ppt

1. Structural Bioinformatics
in Drug Discovery
Melissa Passino

2. Structural Bioinformatics
• What is SBI?
“Structural bioinformatics is a subset of
bioinformatics concerned with the use
of biological structures – proteins, DNA,
RNA, ligands etc. and complexes thereof
to further our understanding of
biological systems.”
http://biology.sdsc.edu/strucb.html

3. SBI in Drug Design and Discovery
• SBI can be used to examine:
• drug targets (usually proteins)
• binding of ligands
↓
“rational” drug design
(benefits = saved time and $$$)

4. Traditional Methods of Drug Discovery
natural
(plant-derived)
treatment for
illness/ailments
↓
isolation of active
compound
(small, organic)

5. synthesis
of compound
↓
manipulation of
structure to get
better drug
(greater efficacy,
fewer side effects)
Aspirin

6. Modern Methods of Drug Discovery
What’s different?
• Drug discovery process begins
with a disease (rather than a treatment)
• Use disease model to pinpoint
relevant genetic/biological
components (i.e. possible drug targets)

7. Modern Drug Discovery
disease → genetic/biological target
↓
discovery of a “lead” molecule
- design assay to measure function of
target
- use assay to look for modulators of
target’s function
↓
high throughput screen (HTS)
- to identify “hits” (compounds with
binding in low nM to low μM range)

8. Modern Drug Discovery
small molecule hits
↓
manipulate structure to increase potency
i.e. decrease Ki to low nM affinity
↓
*optimization of lead molecule into candidate drug*
fulfillment of required pharmacological properties:
potency, absorption, bioavailability, metabolism, safety
↓
clinical trials

9. Interesting facts...
• Over 90% of drugs
entering clinical
trials fail to make it
to market
• The average cost
to bring a new
drug to market is
estimated at $770
million

10. Impact of Structural Bioinformatics
on Drug Discovery
Genome Gene Protein HTS Hit Lead Candidate Drug
Genomics
Bioinformatics
Structural Bioinformatics
Chemoinformatics
Structure-based Drug Design
ADMET Modelling
• Speeds up key steps in
DD process by combining
aspects of bioinformatics,
structural biology, and
structure-based drug
design
Fig 1 & 2
Fauman et al.

11. Identifying Targets:
The “Druggable Genome”

12. human genome
polysaccharides lipids nucleic acids proteins
Problems with toxicity, specificity, and
difficulty in creating potent inhibitors
eliminate the first 3 categories...

13. human genome
polysaccharides lipids nucleic acids proteins
proteins with
binding site
“druggable genome” = subset of genes which
express proteins capable of binding small drug-like
molecules

14. Relating druggable targets
to disease...
GPCR
STY kinases
Zinc peptidases
Serine
proteases
PDE
Other 110
families
Cys proteases
Gated ion-
channel Ion channels
Nuclear
receptor
P450 enzymes
Analysis of pharm
industry reveals:
• Over 400 proteins
used as drug targets
• Sequence analysis of
these proteins shows
that most targets fall
within a few major
gene families
(GPCRs, kinases,
proteases and
peptidases)
Fig. 3, Fauman et al.

15. Assessing Target Druggability
• Once a target is defined for your
disease of interest, SBI can help
answer the question:
Is this a “druggable” target?
• Does it have sequence/domains similar to
known targets?
• Does the target have a site where a drug
can bind, and with appropriate affinity?

16. Other roles for SBI in drug discovery
• Binding pocket modeling
• Lead identification
• Similarity with known
proteins or ligands
• Chemical library design /
combinatorial chemistry
• Virtual screening
• *Lead optimization*
• Binding
• ADMET

17. SBI in cancer therapy:
MMPIs

18. • Inability to control metastasis is the
leading cause of death in patients
with cancer (Zucker et al. Oncogene. 2000, 19,
6642-6650.)
• Matrix metalloproteinase inhibitors
(MMPIs) are a newer class of cancer
therapeutics
• can prevent metastasis (but not cytotoxic);
may also play role in blocking tumor
angiogenesis (growth inhibition)
• Used to treat “major” cancers: lung,
GI, prostate

19. What is an MMP?
• Family of over 20 structurally related
proteinases
• Principal substrates:
• protein components of extracellular matrix
(collagen, fibronectin, laminin, proteoglycan
core protein)
• Functions:
• Breakdown of connective tissue; tissue
remodeling
• Role in cancer:
• Increased levels/activity of MMPs in area
surrounding tumor

20. Brown PD. Breast Cancer Res Treat 1998, 52, 125-136.

21. Whittaker et al. Chem. Rev. 1999, 99, 2735-2776

22. MMP-1,3,8
MMP-2
MMP-7
MMP-9
MMP-10 to 13,19,20
MMP-14
to 17
Whittaker et al. Chem. Rev. 1999, 99, 2735-2776

23. Whittaker et al. Chem. Rev. 1999, 99, 2735-2776
“metallo” in MMP = zinc
→ catalytic domain contains 2 zinc atoms
MMP catalysis

24. Peptidic inhibitors
• Structure based
design
– based on natural
substrate collagen
– zinc binding group
• Poor Ki values, not
very selective
(inhibit other MPs)
Brown PD. Breast Cancer Res Treat 1998, 52, 125-136.

25. Peptidic hydroxamate inhibitors
• Specificity for
MMPs over
other MPs
• Better binding
(low nM Ki)
• But poor oral
bioavailability

26. A (not very) long time ago,
in a town (not too) far away…
…lived a company
named Agouron…
…and this company
had a dream, a
dream to design a
nonpeptidic
hydroxamate
inhibitor of MMPs…

27. ...so they made some special crystals…
used x-ray
crystallography/3D
structure of
recombinant human
MMPs bound to
various inhibitors
↓
to determine key a.a.
residues, ligand
substituents needed
for binding Gelatinase A
http://www.rcsb.org/pdb/

28. …and used the magic of structural
bioinformatics to design many, many
nonpeptidic hydroxylates.
oral
bioavailabity
Ki
anti-
growth
anti-
metastasis
repeat…

29. Results…
AG3340
“Prinomastat”
• Good oral
bioavailability
• Selective for
specific MMPs
– may implicate their
roles in certain
cancers

30. Prinomastat
• Evidence showing prevention of lung
cancer metastasis in rat and mice models
• Clinical trials
→ non small cell lung cancer
→ hormone refractory prostate cancer
…stopped at Phase 3 (Aug 2000) because
did not show effects against late stage
metastasis

31. Morals of the story…
• SBI can be used as basis for lead
discovery and optimization
• MMPs are good targets for chemotherapy
to help control metastasis…
…but MMPIs must be combined with other
cytotoxic drugs to get maximum benefits,
and used at earliest stage possible