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The Dengue Docking Project: Virtual Screening on the ProtoGRID

Explore the Dengue Docking Project's virtual screening on the ProtoGRID platform at EGEE'06 conference. Learn about the collaboration between institutions in Switzerland targeting Aedes aegypti-infested areas to combat the Dengue epidemic. Discover the challenges of drug development, the role of virtual screening, and the progress in identifying potential drug candidates using computer simulations. Benefit from the GRID-based computing resources and SwissBioGrid initiative facilitating the exploration of Dengue treatment options.

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The Dengue Docking Project: Virtual Screening on the ProtoGRID

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  1. The Dengue Docking Project:Virtual Screening on the ProtoGRID EGEE'06 conference, Swiss Grid Track Dr. Michael Podvinec Biozentrum, University of Basel & Swiss Institute of Bioinformatics Basel, Switzerland.

  2. Areas infested with Aedes aegypti Areas with Aedes aegypti and recent epidemic dengue Data: CDC, 1999

  3. Every year: • 2.5 billion are at risk of infection • 50-100 million people get infected with Dengue • 500'000 cases of Dengue Hemorrhagic Fever • 25'000 deaths No vaccination. No specific treatment available.

  4. Public-private partnership • Biozentrum, University of Basel :in silico docking • NITD:In vitro/in vivo follow-up • Novartis:Drug development at cost • Schrödinger, Llc.:Scientific collaboration on docking • SwissBioGridGrid computing resources,Proof of Concept for SwissBioGrid

  5. What does it take to make a drug? Target validation Opti- mization Target ID Screening Clinical Preclinical ~12 years 802 mio US$(DiMasi, J.A. et al. (2003) J Health Econ, 22, 151-185). only 1 in 10‘000 NCE survives(Heilman, R.D. (1995) Qual Assur 4(1) 75-9.) HIT LEAD CANDIDATEDRUG DRUG

  6. Virtual screening to the rescue? Target validation Opti- mization Target ID Screening Clinical Preclinical HIT LEAD CANDIDATEDRUG DRUG  Virtual screening (computer simulations) • Save initial investment (HTS) • Predict likely hits in silico • GRID-based • Still must assay results

  7. Camille Pissarro, Haystack, 1873

  8. Protein-ligand complexesshare common characteristics.We can use these characteristics to predict ligands for target molecules.

  9. 2: NS3 serine protease 1: Envelope Glycoprotein E Structure and serotype analysis of dengue target sites: catalytic triad b-OG P1Arg contact S-Adenosyl-homocysteine GMP analogue 3: NS3 RNA helicase 4: NS5 RNA methyl transferase

  10. [BC]2 UD PC grid [BC]2 Linux cluster Uni ZH AIX cluster VitalITLinux cluster CSCSUNIX HPCresources SwissBioGrid Initiative Federate resourcesusing GRID technology provide computing platform enable Dengue proof-of-concept Basel Zürich CERN International collaborations EGEE Lausanne Lugano

  11. Phase I (protoGRID) • Evaluate requirements for productive GRID infrastructure • Federate pre-existing Swiss HPC ressources (non-intrusive system - cycle stealing ONLY) • Swiss HPC ressources are heterogeneous: Clusters, HPC, PC Desktop Grids • Geographically and administratively separate entities • Support the specific data requirements of bioinformatics applications • Validation of docking results on heterogeneous architectures • Productive services for the scientific PoC(Docking against Dengue targets) Phase II (NorduGRID) • Extend NorduGRID based on lessons learnt from ProtoGRID (data model, LRMS support) • Productive services for several scientific projects (e.g. peptide mass fingerprinting in proteomics)

  12. SBG Phase 1: ProtoGRIDSingle interface to Swiss HPC resources QW QW CSCS(PBS, Itanium 64)Ticino [BC]2 PC Desktop Grid(UD MP, Win32)Basel Grid Node Manager Grid Data Manager QW QW [BC]2 HPC cluster(SGE, x86-32)Basel Vital-IT HPC cluster(LSF, Itanium 64/ Nocona)Lausanne

  13. Some hurdles in grid adoption[as identified in the SwissBioGrid development process] • Where do the CPUs come from? • Most HPC resources are busy already • Agree on dedicated compute time for grid projects? • Buy new clusters for your grid? • PC Desktop grids provide a huge untapped resource • Licensing schemesof most commercial software are not suitable for GRIDs • Application clearing: • Ensuring data integrity on distributed resources • Non-intrusiveness of the application • Security issues: Avoid accidental or malicious negative impact on running systems • Numerical stability in heterogeneous environments • Data model in bioinformatics is different from HEP • Most applications need access to large public databases

  14. Achievements of GRID-enabled Dengue Docking • Technical: Phase I SwissBioGrid infrastructure complete • large-scale parameterization test using Autodock 3.0.5: 500‘000 docking runs, 38‘000h CPU time • Prioritized hit list from 127k library screening (GLIDE) is undergoing In vitro testing at NITD • Some initial hits(at 20 M) • Currently screening the ZINC open source compound library (~4 Mio cpd)

  15. Acknowledgements CSCS Marie-Christine Sawley Peter Kunszt Sergio Maffioletti Novartis Institute for Tropical Diseases Alex Matter Mark Schreiber Subhash Vasudevan Siew Pheng Lim Biozentrum & SIB University of Basel: Torsten Schwede Jürgen Kopp Marco Scarsi Rainer Pöhlmann Konstantin Arnold Fraunhofer SCAI: Martin Hoffmann Marc Zimmermann Novartis Manuel Peitsch René Ziegler Eric Vangrevelinghe Pascal Afflard Vital-IT: Victor Jongerneel Bruno Nyffeler Jacques Rougemont Heinz Stockinger Arthur Thomas EGEE/CNRS: Vincent Breton Nicolas Jacq Schrödinger, Inc: Jörg Weiser

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