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Infectious Diseases Drug Discovery: An AstraZeneca Perspective Tomas Lundqvist GSC LG-DECS AstraZeneca R&D Mölndal Stewart L. Fisher Infection Discovery AstraZeneca R&D Boston AstraZeneca R&D Boston History • • • • AZ’s newest research facility Construction initiated August 1998 (Astra) Building completed March 2000 (AstraZeneca) Three Research Areas – Infection Discovery (Global Center) – Oncology – Discovery Informatics • Building expansion completed 2003 – Increased resourcing for Oncology • Approximately 450 employees • Expansion underway: – $100 mil investment in capital (buildings) – Increased resource for Infection Research Why Focus on Infectious Disease? Medical Need Business Opportunity Social Responsibility Causes of Death 35% 30% Percentage of all deaths worldwide 25% 20% 15% 10% 5% 0% Respiratory Disease Cancers Circulatory Disease Infectious Disease Ref. WHO Data Medical need • 41% of global disease burden is due to infection (WHO, 2002) • Outside EU & US the disease burden from infection is greater than the total of all other therapy areas combined A Major Issue for All The Golden Age & Today The Golden Age of Antibiotic Discovery was very brief, mid 1930s- early 1960s penicillin, cephalosporin, streptomycin, erythromycin, tetracycline, vancomycin The pipeline for new antibacterials is drying up Resistance to antibacterials continues to rise There is a clear & present danger of import to both individual patients and the public health Target Based Approaches • 1990’s: Dominant lead generation approach – – – – “Genomic era” Combinatorial/parallel chemistry = large compound libraries Automated screening technologies provided economy of scale Structural approaches most amenable to bacterial targets • Soluble • High yield overproduction/purification • 2000-present – Approach seen as “not delivering the pipeline” – Many reasons for “failure” • • • • Poor compound libraries (not as clean as envisioned) Difficult to choose the “druggable” targets Enzyme inhibition ≠ antimicrobial activity (efflux) Sufficient patience in the industry? Cell Based Approaches • 1990’s: Diminished activity due to target-based approaches – Hit followup appeared “messy” relative to target based – Identification of novel antibiotics increasingly difficult – Major efforts in combinatorial biosynthesis • Genetic manipulation of natural product producers • 2000-present – renewed interest – Less faith in target based approaches (e.g. lessons from GSK FabI) – Improvements in genomic technologies allows facile hit followup • Regulated gene libraries • Target identification via resistance gene mapping – Automated screening technologies affords novel approaches – Approach amenable to pathways and difficult targets “Look Back” Programs • Revisiting past discoveries, finding new value – – • Ramoplanin, Tiacumicin B – value of C. difficile in 1980s? Daptomycin – value of MRSA in 1980’s Advances in chemistry make intractable scaffolds amenable – – – ADEPs Anisomycin Moiramide Target-Based Approaches: Pipeline Target Identification many (100’s) see genomic patents Hit Identification MurA MurB MurC MurD MurE MurF MurG MurA-F pathway MurG MraY-PBPII pathway DdlB FtsZ FtsZ/ZipA LpxC RNA Polymerase (RNAP) DNA Polymerase (DNAP) DnaB Phe-tRNAS Trp-tRNAS Met-tRNAS GyrB PanK Lead Identification Lead Optimisation Preclinical/ Clinical FabDFGAI pathway FabI AcpS FtsZ Mur Pathway H. pylori MurI Peptide Deformylase GyrB/ParE FabI/K Phe-tRNAS Ile-tRNAS GyrB First Step: Define the Problem Target Product Profile Target Identification Hit Identification Lead Identification Lead Optimisation • Definition of a Target Product Profile – Define the disease & unmet medical need – Set the requirements for the drug – Find targets that fit the requirements Preclinical/ Clinical Therapy for Helicobacter pylori Infections • Causative agent for stomach ulcers • Implicated in gastric cancer • Current therapy effective (~ 90%) if properly completed Proton pump inhibitor (O) + two antibiotics: Clarithromycin (C), Amoxicillin (A), Metronidazole (M) • Poor patient compliance due to complicated regimen and side effects • Resistance • Metronidazole 20 - 60%, Clarithromycin 10 -15% Need for New Therapeutic Strategies Target Product Profile (H. pylori TPP) Deliver a candidate drug with this profile: • Monotherapy – Oral dose, once a day (Patient Compliance) • High Selectivity – Minimize gut flora disturbance (Patient compliance) • Novel target – No pre-existing resistance – No threat to current antibiotic regimens – No target based toxicity issues (General Utility) (Cross-Resistance) (Patient Safety) Phases of Target-Based Approach: Target Identification Target Identification • Target Identification – – – – Genomics-based selection Validation of essentiality in relevant organisms Cloning and expression of target proteins Production of target proteins Glutamate Racemase (MurI) UDP-GlcNAc Fosfomycin HO Attributes • • • • Novel target for drug discovery Essential target Pathway is specific to bacteria Clinically validated HO O UDP-MurNAc O OH H2 N H2 N O L-Glu MurC OH UDP-MurNAc-(L) Ala O MurI D-Glu MurD UDP-MurNAc-(L) Ala-(D) Glu B-lactam classes glycopeptides Cons • Cytoplasmic target (Drug penetration?) • Bacterial kingdom conservation (Selectivity?) peptidoglycan Genomic-based Hypotheses for Selectivity Bacillus subtilis Bacillus anthracis Staphylococcus haemolyticus Staphylococcus aureus Bacillus sphaericus Streptococcus pneumoniae Streptococcus pyogenes Enterococcus faecalis Lactobacillus brevis Pediococcus pentosaceus Lactobacillus fermentum Mycobacterium leprae Mycobacterium tuberculosis Haemophilus influenzae Escherichia coli Shewanella putrefaciens Vibrio cholerae Treponema pallidum Borrelia burgdorferi Deinococcus radiodurans Pseudomonas aeruginosa Porphyromonas gingivalis Campylobacter jejuni Helicobacter pylori Aquifex aeolicus • Low sequence identity observed across bacterial species – Lowest sequence identity of all mur pathway genes – H. pylori MurI in a distinct phylogenic clade • Facile protein expression and production – Gram-scale quantities achieved in high purity (>99% pure) Gram +ve Gram -ve H. pylori Phases of Target-Based Approach: Hit Identification Target Identification Hit Identification • Hit Identification – Biophysical and biochemical characterization of targets – Development of primary assay and secondary assays for evaluation of hits – Kinetic mechanism studies for enzyme targets – Screening (e.g. HTS, virtual) and chem-informatic analysis – Limited SAR generation H. pylori MurI: an Enigma • Novel Enzyme Crystal Structure Solved – 1998 Results from Biochemical and Biophysical Characterization: Crystal Structure Features • • Active protein is a dimer Dimericrequired enzyme for activity • No –cofactors – Active sitesofoccluded solvent • Kinetic analysis enzymefrom reaction indicates an unusual profile Selective binding D-Glu and reverse reaction • – Assays required for of forward Enzyme Mechanism and Assays Cys 70 Cys 181 L-Glutamate O O O H SH 70 D-Glutamate O O O NH3+ O O O NH3+ NH3+ -S SH 181 O O - S HS 70 181 70 H O HS 181 Carbanion intermediate Coupled Assay with L-Glutamate dehydrogenase Measure NADH Coupled Assay with MurD Measure Pi or ADP Preferred HTS Assay Resource intensive, Expensive Kinetic Analysis of Native H. pylori MurI D-Glu L-Glu L-Glu D-Glu 100 40 Rate (/min) Rate (RFU/min) 80 20 60 40 20 0 0 0 20 40 60 80 100 120 140 160 0 20 [L-Glu] (mM) D-Glu (M) D-Glu KM = 63 M kcat = 12 min-1 KIS = 5.8 M kcat/KM = 185 mM-1 min-1 40 L-Glu KM = 700 M kcat = 88 min-1 kcat/KM = 126 mM-1 min-1 60 Glutamate Racemases: Biochemistry Energy Energy H. pylori MurI E.L-glu E+L-glu E+L-glu E+D-glu E+D-glu E.L-glu E.D-glu . E D-glu Reaction ReactionCoordinate Coordinate L-Glutamate O O O H SH 70 D-Glutamate O O O NH3+ O O O NH3+ NH3+ -S SH 181 70 O O - S HS 181 70 H O HS 181 Implications of Unique Biochemical Profile • Screening unlikely to identify substrate-competitive inhibitors – Enzyme:Substrate complex = dominant population – Free Enzyme levels = very low • Active site is not drug-friendly – Highly charged – Small – Accessibility • Options: – Structural / Rational Design – HTS – non-competitive or uncompetitive inhibitors? – Suicide substrate / mechanism-based inhibitors No obvious avenues HTS Assay? Poor Inhibition Profile Novel Assay Format HTS of corporate collection using novel assay Suicide Substrate HTS Assay SO3 MurI + O O OH H2 N kcat OH H2 N x4000 O O x1 OH k release kinact + O pyruvate NH3 NAD+ NADH LDH MurI Lactate inactive OH H2 N • HTS Assay – – – – All reagents commercially available Linear time course (irreversible) Excellent Assay Window Amenable to 384-well HTS format rel. Fluorescence O 40 blank 30 20 0.2mM S 0.5mM S 10 2.0mM S 0 0 10 20 30 40 50 time (min) Screened corporate collection for inhibitors (~150,000 cpds) Pyrimidinediones: Features of the Hit Cluster N O N Hit Attributes: O N N N in vitro inhibition confirmed in multiple, orthogonal assay formats Whole cell activity in H. pylori Confirmed mode of action in whole cells Amenable to MPS routes Drug-Like Scaffold Compound A IC50 = 1.4 M MIC = 8 g/mL Phases of Target-Based Approaches: Lead Identification Target Identification Hit Identification Lead Identification Hit Identification •• Target Identification Lead Identification Biochemicaland mode of inhibition understood of targets Biophysical biochemical characterization –– Genomics-based selection Facile synthetic in-place (combichem, MPS) Development of strategies primaryin HTS assayorganisms and secondary –– Validation of essentiality relevant assays for evaluation of hits – Whole-cell activity – Cloning and expression of target proteins – Kinetic mechanism studies for enzyme targets – Confirmed target-mediated mode of action in cells – Production of target proteins – and chem-informatic analysis – HTS EarlyScreening drug metabolism/pharmacokinetics (DMPK) studies – Limited SAR generation Mechanism of Inhibition? N HO O N O N N N Inhibitor ≠ O OH H2 N O Substrate Protein NMR – Foundational Work glutamate free 1.8 mM D-Glutamate • Double (15N, 2H) & Triple-labeled (15N, 13C, 2H) protein prepared in high yield • D-Glutamate titration produced a highly resolved spectrum • All backbone resonances assigned; homodimer ~ 60kD NMR indicates multiple conformations at room temperature D-Glutamate stabilizes protein – consistent with kinetic profile Protein NMR Demonstrates Substrate Dependence N O N O N N N Black = D-Glu + MurI Red = D-Glu + MurI + Inh • • • Titration of compound reveals specific shifts only when substrate present Spectrum remains unresolved when compound titration with apo protein Assignment of resonances allows binding site mapping Compound binding requires substrate Binding site distal from active site Inhibitor:Enzyme Co-Crystal Structure: The “Where” • Cryptic binding site identified ~7.5Å from active site • Consistent with NMR binding studies - C-Terminal helix movement • Catalytic residues unchanged relative to apo structure. • Supported biochemically: – Isothermal Titration Calorimetry – Intrinsic Protein Fluoresence Quenching – Uncompetitive inhibition KI = Kd Cryptic Binding Site – Detailed View MurI + D-Glutamate MurI + D-Glutamate + Inhibitor Unexpected allosteric inhibition mechanism – impact of HTS Biochemical Confirmation of Inhibition Mode 3 0 100000 2 5 Increasing [Inh] 80000 2 0 1 5 60000 RFU/80min RFU Rate (RFU/min) 120000 1 0 40000 5 20000 0 0 0 .1 1 1 0 280 300 320 340 360 380 400 420 440 460 D S O S [D-Glu] (μM) Wavelength (nM) 15000 FS FSI ΔRFU 10000 E+S F+P 5000 ESI 0 0 0.05 0.1 0.15 0.2 ES FP 0.25 [Inhibitor] μM • Binding mode confirmed in multiple formats: – Intrinsic Protein Fluorescence Quenching – Isothermal Titration Calorimetry • Kinetic Mechanism Consistent with Uncompetitive Inhibition KI = IC50 Mode of Inhibition: The “How” Inhibitor Hinge • Catalytic activity dependent on hinge movement • Compounds bind at domain interface – lock hinge movement UDP-MurNAc-(L) Ala 100 Peptidoglycan Biosynthesis UDP-MurNAc 50 MurC MurD UDP-MurNAc-(L) Ala-(D) Glu MurE UDP-MurNAc-(L) Ala-(D) Glu-mDap MurF UDP-MurNAc-(L) Ala-(D) Glu-mDap-(D) Ala-(D) Ala A254nm UDP-MurNAc-(L) Ala L-Glu MurI D-Glu Pentapeptide Bacterial Growth Inhibition Mode of Action Confirmation 0 200 150 + Inhibitor 100 50 * 0 0 10 20 30 Time (min) Growth inhibition through MurI inhibition 40 50 Phases of Target-Based Approaches: Lead Optimization Target Identification Hit Identification • Lead Optimization Hit Identification • TargetIdentification Identification Lead Identification Lead Optimization – Biophysical Focus on analogs of central scaffold(s) Facile synthetic (combichem, MPS) and strategies biochemical characterization of targets – Genomics-based selection in-place Activity in animal disease-state model Biochemical mode of inhibition understood Development of primary HTS assay and secondary –– Validation of essentiality in relevant organisms for evaluation of hits – assays Assess potential for resistance Whole-cell activity – Cloning and expression of target proteins – Kinetic mechanism studies for enzyme targets in vivo DMPK studies for human dosing estimation – Confirmed target-mediated mode of action in cells – Production of target proteins – Screening and studies chem-informatic analysis in vitro toxicological – HTS Early drug metabolism/pharmacokinetics (DMPK) studies – Limited generation Scale upSAR synthesis; process chemistry Trojan Horse or Goldmine? Can we improve potency? What is the potential for resistance? Can we achieve the desired selectivity margin? Potency Enhancements • Established parallel synthesis approaches to rapidly diversify all 4 positions • Short synthesis, clean reactions • Amenable to MPS and readily diversified • Compounds easily purified by preparative HPLC • Guided by co-crystal structure Site partially open to solvent but has potential for specific H-bond interactions (Glu, Ser, H2O) N Exposed to solvent R4 O R1 N O N N N R2 Site mainly surrounded by hydrophobic groups with a polar terminus (His, Lys) R3 Deep large hydrophobic pocket SAR - Highlights O N N N N O N O N N IC50 = 2200 nM N N Cl N O N N O IC50 = 67 nM IC50 = 103 nM N N N N S S N H N H N O O N H N N N O N O H N H IC50 = 503 nM Cl O Glu150 N H N O N O Cl N N N N H IC50 = 6 nM • Combination of best R3 and R4 resulted in 250-fold improvement in potency from Hit Potent inhibitors used to assess resistance Novel Pocket Concerns: Resistance Rates Compound Condition ARHp55 ARHp80 ARHp206 Inhibitor A 8x MIC <1.4 x10-9 <4.9 x10-9 <2.7 x10-9 Inhibitor B 8x MIC <1.2 x10-9 <8.3 x10-10 <2.9 x10-9 Inhibitor C 8x MIC ND <1.7 x10-9 <3.3 x10-9 Inhibitor D 8x MIC <3.9 x10-9 <1.9 x10-9 <2.3 x10-9 Resistance Potential (single step selection): • Acceptable (very low) resistance rates observed • Despite the low resistance rate, mutations in murI were identified at low [Inhibitor] [Inhibitor] ≈ 2 x MIC Biochemical Analysis of Resistance Mutants A35T A75T A75V E151K C162Y I178T G180S L186F L206P Q248R - Mapping onto crystal structure did not yield an obvious answer: Not in the substrate binding pocket Not in the inhibitor binding pocket (L186F) - Two were chosen for biochemical characterization: A75T (most prevalent) E151K (most dramatic) A75T H. pylori MurI Kinetic Profile D-Glu L-Glu L-Glu 600 D-Glu 100 80 Rate Rate ( M/min) 400 200 60 40 20 0 0 0 2000 4000 6000 8000 10000 0 [D-Glu] M D-Glu KM = 275 M kcat = 4 min-1 KIS = 660 M kcat/KM = 14.5 mM-1 min-1 20 40 60 [L-Glu] mM (63 M) (12 min-1) (5.8 M) L-Glu KM = 7400 M kcat = 106 min-1 kcat/KM = 14.3 mM-1 min-1 Inhibition elevation: (IC50A75T/IC50wt) ~9 fold MIC elevation: ~4 – 8 fold (700 M) (88 min-1) E151K H. pylori MurI Kinetic Profile D-Glu L-Glu L-Glu D-Glu 30 120 20 Rate Rate (RFU/min) 100 10 80 60 40 20 0 0 0 2000 4000 6000 8000 10000 0 [D-Glu] M D-Glu KM = 280 M kcat = 5 min-1 kcat/KM = 18 mM-1 min-1 (63 M) (12 min-1) (5.8 M) L-Glu 20 [L-Glu] M 40 KM = 7300 M kcat = 136 min-1 kcat/KM = 18 mM-1 min-1 Inhibition elevation: (IC50E151K/IC50wt) ~15 fold MIC elevation: ~8 - 16 fold 60 (700 M) (88 min-1) A75T E WT ES Reaction Coordinate Resistance impact Energy E151K Decreased Stability Destabilization of ES Complex Resistance Mechanism MurI MurI D-Glu MurI* (MurI*•D-Glu) Substrate inhibited D-Glu (MurI•D-Glu) L-Glu (MurI*•L-Glu) Resistance mutants disfavor [ES]/[FS] species: - Higher Km - Reduced/Eliminated Substrate Inhibition Reduced [ES] = less inhibition! But… increased potency can overcome effect Direct Binding Measurements with Inhibitors 10000 RFU 120000 100000 8000 80000 6000 60000 4000 40000 2000 20000 0 0 280 300 320 340 360 380 400 420 440 460 0 Wavelength (nM) 0.2 0.4 0.6 0.8 1 1.2 [Inhibitor] uM Dissociation Constant (Kd) MurI Enzyme Low D-Glu (50M) High D-Glu (5mM) Native 23 nM 26 nM A75T Mutant 170 nM 31 nM 1.4 Bacterial Selectivity Requirement What about the selectivity profile? Selectivity Profile Organism IC50 (nM) H. pylori CN N O H3 C Cl N N N O 9.2 0.5 E. coli H. influenzae M. catarrhalis P. aeruginosa >400000 >64 >64 >64 >64 S. aureus S. pneumoniae S. pyogenes E. faecalis >400000 >64 >64 >64 N N >400000 C. albicans • MIC (g/mL) >64 Excellent selectivity profile observed in series: • in vitro (IC50) > 50,000-fold • Whole cell > 128-fold • Basis for selectivity understood – variations in inhibitor binding pocket – – Binding pocket sequence divergence Limited flexibility to form pocket across species Trojan Horse or Goldmine? Can we improve potency? YES! What is the potential for resistance? Low Can we achieve the desired selectivity margin? So, where’s the drug? YES! Target Inhibitor Drug • biochemical properties – bona fide enzyme inhibition – potency, spectrum • microbiological properties – potency, spectrum – bona fide inhibition of bacterial growth (MOA) – resistance frequency – population MICs (MIC90) • physical properties – molecular size – lipophilicity – solubility • in-vivo properties – – – – – – plasma protein binding absorption metabolism excretion pharmacokinetics safety Pharmacokinetic Profiles in Mouse Concentration (g/ml) in vivo Drug Levels in Mouse Plasma 10 iv 5 mg/kg po 40 mg/kg 8 6 O Cl N 4 O Cl = 14 µl/min/kg t½ = 0.7 hr F = 76 % N N N N N N 2 MIC 0 0 1 2 3 4 5 6 Time (h) • Improved PK in dogs • Total drug levels above MIC for extended period of time Requirements for Efficacy: Free Fraction Concentration (g/ml) in vivo Drug Levels in Mouse Plasma 10 po 40 mg/kg, free 8 po 40 mg/kg, total 6 O Cl N 4 O Cl = 14 µl/min/kg t½ = 0.7 hr F = 76 % fu < 3 % N N N N N N 2 MIC 0 0 1 2 3 4 5 6 Time (h) • Free drug levels in plasma below MIC • Difficult to achieve balance between protein binding and potency The Agony of Defeat Increase logD Low Efflux High metabolism High protein binding Decrease logD - Acids High Efflux Low metabolism High protein binding Microbiology DMPK MIC MBC Killing Kinetics Clearance Bioavailability Permeability Vss Zwitterions Physical Properties Protein Binding Solubility Decrease LogD - bases High Efflux Low metabolism Low protein binding Phases of Target-Based Approaches: Preclinical Target Identification Hit Identification • Lead Optimization • Preclinical Hit Identification • TargetIdentification Identification Lead Identification Lead Optimisation Preclinical – Biophysical Focus oncompounds analogs of central scaffold(s) Facile Several synthetic (combichem, MPS) and strategies biochemical characterization of targets – –Genomics-based selection in-place Activity in animal disease-state model Biochemical Documentation mode for ofFDA inhibition filing understood Development of primary HTS assay and secondary –––Validation of essentiality in relevant organisms for evaluation hits ––assays in vivo DMPK studies of for human human dosing estimation Whole-cell Toxicological activity to support – Cloning and expression of target proteinsdosing – Kinetic mechanism studies enzyme targets in vitro toxicological studiesfor – Confirmed target-mediated mode of action in cells – Production of target proteins – and process chem-informatic analysis Scale up synthesis; chemistry – HTS EarlyScreening drug metabolism/pharmacokinetics (DMPK) studies – Limited SAR generation Thoughts • MurI Specific: – Essentiality & target conservation may be insufficient to gauge potential – Niche opportunities may be more tractable than broad spectrum • General: – Understand the target: • Mechanistic studies can clarify appropriate strategies for Hit ID • Evaluate the physiological context of in vitro data • Structural studies are integral – HTS can provide novelty – with luck and persistence – Don’t be satisfied with your best lead series – keep looking! More reading Acknowledgments • AZ Boston • AZ Mölndal Richard Alm Barbara Arsenault April Blodgett Ken Coleman Boudewijn deJonge Joe Eyermann Ning Gao Madhu Gowravaram Lena Grosser Pamela Hill Janette Jones Thomas Keating Amy Kutschke Jim Loch Larry MacPherson Cynthia Mascolo Marshall Morningstar Brian Noonan Olga Rivin Maria Uria-Nickelsen Jonny Yang Mark Zambrowski Beth Andrews Greg Basarab Gloria Breault Janelle Comita Gejing Deng Tatyana Friedman Bolin Geng Oluyinka Green Laurel Hajec Sussie Hopkins Camil Joubran Gunther Kern Stephania Livchak Kathleen McCormack John Manchester Scott Mills Trevor Newton Linda Otterson Mike Rooney Jim Whiteaker Wei Yang Marie Andersen Tomas Lundqvist Rutger Folmer Yafeng Xue Nan Albertson Bo Xu Mark Divers Christer Cederberg John Primeau Trevor Trust Mark Wuonola Paul Manning Gautam Sanyal Peter Webborn Supporting Slides Biochemical Studies on MurI Isozymes Species Biochemical data L-Glu → D-Glu D-Glu → L-Glu Escherichia coli KM = 1200 140 μM kcat = 730 20 min-1 KM = 2100 140 μM kcat = 2600 44 min-1 Enterococcus faecalis KM = 1200 12 μM kcat = 1500 40 min-1 Enterococcus faecium Staphylococcus aureus UNAM-Ala Activation Monomer Yes KM = 250 20 μM kcat = 704 14 min-1 Dimer No KM = 1100 100 μM kcat = 2200 50 min-1 KM = 240 23 μM kcat = 900 32 min-1 Dimer No KM = 4600 270 μM kcat = 510 90 min-1 KM = 140 10 μM kcat = 34 3.2 min-1 Dimer No • Various pathogens represented • Gram negative enzymes = activated • Gram positive enzymes = high catalytic turnover Physiology: Resistance vs. D-Glutamate Regulation UDP-Mur Catabolic Energy Source MurC UDP-Mur-(L) Ala Nitrogen Fixation Amino Acid Biosynthesis L-Glu MurI D-Glu MurD UDP-Mur-(L) Ala-(D) Glu Peptidoglycan • Implications of biochemistry of H. pylori MurI mutants: – – – Substrate inhibition is a critical regulatory element Resistant mutants affect enzyme regulation, not binding site Can be overcome via potency enhancement Sampling Diverse H. pylori Strains Genomic DNA from representative strains from a variety of disease states and geographical locations was screened for resistance mutations. A35T A75T A75V E151K C162Y I178T G180S L186F L206P Strain Country Year of Disease state Isolation ARHP55 Identity to J99 MurI(%) Duodenal ulcer 95.359 94.531 94.922 Nonulcer 95.703 dyspepsia Nonulcer 93.359 dyspepsia Duodenal ulcer 92.188 UA861 ARHp18 ARHp25 ARHp64 Canada Canada Australia Argentina 1991 1989 1989 1996 ARHp65 Argentina 1996 ARHp54 United 1996 States ARHp124 Bangladesh 1996 United States ARHp43 Australia ARHp246 Kuala Lumpur ARHp241 Kuala Lumpur 1996 Hiatus hernia 93.75 and gastritis Duodenal ulcer 92.578 1984 1998 94.531 93.359 ARHp243 France ARHp244 France 1998 1998 1998 Q248R Duodenal ulcer, gastritis Duodenal 93.359 ulcer, erosive gastritis Duodenal ulcer 94.141 Nonulcer 93.75 dyspepsia Clinical Resistance Potential? AH244 UA861 SS1_206_ ARHP65 ARHP18 ARHp243 ARHP246 ARHP241 ARHP55 26695 ARHp244 ARHP124 ARHP54 ARHP43 ARHP25 J99 ARHP64 Clustal Co 160 170 180 190 200 ESILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA ENILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA ESILGGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IESYFMGHFA ENILEGELLE TCMRYYFTPL EILPEVIILG CTHFPLIAQK IEGYFMGHFA ENILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAHQ IEGYFMEHFA ENILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAHQ IEGYFMEHFA ENILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAHQ IEGYFMEHFA ESILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL EILPEVVILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL KILPKVIILG CTHFPLIAHQ IKGYFMGHFA ESILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA ESILEGELLE TCMRYYFTPL EILPEVIILG CTHFPLIAQK IESYFMEHFA ESILEGELLE TCMHYYFTPL EILPEVIILG CTHFPLIAQK IEGYFMGHFA ESILEGELLE TCMRYYFTPL KILPEVIILG CTHFPLIAQK IEGYFMEHFA *.** ***** ***:****** :***:*:*** ********:: *:.*** *** • Sequenced murI from 16 clinical strains • Selection criteria: – Global distribution – Disease state progression • Based on sequence conservation, low probability of naturally occurring resistant strains