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The Dengue Docking Project: Virtual Screening on the ProtoGRID

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. Areas infested with Aedes aegypti.

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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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