page 1 scai dr. marc zimmermann department of bioinformatics fraunhofer institute for algorithms and...
TRANSCRIPT
page 1SCAI
Dr. Marc Zimmermann
Department of Bioinformatics
Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)
Grid-enabled drug discovery to address neglected diseases
page 2SCAI
The challenges of the drug discovery
A pharmaceutical grid for the drug discovery
A pharmaceutical grid for a neglected disease
Content
page 3SCAI
TargetIdentification
TargetValidation
LeadIdentification
Lead Optimization
Target discovery Lead discovery
vHTSvHTS
Similarityanalysis
Similarityanalysis
Databasefiltering
Databasefiltering
Computer Aided Drug Design(CADD)
de novo design
de novo design
diversityselectiondiversityselection
BiophoresBiophores
AlignmentAlignment
Combinatorial libraries
Combinatorial libraries
ADMETADMET
QSARQSAR
Phases of a pharmaceutical development
Clinical Phases (I-III)
Duration: 12 – 15 years, Costs: 500 - 800 million US $
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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
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Dataflow and workflow in a virtual screening
hit
crystal structure
ligand data base
junk
docking
Structureoptimization
Reranking
MD-simulation
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The challenges of the drug discovery
A pharmaceutical grid for the drug discovery
A pharmaceutical grid for a neglected disease
Content
page 7SCAI
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
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Basic Grid Technology Layer
Administration of Virtual Organisations
Distributed Data Access / Information Retrieval
Workflows
Data and Knowledge Mining Services
Ontologies / Knowledge Representation
Integration of Applications
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
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Content
The challenges of the drug discovery
A pharmaceutical grid for the drug discovery
A pharmaceutical grid for a neglected disease
page 10SCAI
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.
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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 centresIn plagued areas
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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
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Acknowledgement
IN2P3/CNRS
Nicolas Jacq
Jean Salzeman
Vincent Breton
Fraunhofer SCAI
Marc Zimmermann
Kai Kumpf
Martin Hofmann
Biozentrum Basel
Michael Podvinec
Torsten Schwede