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

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.

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 SwissBioGrid Grid computing resources, Proof of Concept for SwissBioGrid

What does it take to make a drug? Target validation Opti- mization Target ID Screening Preclinical Clinical HIT LEAD CANDIDATE DRUG DRUG ~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.)

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

availability of compounds (or synthetic accessibilty) Chemical space 10E29 derivatives of n-Hexane Need some way to find an interesting region of chemical space availability of compounds (or synthetic accessibilty) natural compounds similarity to other drugs shape/feature complementarity with known drugs/inhibitors Camille Pissarro, Haystack, 1873

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

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

SwissBioGrid Initiative Federate resources using GRID technology provide computing platform enable Dengue proof-of-concept [BC]2 Linux cluster [BC]2 UD PC grid Uni ZH AIX cluster Basel Zürich VitalIT Linux cluster CERN International collaborations CSCS UNIX HPC resources EGEE Lausanne Lugano

Phase I (protoGRID) Phase II (NorduGRID) 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)

SBG Phase 1: ProtoGRID Single 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

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 schemes of 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

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)

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