Drug
Discovery
Done
Differently
      David
L.
Pompliano,
PhD
                CEO

What we doBioLeap delivers custom-made, pre-clinical drug leads andcandidates, in collaboration or as a service.Enabled by...
Many targets do not yield to the “process”Lead identification and optimization is a time-consuming andinefficient process ...
BioLeap changes the approach from trial-correlate todesign- confirm.          BioLeap’s hypothesis-driven design process  ...
Fragment-based ligand design      HT screening hit: asking too much all at once         1.  Find small, but highly specifi...
Tight-binding drugs are composed of weak-bindingfragments                                                   6
The
BioLeap
Technology


       Chemical
diversity
    Design‐centered
process
Predic@ve
ranking
of
compounds
            ...
Insufficient chemical diversity for screening (or anunwillingness to work on weak hits)                                   ...
Chemical diversity: combinatorial chemistry with   fragments known to bind to the target                                  ...
BioLeap’s technology enables our chemists to expandtheir role as drug designers protein-       ligand- centric        cent...
We create a map of where, and with what affinity, smallchemical building blocks bind                                      ...
Tools to rapidly assemble diverse fragments into novelcompounds of predictable binding affinity         Chemists know whic...
Predictable binding using BioLeap’s in silico annealingprocess                                      J.
Med.
Chem.
2002,
45...
No predictability using conventional docking
GSK molecular modelers conclude that computational   methods are not predictive A Critical Assessment of Docking Programs ...
In a blinded test with big pharma, BioLeap correctly ranked87% of predicted binding affinities                            ...
BioLeap controls key attrition factors  •  Biology: Target affinity and selectivity  •  Developability: Physicochemical pr...
BioLeap’s methodology is target-class independent •  Kinases                                        •  Oxygenases/Reductas...
BioLeap transforms economics of drug discovery            Comparison of Time and Resources Required to Produce a Developme...
Custom-built, ligand-efficient compoundswith a past and a future.•  Targets for which HTS methods have failed to produce n...
Extras         21
Leads are hard to find, and then the trouble starts                     • 
Clairvoyance

                     • 
Tenacity
...
What if the ideal position of the fragment is notconsistent with chemical synthesis?               Only two obvious connec...
Ligand-centric design: force constraints                                                      Design ligand   Constrain li...
Alternative designs are possible: choose based onranking and synthetic feasibility                                        ...
Control physicochemical properties and mode of target engagementAutomated
search
for
fragments
  sa@sfying
bond
geometries...
The goal of HTS             +                  27
Upcoming SlideShare
Loading in …5
×

Bio leap InnoCos Europe, Paris

946 views

Published on

BRINGING LEADING EDGE PHARMACEUTICAL CAPABILITIES TO COSMETICS
Novel IP Faster time to market Collaboration opportunities David Pompliano, CEO, Bioleap Inc

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
946
On SlideShare
0
From Embeds
0
Number of Embeds
258
Actions
Shares
0
Downloads
22
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Bio leap InnoCos Europe, Paris

  1. 1. Drug
Discovery
Done
Differently
 David
L.
Pompliano,
PhD
 CEO

  2. 2. What we doBioLeap delivers custom-made, pre-clinical drug leads andcandidates, in collaboration or as a service.Enabled by computational fragment-based methods, we designnovel compounds of unrestricted chemical diversity that bind totheir target with predictable affinities.By minimizing unproductive guesswork, we achieve pre-clinicalmilestones in shorter times and provide better value compared tocurrent methods. 2
  3. 3. Many targets do not yield to the “process”Lead identification and optimization is a time-consuming andinefficient process with low probability of successThe GSK Antibacterial Experience Combi Medicinal KO’s 70 HTS’s chem chem Validated Targets Hits Leads Candidates Targets >360 ~160 26 5 0 Predicted essentialThere has got to be a better way.Source: Payne, Gwynn, Holmes & Pompliano Nature Rev. Drug Discov., 2007 6, 29-40. 3
  4. 4. BioLeap changes the approach from trial-correlate todesign- confirm. BioLeap’s hypothesis-driven design process reduces compound attrition. 4
  5. 5. Fragment-based ligand design HT screening hit: asking too much all at once 1.  Find small, but highly specific, fragments 2.  Link them together (synergistic binding)
  6. 6. Tight-binding drugs are composed of weak-bindingfragments 6
  7. 7. The
BioLeap
Technology


 Chemical
diversity
 Design‐centered
process
Predic@ve
ranking
of
compounds
 7
  8. 8. Insufficient chemical diversity for screening (or anunwillingness to work on weak hits) 8
  9. 9. Chemical diversity: combinatorial chemistry with fragments known to bind to the target We DON’T screen !BioLeap custom-builds novel-structure ligands from fragmentbuilding blocks that calculations show already bind to the target. Chemotype substitution sites for Imatinib # of chemical # of # of = Possible moieties substitutions sites Combinations per site 100 3 5 = 2.4T 100 3 4 = 8.1B 100 3 3 = 27M
  10. 10. BioLeap’s technology enables our chemists to expandtheir role as drug designers protein- ligand- centric centric Constrained Fragment Fragment Drug BioLeap’s 3DBinding Map Designers Design Tools Annealing
  11. 11. We create a map of where, and with what affinity, smallchemical building blocks bind movie Immerse protein Anneal µ Isolated binding Lowest free energy, sites revealed highest affinity site A thermodynamically-principled model upon which to frame molecular design hypotheses 11
  12. 12. Tools to rapidly assemble diverse fragments into novelcompounds of predictable binding affinity Chemists know which compounds to make next ! 12
  13. 13. Predictable binding using BioLeap’s in silico annealingprocess J.
Med.
Chem.
2002,
45,
2994‐3008

  14. 14. No predictability using conventional docking
  15. 15. GSK molecular modelers conclude that computational methods are not predictive A Critical Assessment of Docking Programs and Scoring Functions Gregory L. Warren,*,† C. Webster Andrews,‡ Anna-Maria Capelli,# Brian Clarke,| Judith LaLonde,†,§ Millard H. Lambert,‡ Mika Lindvall,^,b Neysa Nevins,† Simon F. Semus,† Stefan Senger,^ Giovanna Tedesco,# Ian D. Wall,| James M. Woolven,^ Catherine E. Peishoff,† and Martha S. Head† GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, GlaxoSmithKline, Five Moore Drive, Research Triangle Park, North Carolina 27709, GlaxoSmithKline, Centre via Alessandro, Fleming 4, 37135, Verona, Italy, GlaxoSmithKline, New Frontiers Science Park, Third Avenue, Harlow, Essex CM19 5AW, U.K., and GlaxoSmithKline, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K. Received April 17, 2005 Docking is a computational technique that samples conformations of small molecules in protein binding sites; scoring functions are used to assess which of these conformations best complements the protein binding site. An evaluation of 10 docking programs and 37 scoring functions was conducted against eight proteins of seven protein types for three tasks: binding mode prediction, virtual screening for lead identification, and rank-ordering by affinity for lead optimization. All of the docking programs were able to generate ligand conformations similar to crystallographically determined protein/ligand complex structures for at least one of the targets. However, scoring functions were less successful at distinguishing the crystallographic conformation from the set of docked poses. Docking programs identified active compounds from a pharmaceutically relevant pool of decoy compounds; however, no single program performed well for all of the targets. For prediction of compound affinity, none of the docking programs or scoring functions made a useful prediction of ligand binding affinity. 15J. Med. Chem. 2006, 49, 5912-5931
  16. 16. In a blinded test with big pharma, BioLeap correctly ranked87% of predicted binding affinities -5 -4 Experimental
pIC50
 -3 -2 -1 0 0 -10 -20 -30 -40 -50 Predicted
Free
Energy
 16
  17. 17. BioLeap controls key attrition factors •  Biology: Target affinity and selectivity •  Developability: Physicochemical properties For MW, lower is better: 17 Source: J. Med Chem. 2003, 46, 1250-6.
  18. 18. BioLeap’s methodology is target-class independent •  Kinases •  Oxygenases/Reductases –  Mapkap-k2 (5 variants) –  Dihydrofolate reductase –  P38 (3 variants) –  CpI hydrogenase –  cAbl (2 variants) –  Cox1/Cox2 –  Ckit –  IDO –  PhoQ Histidine kinase •  Receptors –  Proprietary kinases (3) –  EPO receptor –  JAK2/JAK3 –  NOGO •  Proteases and Hydrolytic •  Macromolecular Interactions Enzymes –  Protein/DNA complex –  Elastase: PPE, HNE serine proteases –  P53/MDM2 –  Peptide deformylase –  BPTI (trypsin proteinase inhibitor) –  T4 lysozyme –  FABP4 –  peptidyl t-RNA hydrolase –  Fcrn (peptide mimetic) •  Nuclear Hormone Receptors •  Other Classes –  ROR-alpha –  NS5B RNA polymerase –  LXR –  M2 proton pump –  Amino transferaseIn silico validation vs. known ligand –  Keap1Results confirmed experimentally, or in progress –  Arginase 18
  19. 19. BioLeap transforms economics of drug discovery Comparison of Time and Resources Required to Produce a Development Candidate BioLeap Lead Candidate•  150 compounds 3 Cycles 2 Cycles Safety•  30 months Design / Test Design / Test pharm.•  Minimal infrastructure•  Library independent•  Broad diversity Year 1 Year 2 Year 3 Year 4 Pharma•  2,000 compounds HTS Assay Development Hit to Lead Lead Optimization Safety•  48 months Reagent Prep Chemistry pharm.•  Big infrastructure HTS•  Library dependent Hit Confirmation•  Limited diversity Lead Candidate 19
  20. 20. Custom-built, ligand-efficient compoundswith a past and a future.•  Targets for which HTS methods have failed to produce new lead compounds•  Targets where lead optimization efforts have stalled for a lack of understanding of the structure-activity relationship in the lead series•  Expand/bust a patent•  Develop a fast follower of an early stage clinical compounds 20
  21. 21. Extras 21
  22. 22. Leads are hard to find, and then the trouble starts • 
Clairvoyance

 • 
Tenacity
 • 
Regulatory
stability
 Discovery
~
8
y
 Development
~
5.5
y
 “Valley
of
Death”
 Finding
a
 Lead
op
to
 lead
 produce
DC
 22
  23. 23. What if the ideal position of the fragment is notconsistent with chemical synthesis? Only two obvious connections 23
  24. 24. Ligand-centric design: force constraints Design ligand Constrain link to amide Calculate FE with applied constraints Constrain bond to N-atom and fuse Constrained Fragment Annealing 24
  25. 25. Alternative designs are possible: choose based onranking and synthetic feasibility 25
  26. 26. Control physicochemical properties and mode of target engagementAutomated
search
for
fragments
 sa@sfying
bond
geometries
 Design
for
selec@vity,
reduced
 muta@on
resistance 
 Non‐obvious
ideas
for
lead
 op@miza@on 
 Access
vast
chemical
diversity
 by
linking
combina@ons
of
 op@mal
fragments 
 Exploit
moie@es
with
strong
 interac@ons
with
the

backbone
 or
conserved
amino
acid
residues
 Circumven@ng
the
SAR
paradox,
avoiding
 penal@es
from
@ghtly‐bound
waters 

  27. 27. The goal of HTS + 27

×