UCSD Deans and Chairs Presentation - PDB & Drug Discovery

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A presentation made to the Deans and Chairs of the UCSD Health Sciences on Jan. 25, 2011 concerning the role that the PDB might play in drug discovery going forward.

A presentation made to the Deans and Chairs of the UCSD Health Sciences on Jan. 25, 2011 concerning the role that the PDB might play in drug discovery going forward.

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  • Response to stimuli (stress, inflammation, DNA repair) Cellular processes (transcription, translation, RNA splicing, photosynthesis) Other
  • Bacteriophage T4 lysozyme (458 structures) with many different changes (substitutions, ligands) Protein folding: Mutagenesis studies suggest that fraction of amino acid residues that define the structure of T4 lysozyme is about 50% Ligand binding: Understanding binding site flexibility would allow more effective design of ligands or inhibitors Relationship between protein activity and stability: Reduction in activity may increase protein stability Enzyme catalysis Conclusion Matthews, B.W. 1996, The FASEB Journal, v 10, 35-41 Hen White Lysozyme (257 structures) Protein evolution Conclusion Phage and hen lysozymes present no significant sequence similarity. However their three-dimensional structures are homologous. Interactions between substrate and enzyme are homologous Mechanism of catalysis is the same Matthews, B.W., Remington, M.G., Grutter, M.G., Anderson, W.F. 1981, J.Mol.Biol, v 147, (4), 545-58 Human Lysozyme (196 structures) Implication into disease (amyloidosis) Conclusion Crystal structure of wild type and amyloidogenic variants are similar. However amyloidogenic variants have reduced protein stability and altered folding kinetics Booth, R.B., et. all 1997 Nature,387, 787-93
  • Whale Myoglobin (185 structures) looked at: different ligands (carbon dixoide, ...) different substitutions (...)? Protein folding Ligand binding Protein dynamics Protein evolution conclusion: Myoglobin Other species looked at conclusion Hemoglobin different ligands, different species with different sequences conclusion: same fold (evolutionary) Conclusion Sequence similarity between whale and plant myoglobins is ~25%. However their three dimensional structures and functions are homologous Globin genes evolved from divergence from one ancestral globin gene Myoglobin and hemoglobin genes diverged into separate subfamilies Dickerson, R.E., Geis, I 1983 Hemoglobin: structure, function, and pathology Human Hemoglobin (178 structures) Implication into disease (sicke cell anemia, thalassemia)
  • 3,996 proteins in TB proteome 749 solved structures in the PDB, representing a total of 284 proteins (7.2% coverage) ModBase contains homology models for entire TB proteome 1,446 ‘high quality’ homology models were added to the data set Structural coverage increased to 43.8% Retained only those models with a model score of > 0.7 and a Modpipe quality score of > 1.1 (2818 models). There were multiple models per protein. For each TB protein, chose the model with the best model score, and if they were equal, chose the model with the best Modpipe quality score (1703 models). However, 251 (+6) models were removed since they correspond to TB proteins that already have solved structures. 1446 models remained) Score for the reliability of a Model, derived from statistical potentials (F. Melo, R. Sanchez, A. Sali,2001 PDF ). A model is predicted to be good when the model score is higher than a pre-specified cutoff (0.7). A reliable model has a probability of the correct fold that is larger than 95%. A fold is correct when at least 30% of its Calpha atoms superpose within 3.5A of their correct positions. The ModPipe Protein Quality Score is a composite score comprising sequence identity to the template, coverage , and the three individual scores evalue , z-Dope and GA341 . We consider a MPQS of >1.1 as reliable
  • (nutraceuticals excluded)
  • Multi-target therapy may be more effective than single-target therapy to treat infectious diseases Most of the proteins listed are potential novel drug targets for the development of efficient anti-tuberculosis chemotherapeutics. GSMN-TB : Genome Scale Metabolic Reaction Network of M.tb (http://sysbio/sbs.surrey.ac.uk/tb) 849 reactions, 739 metabolites, 726 genes Can optimize the model for in vivo growth Carry out multiple gene inhibition and compute the maximal theoretical growth rate (if close to zero, that combination of genes is essential for growth)


  • 1. The RCSB Protein Data Bank www.rcsb.org Phil Bourne SSPPS [email_address] 1/25/11 UCSD Deans and Chairs Meeting
  • 2. Agenda
    • What is the RCSB PDB and what does it bring to SSPPS/UCSD?
    • Examples of how it is being used in drug discovery
    • How SSPPS/UCSD might leverage it going forward
    1/25/11 UCSD Deans and Chairs Meeting
  • 3. What is the Protein Data Bank (PDB)?
    • The single community owned worldwide repository on the structures of publically accessible biological macromolecules
    • A resource used by ~ 200,000 individuals per month
    • A resource distributing equivalent to ¼ the National Library of Congress each month
    1/25/11 UCSD Deans and Chairs Meeting
  • 4. Total Contents by Year Number of released entries Year 1/25/11
  • 5. Depositor locations Download locations RCSB PDB PDBe PDBj Depositions since 2000 1/25/11 UCSD Deans and Chairs Meeting
  • 6. Cooperative Community Action
    • Individual letters to editors of journals
    • Committees
      • IUCr commission on Biological Macromolecules
      • ACA/USNCCr
      • Richards committee
    • Funding agencies
    • Articles in journals
    1/25/11 UCSD Deans and Chairs Meeting Marvin Cassman Fred Richards Richard Dickerson
  • 7. Structure distribution Other Protein only Protein-DNA complexes DNA only Protein-RNA complexes RNA only RNA-DNA hybrid Structure determination methods Number of structures Year Resolution distribution: protein structures Resolution distribution: other structures Year Resolution Resolution distribution: all structures
  • 8. What has the PDB enabled?
    • Safe storage and retrieval of macromolecular structure data
    • Increased understanding of sequence-structure-function relationships:
      • A “parts list” for structure modeling and prediction
      • Structure based drug design
      • Protein structure classification
      • The details in large scale interactions
    1/25/11 UCSD Deans and Chairs Meeting
  • 9. Lysozyme: Lessons learned Blake, Koenig, Mair, North, Phillips, Sarma (1965) Nature 206: 757.
    • T4 bacteriophage (459 structures)
    • Amino acid replacement studies suggest that fraction of amino acid residues that define the structure of T4 lysozyme is about 50%
    • B.W. Matthews (1996) FASEB J .10: 35-41.
    • Insight into folding and catalysis
    • Hen egg white (297 structures)
    • Low sequence identity
    • Structural similarity of active site to T4
    • B.W. Matthews, M.G. Remington, M.G. Grutter, W.F. Anderson (1981) J.Mol.Biol. 147: 545-58.
    • Insight into evolution and catalysis
    1/25/11 UCSD Deans and Chairs Meeting
  • 10. Myoglobin and hemoglobin: Lessons learned
    • Whale myoglobin (185 structures)
    • Different ligands: oxygen, carbon dioxide 1
    • Amino acid substitution studies 2
    • Laue studies 3
    • Insight into function and dynamics
    • Other species myoglobin
    • Low sequence identity, same structure 4
    • Insight into evolution
    • Human hemoglobin (178 structures)
    • Insight into function and disease (sickle cell anemia, thalassemia) 5
    • Other species hemoglobin
    • Low sequence identity, same structure 4
    • Profound insight into evolution
    Lodish et al . 6 1 Kuriyan, Wilz, Karplus, Petsko (1986) J. Mol. Biol. 192:133–154; 2 Quillin, Arduini, Olson, Phillips, Jr. (1993) J. Mol. Biol . 234: 140–155, Carver, Brantley Jr, Singleton, Arduini, Quillin, Phillips Jr, Olson (1992) J. Biol. Chem. 267:14443–14450; 3 Bourgeois, Vallone, Schotte, Arcovito, Miele, Sciara, Wulff, Anfinrud, Brunori (2003) PNAS 100: 8704-8709; 4 Dickerson, Geis (1983) Hemoglobin: structure, function, and pathology; 5 Kidd, Baker, Mathews, Brittain Baker (2001) Prot. Sci. 10:1739-1749, Harrington, Adachi, Royer Jr. (1998) J. Biol. Chem . 273: 32690 - 32696; 6 Lodish, Berk, Zipursky, Matsudaira, Balitmore, Darnell (2000) Molecular Cell Biology WH Freeman & Co.
  • 11. Agenda
    • What is the PDB and what does it bring to UCSD?
    • Examples of how it is being used in drug discovery
    • How UCSD might leverage it going forward
    1/25/11 UCSD Deans and Chairs Meeting
  • 12. RCSB PDB Pharmacology/Drug View
    • Establish linkages to drug resources (FDA, PubChem, DrugBank, ChEBI, BindingDB etc.)
    • Create query capabilities for drug information
    • Provide superposed views of ligand binding sites
    • Analyze and display protein-ligand interactions
    Mockups of drug view features Drug Name Asp Aspirin Has Bound Drug % Similarity to Drug Molecule 100
  • 13. HIV-related structures Year HIV-1 reverse transcriptase HIV-1 protease 1/25/11 311 110 39 27 122 Protease Reverse Transcriptase Gag protein Integrase Other Amprenavir (GSK) Fosamprenavir (GSK) Lopinavir (Abbott) Atazanavir (BMS) Nelfinavir ( Agouron) Darunavir ( Tibotec) Tipranavir (BI) Indinavir (Merck) Ritonavir (Abbott) Saquinavir (Roche) 2R5P, 2B7Z, 2AVV, 2AVO, 2AVS, 1SGU, 1SDT, 1SDV, 1SDU, 1K6C, 1C6Y, 2BPX, 1HSG, 1HSH 1T7J, 1HPV 2B60, 1RL8, 1SH9, 1N49, 1HXW 2QAK, 2PYM, 2Q63, 2PYN, 2Q64, 2R5Q, 1OHR 2O4N, 2O4L, 2O4P, 1D4Y, 1D4S 3D1X, 3D1Y, 3CYX, 2NMW, 2NMZ, 2NNP, 2NMY, 2NNK, 1C6Z, 1FB7 2FXE, 2FXD, 2O4K, 2AQU, 2FND 2RKG, 2RKF, 2QHC, 2Z54, 2Q5K, 2O4S, 1RV7, 1MUI Abacavir (GSK) Nevirapine (BI) Stavudin (BMS) Efavirenz (BMS) Lamivudine (GSK) Zidovudine (GSK) Emtricitabine (Gilead) Tenofovir (Gilead) Zalcitabine (Hoffmann- LaRoche) Etravirine (Tibotec) Delavirdine (Pfizer) 2HND, 2HNY, 1S1U, 1S1X, 1LW0, 1LWE, 1LWC, 1LWF, 1JLB, 1JLF, 1FKP, 1VRT, 3HVT 1JKH, 1IKW, 1IKV, 1FKO, 1FK9 1S6P 1T05
  • 14. Consider one example of using the corpus as a whole from our own research – high throughput hypothesis generation for use in drug discovery 1/25/11 UCSD Deans and Chairs Meeting
  • 15. Polypharmacology - One Drug Binds to Multiple Targets
    • Tykerb – Breast cancer
    • Gleevac – Leukemia, GI cancers
    • Nexavar – Kidney and liver cancer
    • Staurosporine – natural product – alkaloid – uses many e.g., antifungal antihypertensive
    Collins and Workman 2006 Nature Chemical Biology 2 689-700
  • 16. The TB-Drugome
    • Determine the TB structural proteome
    • Determine all known drug binding sites from the PDB
    • Determine which of the sites found in 2 exist in 1
    • Call the result the TB-drugome
    Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976 UCSD Deans and Chairs Meeting
  • 17. 1. Determine the TB Structural Proteome
    • High quality homology models from ModBase (http://modbase.compbio.ucsf.edu) increase structural coverage from 7.1% to 43.3%
    284 1, 446 3, 996 2, 266 TB proteome homology models solved structures 1/25/11 UCSD Deans and Chairs Meeting
  • 18. 2. Determine all Known Drug Binding Sites in the PDB
    • Searched the PDB for protein crystal structures bound with FDA-approved drugs
    • 268 drugs bound in a total of 931 binding sites
    No. of drug binding sites Methotrexate Chenodiol Alitretinoin Conjugated estrogens Darunavir Acarbose 1/25/11 UCSD Deans and Chairs Meeting
  • 19. Map 2 onto 1 – The TB-Drugome http://funsite.sdsc.edu/drugome/TB/ Similarities between the binding sites of M.tb proteins (blue), and binding sites containing approved drugs (red).
  • 20. From a Drug Repositioning Perspective
    • Similarities between drug binding sites and TB proteins are found for 61/268 drugs
    • 41 of these drugs could potentially inhibit more than one TB protein
    No. of potential TB targets raloxifene alitretinoin conjugated estrogens & methotrexate ritonavir testosterone levothyroxine chenodiol 1/25/11
  • 21. Top 5 Most Highly Connected Drugs Drug Intended targets Indications No. of connections TB proteins levothyroxine transthyretin, thyroid hormone receptor α & β -1, thyroxine-binding globulin, mu-crystallin homolog, serum albumin hypothyroidism, goiter, chronic lymphocytic thyroiditis, myxedema coma, stupor 14 adenylyl cyclase, argR , bioD, CRP/FNR trans. reg ., ethR , glbN , glbO, kasB , lrpA , nusA , prrA , secA1 , thyX , trans. reg. protein alitretinoin retinoic acid receptor RXR- α , β & γ , retinoic acid receptor α , β & γ -1&2, cellular retinoic acid-binding protein 1&2 cutaneous lesions in patients with Kaposi's sarcoma 13 adenylyl cyclase, aroG , bioD, bpoC, CRP/FNR trans. reg. , cyp125 , embR , glbN , inhA , lppX , nusA , pknE , purN conjugated estrogens estrogen receptor menopausal vasomotor symptoms, osteoporosis, hypoestrogenism, primary ovarian failure 10 acetylglutamate kinase, adenylyl cyclase, bphD , CRP/FNR trans. reg. , cyp121 , cysM, inhA , mscL , pknB , sigC methotrexate dihydrofolate reductase, serum albumin gestational choriocarcinoma, chorioadenoma destruens, hydatidiform mole, severe psoriasis, rheumatoid arthritis 10 acetylglutamate kinase, aroF , cmaA2 , CRP/FNR trans. reg. , cyp121 , cyp51 , lpd , mmaA4 , panC , usp raloxifene estrogen receptor, estrogen receptor β osteoporosis in post-menopausal women 9 adenylyl cyclase, CRP/FNR trans. reg., deoD, inhA, pknB , pknE , Rv1347c , secA1, sigC
  • 22. Agenda
    • What is the PDB and what does it bring to UCSD?
    • Examples of how it is being used in drug discovery
    • How UCSD might leverage it going forward
    1/25/11 UCSD Deans and Chairs Meeting
  • 23. How UCSD Might Leverage the PDB
    • Part of the foundation of a drug discovery effort.
    • Outreach tool
    • The Devil is in the Details - talented group of PDB scientists capable of working with the details
    • Lots of experience with UCSD’s unique infrastructure, data curation, management, dissemination etc. available for new initiatives
    1/25/11 UCSD Deans and Chairs Meeting
  • 24. Acknowledgements Funding Agencies: NSF, NIGMS, DOE, NLM, NCI, NCRR, NIBIB, NINDS, NIDDK 1/25/11 UCSD Deans and Chairs Meeting