1. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 1 Projects 1-4 update David Wild CICC Quarterly Meeting January 27 th 2006

2. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 2 CICC-related projects Formal CICC projects 1.Innovative cross-screen analysis of NIH DTP Human Tumor Cell Line Data – innovative scientific analysis of NIH HTS data 2.Development of cheminformatics web services and use cases in Taverna – web service & workflow infrastructure 3.Development of a novel interface for the analysis of PubChem HTS data – tools for interacting with lots of complex data 4.A structure storage and searching system for Distributed Drug Discovery – innovative kinds of chemical databases Other, related projects –Fast clustering of very large datasets using Linux clusters –Smart client for mining drug discovery data (Microsoft supported)

3. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 3 PROJECT 4 Experimental Databases PROJECT 2 Web services & workflows PROJECT 1 Innovative cross-screen analysis of HTS data PROJECT 3 Visualization, navigation & analysis tools for HTS data SMART CLIENT Smart interfaces (incl. NLP, RSS, agents, etc) SMART CLIENT General drug discovery web services & workflows SMART CLIENT Smart interfaces (incl. NLP, RSS, agents, etc) FAST PARALLEL CLUSTERING Using DivKmeans & AVIDD

4. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 4 Desired outcomes by Summer 2006 A chemical informatics web service infrastructure running at IU Several Taverna workflows that use these and other web services, and which demonstrate that the infrastructure can be used to perform complex, relevant operations on PubChem data Demonstrated scientific results with the NIH DTP data An established Distributed Drug Discovery database linked with PubChem, that shows that our techniques together with PubChem can be employed in ways which benefit humanity in general A sandbox PubChem copy with improved functionality and architecture One or more novel visualization tools for PubChem data Demonstrate the feasibility of fast, accurate clustering of very large datasets (including the whole of PubChem) using the AVIDD Linux Cluster and a parallelized clustering algorithm (DivKmeans) Show that.NET and Java-based web services can work well together in a common infrastructure Demonstrate the feasibility of a natural language or other straightforward interface for scientists to express their information needs

5. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 5 NIH Database Service PostgreSQL CHORD Fingerprint Generator BCI Makebits Cluster Analysis BCI Divkmeans Table Management VoTables Plot Visualizer VoPlot Docking Selector Script 2D-3D OpenEye OMEGA Docking OpenEye FRED 3D Visualizer JMOL Cluster the compounds in the NIH DTP database by chemical structure, then choose representative compounds from the clusters and dock them into PDB protein files of interest SMILES + ID Fingerprints PDB Database Service SMILES + ID + Data Cluster Membership SMILES + ID + + Cluster # + Data SMILES + ID MOL File PDB Structure + Box Docked Complex

6. Indiana University School of David Wild – CICC Quarterly Meeting, Jan 27 2005. Page 6 NIH Database Service PostgreSQL CHORD Docking Selector Script 2D-3D OpenEye OMEGA Docking OpenEye FRED 3D Visualizer JMOL PDB Ligand Database Service SMILES + ID + + Data NIH SMILES + ID MOL File Docked Complex PDB Database Service Protein