs Side effects may be predicted
Costs are reduced Computational discovery Use
of preapproved drugs Lower number of failed drugs
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PROTEIN INHIBITOR DOCKING WITH DYNAMICS
HIV protease
Jenwitheesuk
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ACCURACY COMPARISON
Bernard Samudrala. Proteins (2009).
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BACKGROUND AND MOTIVATION
My research on protein and proteome structure,
function, and interaction is directed to
understanding how genomes specify phenotype and
behaviour my goal is to use this information to
improve human health and quality of
life. Protein functions and interactions are
mediated by atomic three dimensional structure.
We are applying all our structure prediction
technologies to the area of small molecule
therapeutic discovery. The goal is to create a
comprehensive in silico drug discovery pipeline
to increase the odds of initial preclinical hits
and leads leading to significantly better
outcomes downstream in the clinic. The
knowledge-based drug discovery pipeline will
adopt a shotgun approach that screens all known
FDA approved drug and drug-like compounds against
all known target proteins of known structure,
simultaneously examining how a small molecule
therapeutic interacts with targets, antitargets,
metabolic pathways, to obtain a holistic picture
of drug efficacy and side effects. Find new uses
for existing drugs that can be used in the
clinic, with a focus on third world and neglected
diseases with poor or nonexisting treatments.
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MULTITARGET DOCKING WITH DYNAMICS
Disease target identification
NOVEL FRAGMENT BASED

TRADITIONAL SINGLE MULTITARGET SCREENING
TARGET SCREENING
Single disease related protein
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WHY WILL IT WORK
Fragment based docking with dynamics dynamics
improves accuracy fragmentation exploits
redundancy in existing drugs most accurate
docking protocol out there. Use of existing
drugs exploits all the knowledge from
Pharma. Multitargeting multiple low Kd can work
synergistically screening for targets and
antitargets simultaneously. Knowledge based
potential from known structures, will have a big
matrix relating drugs, targets, PK, ADME,
solubility, bioavailability, toxicity, etc. rich
dataset for combining our biophysics based
methods with machine learning tools in an
iterative manner.
Targets with known structure
docking score, Kd, PK, ADME, absorption,
bioavailability, toxicity
Known drugs
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BROADER IMPACT
Multiple drugs can be combined to produce
therapeutic effect and overcome disease
resistance. Good for any condition where one or
more viable targets exist. Harnesses the power
of all the drug discovery done thusfar new
paradigm for fast track FDA approval Translationa
l approach goes from providing atomic mechanistic
detail to measuring clinical efficacy in one
shot. Protocol can be used to design novel drugs
also.
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SUITABILITY FOR THE PIONEER AWARD
Not good for Pharma because of reuse of existing
drugs (most profit in novel compounds) Not good
for Pharma because of focus on third
world/neglected diseases. Not good for Pharma
because of nonfocus on single target model they
love. Marked departure from my protein structure
prediction work, but now applied research from
basic protein folding to producing therapeutics
in a clinic. Funding will help focus work on
drug discovery which until now has been done on a
shoestring.