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How Difficult Is It to
Discover
Discover
New
New
Novel
Antibacterials?
Lynn L. Silver, Ph.D.
LL Silver Consulting, LLC
2
Antibacterials at FDA 2000-2011
Compound
Usage
Class
Active versus
resistance
Discovery of
class
Linezolid
Systemic IV/oral
Oxazolidinones
MRSA
1978
2000
Ertapenem
Systemic IV/IM
Carbapenem
1976
2001
Cefditoren
Systemic oral
Cephalosporin
1948
2001
Gemifloxacin
Systemic oral
Fluoroquinolone
1961
2003
Daptomycin
Systemic oral
Lipopeptide
MRSA
1987
2003
Telithromycin
Systemic oral
Macrolide+
EryR S. pneumo
1952
2004
Tigecycline
Systemic IV
Tetracycline+
TetR
1948
2005
Faropenem
Systemic oral
Penem
Retapamulin
Topical
Pleuromutilin
Dalbavancin
Systemic IV
Glycopeptide
1953
Doripenem
Systemic IV
Carbapenem
1976
Oritavancin
Systemic IV
Glycopeptide+
VRE
1953
2008
Cethromycin
Systemic oral
Macrolide+
EryR S. pneumo
1952
2009
Iclaprim
Systemic IV
Trimethoprim+
TrmR
1961
2009
Besifloxacin
Ophthalmic
Fluoroquinolone
Telavancin
Systemic IV
Glycopeptide+
Ceftobiprole
Systemic IV
Ceftaroline
Fidaxomicin
1978
MRSA
Fail at FDA
Pass at FDA
2006
1952
2007
2007
2007
1961
2009
VRE
1953
2009
Cephalosporin+
MRSA
1948
Systemic IV
Cephalosporin+
MRSA
1948
2010
Oral CDAD
Lipiarmycin
1975
Due soon
2009
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Discovery Timeline
Last novel agent to reach the
clinic was discovered in 1987
Fidaxomicin
Retapamulin
2005
Linezolid
Bactroban
daptomycin
monobactams
1995
1930
sulfonamide
penicillin
2000
Daptomycin
Synercid
1990
1985
Norfloxacin
Imipenem
1980
lipiarmycin
oxazolidinones
cephamycin
1975
carbapenem
fosfomycin
1970
mupirocin
lincomycin
fusidic acid
1965
metronidazole
novobiocin
nalidixic acid
cycloserine
1960
trimethoprim
isoniazid
rifamycin
1955
erythromycin
vancomycin
cephalosporin
streptogramins
1950
pleuromutilin
bacitracin
chlortetracycline
chloramphenicol
1945
polymyxin
streptomycin
1940
1935
2010
Although development and
modification of old classes
has proceeded – no newly
discovered novel classes have
made it to the clinic in 24 years
4
Discovery Strategies
2010
2005
2000
1995
1990
1985
1980
1975
1970
1965
1960
1955
1950
1945
1940
1935
Screening for and design of novel
antibacterials was vigorously
pursued by Big Pharma until recently
5
Consider…


If Big Pharma (and biotechs) have been largely
unsuccessful in finding novel antibacterials to
develop…
Will that be reversed by




Increasing financial incentives?
Revising regulatory policy?
What has prevented novel discovery?
The need to address scientific obstacles
6
Genomics
Gene-to-Drug Approach
Novel antibacterial targets
High Throughput Screening
Inhibit the enzyme
Smallmolecule
molecule ‘Hits’
Small
‘Hits’
Inhibit bacterial growth
Inhibit bacterial growth by
inhibiting the enzyme
Druglike properties
Low resistance potential
Smallmolecule
molecule ‘Leads’
Small
‘Leads’
ez
ez ab
ab
Candidates
Candidates
Preclinical testing
Clinical Trials
Drug
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The Obstacles to Antibacterial Discovery

Improve chemical sources




Remove toxic, detergent, reactive compounds from
libraries
Define physicochemical characteristics specifying bacterial
entry & efflux
Revive natural product screening
Pursue targets with low resistance potential
8
-lactams
Glycopeptides
Cycloserine
Fosfomycin
The bacterial entry problem
gram positive
Cytoplasm
Rifampin
Aminoglycosides
Tetracyclines
Chloramphenicol
Macrolides
Lincosamides
Oxazolidinones
Fusidic Acid
Mupirocin
Novobiocin
Fluoroquinolones
Sulfas
Trimethoprim
Metronidazole
Daptomycin
Almost all “gram positive”
Polymyxin
drugs are active (biochemically)
on the analogous gram negative targets –
but the drugs are not antibacterial vs gram negatives
P. Aeruginosa is more
problematic due to
strong efflux and
reduced permeability
Periplasm
CM
Gram
negative
P. aeruginosa
Cytoplasm
Impermeability
and efflux of Grender many
agents inactive
CM
OM
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Antibacterials Useful in
Targets Systemic
with low Monotherapy
resistance potential
ANTIBACTERIAL
-lactams
 Examine
TARGET
multiple penicillin binding proteins [PBPs]
successful
antibacterials
synthesis
of cell wall peptidoglycan
Glycopeptides
Tetracycline
Aminoglycosides
Macrolides
Lincosamides
Chloramphenicol
Oxazolidinones
Fluoroquinolones
Metronidazole
Daptomycin
D-ala-D-ala of peptidoglycan substrate
rRNA of 30s ribosome subunit
rRNA of 30s ribosome subunit
rRNA of 50s ribosome subunit
rRNA of 50s ribosome subunit
rRNA of 50s ribosome subunit
rRNA of 50s ribosome subunit
bacterial topoisomerases (gyrase and topo IV)
DNA
membranes
enzymes
All have multiple targets or targets encoded by multiple genes
No high-level resistance by single-step mutation
10
Single Enzyme Targets of Antibiotics in
Clinical Use
ANTIBIOTIC
TARGET
USE
rifampicin
RNA polymerase
Multi-drugTB therapy
isoniazid
InhA
Multi-drug TB therapy
streptomycin
30s ribosome/rpsL
Multi-drug TB therapy
trimethoprim
DHFR (FolA)
Combo w/ Sulfas
sulfamethoxazole
PABA synthase (FolP)
Combo w/ Trimethoprim
novobiocin
DNA gyrase B subunit
Multi-drug therapy
mupirocin
Ile tRNA-synthetase
Topical therapy
fosfomycin
MurA
UTI
All are subject to single-step high level resistance
11
Based on existing antibacterial drugs…

Successful monotherapeutic antibacterials


Not subject to single-site mutation to high level resistance
because they are multi-targeted
Current drugs inhibiting single enzymes

Generally used in combination
because they are subject to single mutation to significant resistance
THUS: "Multitargets" are preferable to single enzyme
targets for systemic monotherapy
BUT:
The search for single enzyme inhibitors has been the
mainstay of novel discovery for at least 20 years …
12
If single enzyme targets give rise to
resistance in the laboratory…

Determine if the in vitro (laboratory) resistance
is likely to translate to resistance in the clinic
Standardize the use of models for evolution of
resistance under therapeutic conditions
 To validate targets, test target/lead pairs in these
models


Pursue multitargets
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A way forward

Targets



Chemicals





For single-enzyme inhibitors: Robust modeling of resistance
Pursue multi-targets
Deduce rules for bacterial entry and efflux, especially in GClean up libraries and incorporate rules for entry
Revive Natural Products
With better chemicals, return to empirical discovery
Collaboration between academe and industry



Computation for multitargeting
Modeling of resistance
Chemistry for cell entry and efflux avoidance
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15
Antibacterials Are Chemically Unlike
other Drugs
gram negative
gram positive only
cLogD7.4 = GREASINESS
other drugs
MW = SIZE


Mammalian targets ≠ antibacterial targets
Many antibacterials must enter bacterial cells
+
16
Cytoplasm-targeted antibacterials
8.0
Gram positive only
Cytoplasmic
6.0
Gram negative cytoplasmic
entry by diffusion
cLogP = Greasiness
4.0
2.0
0.0
-2.0
Gram negative cytoplasmic
carrier-mediated transport
-4.0
-6.0
0
200
400
600
MW = SIZE
800
1000
1200
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An approach to new multitargets:
Sorting targets by their ligands

Compound and fragment profiling
binding/docking to bacterial proteins
Can be done computationally
Candidate multitargets
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What is Antibacterial Multitargeting?
Targeting the products of multiple genes – or the product
of their function – such that single mutations cannot lead
ciprofloxacin
to high level resistance





Two or more essential gene products with
similar active sites: DNA Gyrase & Topisomerase IV
Gyrase
Topo IV
Products of identical genes : rRNA
gentamicin
tetracycline
Essential structures produced by a pathway where
chloramphenicol
linezolid
structural changes cannot be made by single
erythromycin
mutations:
Membranes
Lipid II
GlcNAc
These and other known multiargets have beenMurNAc
pursued
PP-C
More may be uncovered by computation based on structural
vancomycin
studies of bacterial proteins
and the small molecule “ligands”
daptomycin
that bind to them
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