Chattanooga Research Institute Presentation

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A presentation made to Chattanooga officials about the importance of computational biology to the future of health care and what it might mean to the Chattanooga Research Institute (CRI).

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  • (nutraceuticals excluded)
  • Multi-target therapy may be more effective than single-target therapy to treat infectious diseasesMost 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 genesCan optimize the model for in vivo growthCarry out multiple gene inhibition and compute the maximal theoretical growth rate (if close to zero, that combination of genes is essential for growth)
  • Chattanooga Research Institute Presentation

    1. 1. Computational BiologyPhilip E. Bourne PhD<br />pbourne@ucsd.edu<br />http://www.sdsc.edu/pb<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />Thanks to Howard Asher for some slides<br />
    2. 2.
    3. 3. Agenda<br />Computational Biology<br />What is it?<br />What are some success stories to date<br />What pitfalls can be avoided based on the experiences of others<br />What opportunities does it afford the region from a research, education and hence economic perspective?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    4. 4. Biology has moved from being an observational to an analytical science <br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    5. 5. Biology covers vast scales<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    6. 6. 02/07/2011<br />Computational Biology Summit Chattanooga<br />Comparative Genomics<br />Neural Circuits<br />Biochemical pathways <br />underlying drug addiction<br />Adaptive fast walking<br />Object recognition<br />Biologics<br />
    7. 7. What drove these research directions?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    8. 8. Technologies producing digital Information<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    9. 9. Its not just about numbers its about complexity<br />Number of released entries<br />Year<br />Courtesy of the RCSB Protein Data Bank<br />
    10. 10. 02/07/2011<br />Computational Biology Summit Chattanooga<br />
    11. 11. June 26, 2000 was a milestone with the mapping of the human genome<br />British Prime Minister Tony Blair <br />Announced by then US president Bill Clinton <br />and the British Prime Minister Tony Blair<br />U.S. President Bill Clinton listens to British Prime Minister Tony Blair as Celera President J Craig Venter looks on during a joint teleconference announcement in the East Room of the White House, June 26, 2000. Venter's company Celera Genomics Corporation participated in a publicly financed Human Genome Project with private efforts and have both completed the first rough map of the human genome, the working blueprint for human beings. The discovery is seen as one of history's great scientific milestones.<br />02/07/2011<br />
    12. 12. Today informatics ≥ 2 x data ≅3 months<br />
    13. 13. Subdisciplines of “matics”<br />Electronic HR<br />Decision support<br />Drug dosing<br />Pharmacokinetics<br />Pharmacy Information<br />Systems<br />Pharmacy<br />Informatics<br />Biomedical<br />Informatics<br />Algorithms<br />Genomics<br />Proteomics<br />Systems<br />Bioinformatics<br />Computational Biology Summit Chattanooga<br />Note: These are only representative examples<br />
    14. 14. Agenda<br />Computational Biology<br />What is it?<br />What are some success stories to date<br />What pitfalls can be avoided based on the experiences of others<br />What opportunities does it afford the region from a research, education and hence economic perspective?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    15. 15. Metagenomics<br />New type of genomics<br />New data (and lots of it) and new types of data<br />17M new (predicted proteins!) 4-5 x growth in just few months and much more coming<br />New challenges and exacerbation of old challenges<br />
    16. 16. Metagenomics: early results<br />More then 99.5% of DNA in every environment studied represent unknown organisms<br />Most genes represent distant homologs of known genes, but there are thousands of new families<br />Environments being studied:<br />Water (ocean, lakes)<br />Air<br />Soil<br />Human body (gut, oral cavity, human microbiome)<br />
    17. 17. Metagenomics new discoveriesEnvironmental (red) vs. Currently Known PTPases (blue)<br />1<br />2<br />3<br />4<br />Higher eukaryotes<br />
    18. 18. Personalized medicine<br />
    19. 19. Personalized medicine<br />Right Therapeutic—Right Dose—Right Time—Right Place—Right Person<br />& Understanding of genetic contributions to disease and to its treatment… <br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    20. 20. Your health—optimized to you<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    21. 21. Drug discovery – the sad truth<br />We know very little about how the major drugs we take work<br />We know even less about their side effects<br />Drug discovery seems not to have moved into the omics era<br />The cost and time of bringing a drug to market is huge ~ $1 Bn<br />The cost of failure is even higher e.g., Vioxx ~ $5 Bn<br />Fatal diseases are neglected because they do not make money<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    22. 22. Why the failure?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    23. 23. Polypharmacology - One Drug Binds to Multiple Targets<br /><ul><li>Tykerb – Breast cancer
    24. 24. Gleevac – Leukemia, GI cancers
    25. 25. Nexavar – Kidney and liver cancer
    26. 26. Staurosporine – natural product – alkaloid – uses many e.g., antifungal antihypertensive</li></ul>Collins and Workman 2006 Nature Chemical Biology 2 689-700<br />
    27. 27. Why the failure?What can be done about it?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    28. 28. High-throughput computational drug discovery can Be applied on three axes<br />Target<br />One to Multiple Targets<br />Bioinformatics<br />Cheminfomatics<br />Drug<br />Docking<br />HTS<br />Associative Transfer of Indications<br />Disease<br />
    29. 29. Consider one example of using the corpus as a whole from our own research – high throughput hypothesis generation for use in drug discovery<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    30. 30. The TB-Drugome<br />Determine the TB structural proteome<br />Determine all known drug binding sites from the PDB<br />Determine which of the sites found in 2 exist in 1<br />Call the result the TB-drugome<br />Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976<br />Computational Biology Summit Chattanooga<br />02/07/2011<br />
    31. 31. 2. Determine all Known Drug Binding Sites in the PDB<br />Searched the PDB for protein crystal structures bound with FDA-approved drugs<br />268 drugs bound in a total of 931 binding sites<br />No. of drugs<br />Acarbose<br />Darunavir<br />Alitretinoin<br />Conjugated estrogens<br />Chenodiol<br />Methotrexate<br />No. of drug binding sites<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    32. 32. Map 2 onto 1 – The TB-Drugome<br />http://funsite.sdsc.edu/drugome/TB/<br />Similarities between the binding sites of M.tb proteins (blue), <br />and binding sites containing approved drugs (red). <br />
    33. 33. From a Drug Repositioning Perspective<br />Similarities between drug binding sites and TB proteins are found for 61/268 drugs<br />41 of these drugs could potentially inhibit more than one TB protein<br />conjugated estrogens &<br />methotrexate<br />No. of drugs<br />chenodiol<br />levothyroxine<br />testosterone<br />raloxifene<br />alitretinoin<br />ritonavir<br />No. of potential TB targets<br />02/07/2011<br />
    34. 34. Top 5 Most Highly Connected Drugs<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    35. 35. Agenda<br />Computational Biology<br />What is it?<br />What are some success stories to date<br />What pitfalls can be avoided based on the experiences of others<br />What opportunities does it afford the region from a research, education and hence economic perspective?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    36. 36. SDSC Abbreviated Timeline<br />1985<br />1990<br />2005<br />2010<br />1995<br />2000<br />Cray-XMP48<br />220 Mflops<br />Cray T3E<br />1 Tflops<br />Cray C90<br />5 Gflops<br />http://www.sdsc.edu/News%20Items/PR101510_25years.html<br />
    37. 37. SDSC Lessons Learned<br />There is a tension between engineering and science – you need people at the interface<br />People and the services they provide are what make the difference<br />Fundamental shift from computer speed to data storage<br />The future is open with provenance<br />Beware the cloud<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    38. 38. SDSC lessons learned<br />More focus on education<br />More focus on integration with surrounding communities<br />More focus on outreach<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    39. 39. Agenda<br />Computational Biology<br />What is it?<br />What are some success stories to date<br />What pitfalls can be avoided based on the experiences of others<br />What opportunities does it afford the region from a research, education and hence economic perspective?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    40. 40. From the Art of Medicine to the Science of Health…<br />2010 the Tipping Point<br />ArtTransformation Science<br />Art of<br />Medicine<br />at the<br />organ level <br />Science of<br />Health<br />at the<br />molecular level <br />2020<br />2000<br />2010<br />Genomic Era<br />Data Information Knowledge Wisdom<br />
    41. 41. How to take advantage of this change?Pick important problems and become a source of valuable data and human resources for solving those problems<br />
    42. 42. Depositor locations <br />Depositions since 2000<br />Download locations<br />RCSB PDB<br />PDBe<br />PDBj<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    43. 43. How to take advantage of this change?Enable the use of those data and resources in ways that the next generation will build upon<br />
    44. 44. www.scivee.tv<br />
    45. 45. 02/07/2011<br />Computational Biology Summit Chattanooga<br />
    46. 46. Enjoy the ah ha moments<br />
    47. 47. Acknowledgements<br />Funding Agencies: <br />NSF, NIGMS, DOE, NLM, NCI, <br />NCRR, NIBIB, NINDS, NIDDK<br />44<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    48. 48. pbourne@ucsd.edu<br />Questions?<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />
    49. 49. What is the Protein Data Bank (PDB)?<br />The single community owned worldwide repository on the structures of publically accessible biological macromolecules<br />A resource used by ~ 200,000 individuals per month<br />A resource distributing equivalent to ¼ the National Library of Congress each month<br />02/07/2011<br />Computational Biology Summit Chattanooga<br />

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