page 1 SCAI Dr. Marc Zimmermann Department of Bioinformatics Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Grid-enabled drug discovery to address neglected diseases

page 2 SCAI The challenges of the drug discovery A pharmaceutical grid for the drug discovery A pharmaceutical grid for a neglected disease Content

page 3 SCAI Target Identification Target Validation Lead Identification Lead Optimization Target discoveryLead discovery vHTS Similarity analysis Similarity analysis Database filtering Database filtering Computer Aided Drug Design (CADD) de novo design diversity selection diversity selection Biophores Alignment Combinatorial libraries ADMET QSAR Phases of a pharmaceutical development Clinical Phases (I-III) Duration: 12 – 15 years, Costs: million US $

page 4 SCAI Enable scientists to quickly and easily find compounds binding to a particular target protein -growth of targets number -growth of 3D structures determination (PDB database) -growth of computing power -growth of prediction quality of protein-compound interactions Experimental screening very expensive : not for academic or small companies Aim : Enrichment = Actives molecules Tested molecules Computational aspects of Drug Discovery : virtual screening

page 5 SCAI Dataflow and workflow in a virtual screening hit crystal structure ligand data base junk docking Structure optimization Reranking MD-simulation

page 6 SCAI The challenges of the drug discovery A pharmaceutical grid for the drug discovery A pharmaceutical grid for a neglected disease Content

page 7 SCAI To guarantee and preserve knowledge in the areas of discovery, development, manufacturing, marketing and sales of next drug therapies -Provides extremely large CPU power to perform computing intense tasks in a transparent way by means of an automated job submission and distribution facility -Provides transparent and secure access to storage and archiving of large amounts of data in an automated and self-organized mode -Connects, analyses and structure data and metadata in a transparent mode according to pre-defined rules (science or business process based) A shared in silico resource

page 8 SCAI Semantic inconsistence between biological and chemical databases => ontology-based mediation services Meta-information on softwares and formats Users integration from different and heterogeneous organisations Statistical models, optimization Grid engine Virtual screening machine with formal description Construction in function of the disease/subject of the grid Structure of a grid for drug discovery

page 9 SCAI Content The challenges of the drug discovery A pharmaceutical grid for the drug discovery A pharmaceutical grid for a neglected disease

page 10 SCAI Overview on neglected diseases Infectious diseases kill 14 million people each year, more than 90% of whom are in the developing world. Access to treatment is problematic -the medicines are unaffordable, -some have become ineffective due to drug resistance, -and others are not appropriately adapted to specific local conditions and constraints. Neglected diseases represent grave personal tragedies and substantial health and economic burdens even for the wealthiest nations. Drug discovery and development targeted at infectious and parasitic diseases in poor countries has virtually ground to a standstill, so that these diseases are neglected.

page 11 SCAI In silico drug discovery process (EGEE, SwissBioGRID, …) Clermont-Ferrand The grid impact : Computing and storage resources for genomics research and in silico drug discovery cross-organizational collaboration space to progress research work Federation of patient databases for clinical trials and epidemiology in developing countries Grids for rare diseases and diseases of the developing world Support to local centres in plagued areas (genomics research, clinical trials and vector control) SCAI Fraunhofer Swiss Biogrid consortium Local research centres In plagued areas

page 12 SCAI Collaborative environment We will support such processes as: -search of new drug targets through post-genomics requiring data management and computing -providing a large public database with drug like molecules and found hits -massive docking to search for new drugs requiring high performance computing and data storage -handling of experimental data requiring data storage and management

page 13 SCAI Acknowledgement IN2P3/CNRS Nicolas Jacq Jean Salzeman Vincent Breton Fraunhofer SCAI Marc Zimmermann Kai Kumpf Martin Hofmann Biozentrum Basel Michael Podvinec Torsten Schwede