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An overview of the drug discovery process
“Hit to Lead”
Nature Review Drug Discovery,8, 892 2009.
2
From Hit to Lead Hits from HTS screening- may have many
potential scaffolds
Hit-to-lead involves synthesis of many compounds to determine what is important
Need to see if there is room to improve the compound
NN
NN NH
Synthesis
HTS HIT/Natural Product
Essential scaffold
Synthesis
Potential lead compound
3
Hit to lead – fragment evolution
Nature Reviews Drug Discovery 3, 660-672 (August 2004)
Fragment evolution – aided by structure of fragment in the protein
Essential fragment
Synthesis to increase potencyPotential lead
compound
N
N
N
Hits from Fragment based screening- may have many potential scaffolds
Hit-to-lead involves synthesis to expand the core to move from binding to activity
Most efficient when aided by structure-based methods
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From Hit to Lead For a hit to become a lead it must:
Show structure-activity relationships (SAR)
Activity should be sensitive to structure
Losing activity is NOT a negative result!
The compound should have handles for reactivity
Able to modify
Most scaffolds are retained during optimization
Compounds should be simple
Stereocenters = cost
Should show activity in a cellular assay (or in vivo)
Can your hits get into a cell or a target tissue?
Should show lead-like molecular properties
Expedite and simplify further optimization
5
Lead Optimization
Nat Rev Drug Disc 2, 369-78, 2003
Medicinal chemistMedicinal chemist
In vivo efficacy is key
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An overview of the drug discovery process
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Medicinal Chemistry Refinement
Synthesis of compounds
Screen for activity AND/OR
Screen against activity AND/OR
Screen for ADME
Data Analysis (SAR trends)
Refinement of criteria
Planning
Many compounds must be made! What are the strategies used for efficient synthesis? What tools
are in the chemists’ synthetic toolbox?
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Approaches to synthesis - discovery
Compounds are made in bunches, not as single efforts
The more molecules made at once, the better to understand trends in efficacy, physicochemical properties, etc.
If one compound fails to show the expected in vivo pharmacology, others are there to fall back on-
Is it the scaffold?
Is it the target?
Without a variety of lead compounds, you won’t know!
Compounds may show similar activity, but vary greatly in selectivity, or ADME properties
Making series of compounds helps to spot trends to guide future research
Parallel synthesis of groups of compounds made by facile reactions from a common intermediate
Allows response to biological data with the shortest turnaround time possible
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A case study for library design
R. J. Gillespie et al. / Bioorg. Med. Chem. 17 (2009) 6590–6605
N
Cl
ClHO
O
A diversifiable scaffold with three synthetic handles
N
Cl
ClHO
O
N
Cl
ClN
O
R1
R
Facile coupling reactions with commercially available
amines create a library to explore space around this
position
N
R2
ClN
O
R1
R
The more reactive chloride can be
replaced with various groups through carbon-carbon bond formation
N
R2
XN
O
R1
R
The chloride can be substituted with various heteroatoms and groups
Straightforward chemistries and commercial reagents allow for rapid diversification
Prioritization is necessary
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An overview of the drug discovery process
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Synthesis of an active pharmaceutical ingredient (API)
Syntheses that are scalable from gms to kgs
Syntheses that avoids metals, such as Pd
Metal impurities must be minimal in the final compound
Removal of metals can be very expensive
Syntheses that can be purified easily
Salt forms are often used as APIs due to their greater stability and solubility
As the focus of chemistry efforts shift from making a library of many compounds to making large amounts of one compound, strategies change
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Discovery synthesis vs API synthesis: A case study
The chosen compound 5 has a methyl group added in the last step via a Pd catalyzed reaction as part of a parallel chemistry scheme
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Synthetic scheme for compound 5 as an API
W. Hu et al. / Bioorg. Med. Chem. Lett. 17 (2007) 414–418
Methyl group is set early in the synthesis via a
cyclization reaction
“Green chemistry”
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Summary
The path to drug discovery begins with the selection of the library picked for screening
Libraries should be chosen for the same reasons that compounds are chosen later in development
There are a variety of complimentary ways to get hits
Optimization of hits toward clinical candidates
Increase of potency and selectivity
Increase of in vivo efficacy
Maintenance of potency and selectivity; optimization of other factors
Incorporation of drug-like molecular property filters in the front end of discovery facilitates this process
Chemists use standard tools in drug discovery regardless of the therapeutic area
Pattern recognition
Parallel chemistries
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Conclusions
Many factors influence all steps of drug discovery, from choosing how to find a hit to choosing a clinical candidate
Drug discovery chemistry works to find compounds that are potent and selective with ADME properties that forecast in vivo efficacy in the clinic
Discovery synthesis and design should be efficient and make the best compounds possible to guarantee success
Chemistry efforts are led by biological results
Constant communication and feedback between team members of different disciplines gives the best chance to overcome the many obstacles and to succeed in the discovery of an efficacious drug
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Thank you for your attention!
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A structure – toxicity study - A2A antagonists
N N
N
NNH2
O
N
N
O
H3CO
A2A binding: 2.8 nm A1 binding: 601 nm
3mg/kg p.o. efficacious in vivo for anti-cataleptic
activity
Molecular Weight: 449.51log P: 3.33
tPSA: 100.51
hERG inhibition of 81%
Maintain potency and selectivity while decreasing hERG % inhibition
Molecular Weight: 447.53Log P: 2.83tPSA: 91.28
J. J. Matasi et al. / Bioorg. Med. Chem. Lett. 15 (2005) 3670–3674J. J. Matasi et al. / Bioorg. Med. Chem. Lett. 15 (2005) 3675–3678
Natural Products as Drug Starting Points
Frank E. Koehn
6th Drug Discovery for Neurodegeneration
February 13th , 2012
New York, NY
HO
O
NOOO
O
HOO
O
O
OH
R
O
Just What in Fact, is a Natural Product?
~300,000 distinct compounds from microbes, plants, and other organisms
FK-506- fujimycin
Streptomyces tsukubaensis
palytoxin
Palythoa tuberculosum
Cl
OH OHO O
CONH2
OH
OH Me HNMe2
OH
aureomycin
Streptomyces sp.
N
N
H
nicotine
Nicotiana tabacum
Natural products- A major impact on drug discovery
Liberal analysis - 47% of New Chemical Entities 1940-2006 are “Natural Product Derived”
Conservative analysis - 1970-2012 - 58 approved NCE’s came directly from natural products
10% of all drugs over last 10 years (19 of 200)
Native molecules- 27, analogues- 31
Sources: microorganisms> Plants>> marine sources
Unique Challenges with NPs.
Accessibility- synthetic manipulation
NP extracts- Isolation is slow, resource-intensive
Pure NP libraries- difficult to enable
J. Med Chem. 2009, 52 1953-1962, Curr. Opin. in Chem. Biol, 2008, 12:306-31721
Targets, Libraries and Screening Strategies
• Chemical Space - Exceeds 1060 compounds with less than 500 MW
• Not all chemical space is biologically relevant!
• To screen effectively- screen the biologically relevant part of chemical space
• Natural products are privileged (biased to occupy biologically relevant chemical space)
Predicted score plot of NP and medicinally active WOMBAT compounds.
Rosen, et. al.,J. Med. Chem. 2009, 52, 1953–1962
Screening for Lead Generation
Compounds
Biochemical HTS
(Single target)
Target-compound binding
Phenotypic Screening
(many targets)NP chemical Library
Phenotypic response
New target & mechanism
Cell
Target
minutes
AB
SO
RB
AN
CE
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34.
Media components
polar metabolites
& biopolymers
Lipids, fatty acids
non-polar biopolymers
Crude Extract Library
Fractions/extract
Library size per culture
Low
Assay interferences
High
Sample prep Low
Redundancy High
Hit identification Slow
Sensitivity 10X
Pre-fractionated Library
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 0
Moderate
Moderate
Moderate
Moderate
Moderate
100X
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34
Pure Compound Library
Moderate
Low
High
Very Low
Rapid
10 Liter Fermentation
100 Liter Fermentation
optimized
Screening and Natural Products Library Design
The Challenge- Tougher Targets
The Rule of Five (Ro5) has guided the design of compounds into privileged ADME space
MW <500 DaClogP <5HBD <5
HBA (N, O) <10
Good Fraction Absorbed(Solubility,
Permeability)
Low Clearance
OralBioavailability
Excellent strategy for many targets…..But not for targets involving protein-protein
interactions
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The “Druggable” Genome - Hopkins
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Highly “Druggable” targets, Ro5
leads
Disease relevant
“Undruggable” biological targets,
Beyond Ro5 leads
Very Limited Overlap
Hopkins, A.L., Groom, C.R. “The druggable genome” Nat. Rev. Drug Discov., 2002, 1(9) 727-30.
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NP Lead, year NCEs Indication/MOA MW ClogP HBD HBA Oral Bioavaila
bilityDose
Validamycin, 1970
Acarbose, 1990Voglibose, 1994
Anti-diabetic/glucosidase inhibitor 498 -6.2 13 14 25 mg
Midecamycin, 1971 Miocamycin, 1985 Antibacterial/protein
synthesis inhibitors 815 3.5 4 16 100% 600 mg
Rapamycin, 1974
Sirolimus, 1999Everolimus, 2004Zotarolimus, 2005Temsirolimus, 2007
Immune suppression/mTOR 914 7.0 3 14 20% 2 mg
Cyclosporine A, 1975 Cyclosporine, 1983 Immune suppression /IL-2
inhibitor 1203 14.4 5 23 30% 25 mg
Lipstatin, 1975 Orlistat, 1987 Obesity/Lipase inhibitor 492 7.6 1 6 120 mgAvermectin B1a, 1979 Ivermectin, 1987 Antiparasitic/Glutamate-
gated chloride channel 873 5.1 3 14 100% 3 mg
FK506, 1984 Tacrolimus, 1993Immune suppression/T-lymphocyte activation inhibitor
804 5.8 3 13 20% 1 mg
Myriocin Gilenya, 2010 Multiple sclerosis/S1P1 inhibitor 402 2.8 6 7 93% 0.5 mg
Natural Products are Successful Therapeutics in the Beyond Ro5 Space
Selected Orally Active BRo5 Natural Product Drugs
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Recent Synthetic Natural Product Derived Drugs
OHNH2
HO
HO
H2N
O
OH
O
HO
HO
O
O
OO
OO
O
O
O
O
O
O
OO
HOOH
O
O
OH
Myriocin
Mycelia sterilia
Fingolimod
Halichondrin B
Halichondria okadai
Eribulin
HO
HOO
OHStarter acid
HO
HOO
OH
HO
Shikimic acid
rapK
O
OH
OH
O
OH
O
OH
ORHO
S
OH
OH
O
OH
O
OH
ORHO
OSS
OH
O
OH
O
OH
ORHO
O
rapC
Module 11Module 12
Module 13Module 14
SO
O
OH
OH
O
OH
O
ORHO
OH
ACPACP KSAT AT
KRDHER
ACPKS AT
KR
ACPKS AT
KR
KS
RAPS 3
S
O
OH
O
OH
ORHO
OS
O
OH
O
OH
ORHO
O
O
OH
S
O
OH
ORHO
OS
O
OH
O
OH
ORHO
OS
O
OH
O
OH
ORHO
OS
O
OH
O
OH
ORHO
rapB
Module 5Module 6
Module 7Module 8
Module 9Module 10
ACP ACP ACP ACP ACP ACPKS KS KS KS KS KS ATATATATAT
KR KR KR KR KR KRDHDHDHDHDHER
RAPS 2
rapARAPS 1
ORHO
OSH
Loadingdomain
CoL ER ACP
S
ORHO
O
Module 1
ER
ACPKS AT
DH KR
SO
OH
ORHO
Module 2
KS AT ACP
KR
O
OH
ORHO
OS
Module 3
ACP
KRER
DH
ATKS
Module 4
O
OH
ORHO
SO
KS AT ACP
KRDH
X
XHO
O
AlternativeStarter unit
R2R1
methylation and oxidation Pipecolate Incorporating Enzyme
OHNH
O
O OCH3
O
OHOON
OHO
O
OH
OH3CO
OCH3
1) Gregory, M.A. and Leadlay, P.F. et al., Angew. Chem. Int. Ed. 2005, 44, 4757-4760. 2) Gregory, M. A. and Leadlay, P.F. et al., Org. & Biomol. Chem. 2006, 4, 3565-3568.
PKS Engineering of Rapamycin
rapamycin
Rationale for NP Biological Bias is Based on Protein Fold Space Properties
30
Protein sequence space is essentially infinite- at 300 aa, possible sequences = 20300 >>> than particles in known universe (1080)
Total complement of estimated world proteome 1010
Most proteins resemble other proteins - built by amplification, recombination, divergence from a basic set of folding units- domains
Around 100 domain families have been recognized by sequence
Only ca. 1000 folds are populated in nature
Subdomain level - recurrent local arrangements of secondary structures
Biophysical constraints limit the number of folded conformations
Characteristics of Protein folds
• Distinct sequences often adopt very similar folds
• Highly similar sequences can adopt very different folds
• Identical peptide sequences can have different conformations in different proteins
• A single protein chain may encode for more than one structural domain.
• Similar domains are formed via different “methods”
Structure is conserved far more than sequence.
31
Distinct Sequences Often Adopt Very Similar Folds
32
Superposition of 3 proteins of similar structure but distinct sequences.
1-Isomerase from Rhodopseudomonas palustris
2- B chain of limonene-1,2-epoxide hydrolase from Rhodococcus erythropolis
3- Putative polyketide cyclase from Acidithiobacillus ferrooxidans
a) 1 and 2
b) 2 and 3
c) 1 and 3
<20% sequence identity in aligned regions
Regions of overlap in protein 1
Regions of overlap in protein 2
A- Proteins with virtually identical structure and little or no sequence similarity
Current Opinion in Structural Biology 2009, 19:312–320, J Biol Chem 2009, 284:992-999
B- Proteins with high sequence similarity and no structure similarity
Arl2 (BART) from Homo sapiens and ADP-ribosylation factor-like protein 2-binding protein from Danio rerio – 72%
Domains in Related Enzymes can be Formed in Distinctly Different Ways
33
(a) Dimerization domain of GDP-mannose dehydogenase from P.
aeruginosa
(b) Central dimerization domain of UDP-glucose dehydrogenase from S.
pyogenes
(c) Single chain domain of ovine 6-phosphogluconate dehydrogenase
The blue and yellow fragments highlight the correspondence with the
chains shown in (b).
Current Opinion in Structural Biology 2009, 19:312–320
Natural Products Bind Proteins
As substrates for via PKS, NRPS, tailoring enzymes, etc.
Outcome of selective pressure to binding protein and cellular targets
Domains of these fold targets are conserved in the “protein foldome”
Natural product ligands leverage these properties in their mechanism and properties
Natural products, by virtue their origin, are within or at least proximal to, biologically relevant chemical
space.
34
Polyketide Immunophilin Ligand Family
HO
NO
O
HOO
O
OH
OH
OHOH
HO
O
meridamycinnormeridamycin
rapamycin
HO
O
NOOO
O
HOO
O
O
OH
R
O
OCH3
NO
OHO O
CH3OHOO
O
O
OH
O
OCH3
fujimycin (FK-506): R = allylascomycin (FK-520): R = ethyl
HO
HO
N OOO
HOO
O
O O
antascomicin BOH
Immunosuppressive
Non-immunosuppressive
n= 1,0
Salituro, G. et. al., Tet. Lett., 1995, 36(7), 997-1000
Summers, M.Y.; Leighton, M.; Liu, D.; Pong, K.; Graziani, E.I., J. Antibiot., 2006, 59(3), 184-189.
OCH3
NO
OHO O
HOO
O
OH
O
OCH3
H3COO
Natural Products lead to Unanticipated Drug Targets and Mechanisms
FKBP binding
domain
mTOR effector
domain
Sehgal, S.N.; Baker, H.; Vézina, C., J. Antibiot., 1975, 28(10), 721-726.
Choi, J.; Chen, J.; Schrieber, S.L.; Clardy, J., Science, 1996, 273, 239-241.
1. Rapamycin binds tightly to FKPB12 via FKBP binding domain
2. Rapa-FKBP12 complex binds mTOR, disrupting TORC1 complex
mTOR
FKBP-12
RAPAMYCIN
36
Natural products, by virtue their origin, are within or at least proximal to, biologically relevant chemical space!
ILS-920 Promotes Neurite Outgrowth and Neuronal Survival in Cortical Neuron Cultures
Control ILS-920
Control ILS-920
0.5
1
1.5
2
2.5
3
Contro
l0.0
05 0.01
0.05 0.1 0.5 1 5 10
Neu
rofil
amen
t Con
tent
(OD
@ 6
50 n
m)
ILS-920
Ruan, B. et. al. “Binding of rapamycin analogs to calcium channels and FKBP52 contributes to their neuroprotective activities” (2008) Proc. Natl. Acad. Sci. USA, 105(1), 33-38.
O
N
O
OHO O
OOH
O
O
O
OH
O
O
O N
OMe
N
O
OHO O
OH
O
O
OR
O
OMe
MeOO
ILS-920
rapamycin
Varenicline
NN
H
NH
N
NH
N
N
nicotine
Nicotiana tabacumcytisine
Lupinus sp.
Plant Natural Products as Drug Leads- Varenicline
Varenicline
Homo sapiens
39
Summary
Natural products have been, and continue to be a rich source of chemotherapeutics
Natural products are biologically privileged chemical structures with which to attack previously undruggable targets.
Natural products are biologically privileged structures which can be leveraged for new biology and targets.
Complex natural products can access desired drug property space
Acknowledgments
Natural Products/Chemistry Neuroscience/Biology
Benfang Ruan Kevin Pong
Edmund Graziani Mene Pangelos
Leonard McDonald Flora Jow,
Ronald L. Magolda Andrew Wood
Guy Carter Mark Bowlby
Jerauld Skotnicki Peter H. Reinhart
Magid Abou-Gharbia Margaret M. Zaleska
Xidong Feng Danni Liu
Caroline Proul-LaFrance Shi Liang
Jack Bikker Robert A. Crozier
Bruce Rogers Mary Lynn Mercado
Anabella Villalobos Jotham Coe
Brian O’neill David von Schack
Jotham Coe Yi Chen
