Grid07 6 Jacq

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Grid07 6 Jacq

  1. 1. World-wide in silico drug discovery against neglected and emerging diseases on grid infrastructures Dr Nicolas jacq HealthGrid association Credit : the WISDOM collaboration http://wisdom.healthgrid.org International Symposium on Grids for Science and Business 12 June 2007 www.healthgrid.org
  2. 2. The HealthGrid association • The vision of HealthGrid is the deployment of e-infrastructures able to interoperate geographically distributed repositories of health-related data and the integration of high-end processing services on top of them. • Some key aspects are: – The integration of health-related actors in grid projects – The integration of grid standards and medical informatics standards for interoperability – The deployment of pilots for new ways of research and new methods – The integration of bioinformatics community and medical informatics • The mission of HealthGrid is to foster the communication among the different key actors and to catalyse joint research actions at international level Jacq - 12 June 2007 2
  3. 3. Main achievements • Edition of the HealthGrid Whitepaper in 2005 outlining the concept, benefits and opportunities offered by applying grids in different applications in biomedicine and healthcare – http://whitepaper.healthgrid.org • Involvement as full partner in several projects – SHARE (SSA): http://www.eu-share.org – EGEE II (I3): http://www.eu-egee.org – ACGT (IP): http://www.eu-acgt.org • Organisation of the HealthGrid conference since 2003 – HealthGrid.US Alliance will host the 6th International HealthGrid Conference in Chicago – Spring 2008 • Development of the health grids knowledge base – http://kb.healthgrid.org Jacq - 12 June 2007 3
  4. 4. Content • WISDOM, an initiative for grid-enabled drug discovery against neglected and emerging diseases • Deployment and results of grid-enabled large scale virtual screening against malaria and avian influenza • Deployment method • Conclusion and perspectives Jacq - 12 June 2007 4
  5. 5. Goal of the WISDOM initiative • WISDOM stands for World-wide In Silico Docking On Malaria • Goal: contribute to develop new drugs for neglected and emerging diseases with a particular focus on malaria and avian flu • Specificity: extensively rely on emerging information technologies to provide new tools and environments for drug discovery • Initial focus: virtual screening • Web site: http://wisdom.healthgrid.org Jacq - 12 June 2007 5
  6. 6. WISDOM collaboration LPC Clermont-Ferrand: SCAI Fraunhofer: Biomedical grid Knowledge extraction, Web service Chemoinformatics CEA, Acamba project: Univ. Modena: Malaria biology, Malaria biology, Chemogenomics Molecular Dynamics HealthGrid: ITB CNR: Academica Sinica: Biomedical grid, Bioinformatics, Grid user interface Dissemination Molecular modelling Avian flu biology In vitro testing Univ. Los Andes: Bioinformatics, New Malaria biology Chonnam Nat. Univ.: Univ. Pretoria: Mahidol Univ. Bangkok: In vitro testing Bioinformatics, In vitro testing Malaria biology Partners Associated labs 7 partners, 4 associated laboratories providing targets and/or in vitro facilities Jacq - 12 June 2007 6
  7. 7. Benefits from using the grid (1/2) • World-wide distribution of malaria resistance • 1975-2004: Only 21 new drugs for tropical diseases on 1,556 were marketed (Chirac P. Toreele. E Lancet. May 2006) • Neglected diseases keep suffering lack of R&D • Grids allow reduced costs Jacq - 12 June 2007 7
  8. 8. Benefits from using the grid (2/2) • H5N1 virus has the potential to cause a large-scale pandemic • H5N1 may mutate and acquire the ability of drug resistance • Time is a critical factor for handling emerging diseases • Grids provide accelerating factor months Deaths from all causes each week expressed as an annual rate per 1000 Source : Ross E.G. Upshur BA(HONS), MA, MD, MSc, CCFP, FRCPC Jacq - 12 June 2007 8
  9. 9. In silico drug discovery • Problem: development of a drug takes 12 to 15 years and costs approximately 800 million dollars Target discovery Lead discovery Target Target Lead Lead Clinical Identification Validation Identification Optimization Phases (I-III) Jacq - 12 June 2007 9
  10. 10. Grid impact on drug discovery workflow down to drug delivery (1/2) • Grids provide the necessary tools and data to identify new biological targets – Bioinformatics services (database replication, workflow…) – Resources for CPU intensive tasks (genomics comparative analysis, inverse docking…) • Grids provide the resources to speed up lead discovery – Large scale in silico docking to identify potentially promising compounds – Molecular dynamics computations to refine virtual screening and further assess selected compounds • Grid offers very interesting perspectives to enable collaboration between public and private partners – Platform for information and knowledge sharing Jacq - 12 June 2007 10
  11. 11. Grid impact on drug discovery workflow down to drug delivery (2/2) • Grids provide environments for epidemiology – Federation of databases to collect data in endemic areas to study a disease and to evaluate impact of vaccine, vector control measures – Resources for data analysis and mathematical modelling • Grids provide the services needed for clinical trials – Federation of databases to collect data in the centres participating to the clinical trials • Grids provide the tools to monitor drug delivery – Federation of databases to monitor drug delivery Jacq - 12 June 2007 11
  12. 12. Content • WISDOM, an initiative for grid-enabled drug discovery against neglected and emerging diseases • Deployment and results of grid-enabled large scale virtual screening against malaria and avian influenza • Deployment method • Conclusion and perspectives Jacq - 12 June 2007 12
  13. 13. Virtual screening by docking Compound Target structure database model DOCKING Predicted binding models Post-analysis Docking: predict how small molecules bind to a receptor of known 3D structure Compounds for assay Jacq - 12 June 2007 13
  14. 14. Grid-enabled high throughput virtual screening by docking Millions of potential High Throughput Screening drugs to test against 1-10$/compound, several hours interesting proteins! Too costly for neglected disease! Compounds: Molecular docking (FlexX, Autodock) ZINC: 4.3M ~1 to 15 minutes Chembridge: 500,000 Data challenge on EGEE Targets: ~ 2 to 30 days on ~5,000 computers PDB: 3D structures Cheap and fast! Hits screening Leads Selection of the using assays Clinical testing best hits performed on living cells Drug Jacq - 12 June 2007 14
  15. 15. Statistics of deployment • First Data Challenge: July 1st - August 15th 2005 – Target: malaria – 80 CPU years, 1 TB of data produced, 1,700 CPUs used in parallel – 1st large scale docking deployment world-wide on a e-infrastructure • Second Data Challenge: April 15th - June 30th 2006 – Target: avian flu – 100 CPU years, 800 GB of data produced, 1,700 CPUs used in parallel – Collaboration initiated on March 1st: deployment preparation achieved in 45 days • Third Data Challenge: October 1st - 15th December 2006 – Target: malaria – 400 CPU years, 1.6 TB of data produced, Up to 5,000 CPUs used in parallel – Very high docking throughput: > 100,000 compounds per hour Jacq - 12 June 2007 15
  16. 16. A huge international effort for the third data challenge 1% 2% 2% 3% 3% 3% EGEE Germany Switzerland 3% EGEE Asia Pacific 38% 5% EGEE Russia Auvergrid 6% EuChinaGrid EELA EGEE South Western Europe EGEE Central Europe EGEE Northern Europe EGEE Italy 7% EGEE South Eastern Europe EGEE France EGEE UKI 12% 15% Over 420 CPU years in 10 weeks A record throughput of 100,000 docked compounds per hour WISDOM calculations used FlexX from BioSolveIT (6k free, floating licenses) Jacq - 12 June 2007 16
  17. 17. Biological objectives • Malaria – Plasmepsin – DHFR Plasmodium falciparum – DHFR Plasmodium vivax – GST – Tubulin N1 • Avian influenza – Neuraminidase N1 H5 Credit: Y-T12 June 2007 Jacq - Wu (ASGC) 17
  18. 18. Results from avian flu data challenge (1/2) • 5 out of 6 known effective inhibitors can be identified in the first 15% of the ranking and in the first 5% reranked (2,250 compounds) – Enrichment: (5/6)/(15%x5%) = 111 (<1 in most cases) • Most known effective inhibitors lose their affinity in binding with a mutated target Original type E119A E119A mutated type GNA 2.4% GNA 11.5% 11.5% 15% cut off GNA=zanamivir Jacq - 12 June 2007 18
  19. 19. Results from avian flu data challenge (2/2) • Experimental assay confirms 7 actives out of 123 purchased “potential hits” (interacting complexes with higher affinities and proper docked poses) = 6% • Average success rate of in vitro testing = 0.1% • To be confirmed on more hits, tests are running in Univ. of Chonnam (South Korea) NA Jacq - 12 June 2007 19
  20. 20. Results from first malaria data challenge 1,000, 000 chemical compounds Sorting based on scoring in different parameter sets; Consensus scoring 10,000 compounds selected Based on key interactions, binding modes, etc. 1,000 compounds MD 100 compounds will be tested in July by Univ. of Credit: V. Kasam Chonnam (South Korea) Fraunhofer Institute Jacq - 12 June 2007 20
  21. 21. Content • WISDOM, an initiative for grid-enabled drug discovery against neglected and emerging diseases • Deployment and results of grid-enabled large scale virtual screening against malaria and avian influenza • Deployment method • Conclusion and perspectives Jacq - 12 June 2007 21
  22. 22. Requirements for a deployment on grid • Adaptation of the application to the grid • Access to a large infrastructure providing maintained resources • Use of a production system providing automated and fault-tolerant job and file management Jacq - 12 June 2007 22
  23. 23. Adaptation of the application to the grid DB • The application codes can not be modified and Input Data are not designed for grid data DB Data DB subset computing. Parameters • A common strategy is to Docking software split the application into shorter tasks • License management for Output commercial software is not adapted for large Embarrassingly parallel application infrastructure Jacq - 12 June 2007 23
  24. 24. Real Time Monitor (Imperial College London) Grid Added Value http://gridportal.hep.ph.ic.ac.uk/rtm/ • Large number of CPUs available • Reliable and secured Data Management Services – Sharing of results – Replication of the data – ACLs • Availability of the resources Jacq - 12 June 2007 24
  25. 25. Grid infrastructures and projects contributing to the data challenges EMBRACE BioinfoGrid SHARE EGEE Auvergrid EUMedGrid EUChinaGrid TWGrid EELA : European grid infrastructure : European grid project : Regional/national grid infrastructure Jacq - 12 June 2007 25
  26. 26. WISDOM production environment Credit: CNRS-IN2P3 Jacq - 12 June 2007 26
  27. 27. GUI designed by biologists Compound selection Complex visualization Target selection Energy table Docking parameter setter Credit: H-C12 June(ASGC)27 Jacq - Lee 2007
  28. 28. Content • WISDOM, an initiative for grid-enabled drug discovery against neglected and emerging diseases • Deployment and results of grid-enabled large scale virtual screening against malaria and avian influenza • Deployment method • Conclusion and perspectives Jacq - 12 June 2007 28
  29. 29. Conclusion • WISDOM proposes a new approach to drug discovery thanks to the grid – Rapid deployment of large scale virtual screening – Collaborative environment for the sharing of data in the research community • First biochemical results demonstrate grid relevance to the drug discovery community Jacq - 12 June 2007 29
  30. 30. Perspectives • Summer 2007 – 2nd data challenge against avian flu – In vitro tests of the best molecules from the data challenges • Winter 2007 – Discussion with WHO and Novartis Targets provided by the Drug Target Portfolio Network from the Tropical Disease Research initiative – Discussion with Africa@home initiative WISDOM deployment on a desktop grid Jacq - 12 June 2007 30
  31. 31. Thank you • To all members of the WISDOM collaboration for their contribution to the project (CNRS-IN2P3, ASGC, ITB-CNR, SCAI Fraunhofer, Univ of Modena…) • To all grid nodes which committed resources and allowed the success of the initiative • To all projects which supported the initiative by providing either computing resources or manpower to develop the WISDOM environment (EGEE, BioinfoGRID, Embrace, SHARE…) • To BioSolveIT by offering up to 6,000 free licenses of FlexX Jacq - 12 June 2007 31

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