HierS Hierarchical Scaffold- Based Molecular Clustering

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1 HierS Hierarchical Scaffold- Based Molecular Clustering Steven J. Wilkens Genomics Institute of the Novartis Research Foundation

2 GNF Founded in 1999 Over 400 employees Located in Torrey Pines Research Park Scripps Research Institute (TSRI) Salk Institute UCSD Multidisciplinary Drug discovery Structural biology Proteomics Engineering Genomics

3 lead discovery custom high-throughput screening (HTS) robotics 1536-well screening system and hit picker 1.5 million compounds in-house combinatorial commercial collections Novartis about 30 HTS campaigns a year more HTS capacity than follow-up capacity opportunistically choose targets

4 HierS Hierarchical Scaffold clustering Goals Simple easy for chemists and biologists to figure out no assumptions, special cases Intuitive consistent with chemical intuition Interpretable cluster membership is obvious Visual readily visualize cluster and member compounds Interactive quickly navigate through clusters

5 HierS Hierarchical Scaffold clustering Goals Simple easy for chemists and biologists to figure out no assumptions, special cases Intuitive consistent with chemical intuition Interpretable cluster membership is obvious Visual readily visualize cluster and member compounds Interactive quickly navigate through clusters

6 Definitions Bemis, G. W. and M. A. Murcko (1996). "The properties of known drugs.1. Molecular frameworks." J. Med. Chem. pp Xu, J. (2002). "A new approach to finding natural chemical structure classes." J. Med. Chem. 45 pp BIRB 796

7 Definitions Rings that share internal bonds are part of the same ring system Ring Systems BIRB 796

8 Definitions atoms and bonds and connect ring systems Linkers BIRB 796

9 Definitions Chains BIRB 796

10 Building Scaffolds Trim Chains X BIRB 796 X

11 super scaffold retain atoms double bonded to linkers and rings

12 identify basis scaffolds 5 rings 4 ring systems 3 basis scaffolds

13 two ring systems

14 three ring systems

15 all scaffolds

16 structural hierarchy larger scaffolds are derived from smaller scaffolds BIRB 796

17 HTS data analysis 1. generate all possible scaffolds for each compound in the set 2. build complex network of connections between scaffolds compounds naturally aggregate in important/interesting scaffold classes compounds are members of all scaffold classes that are substructures of them 3. remove redundant scaffolds complete and compact 4. use connections between scaffold classes to follow your nose through the set of compounds

18 example data set September 2003 release of the NCI Developmental Therapeutics Program Human Tumor Cell Line Screen about 32,000 compounds after filtering data were grouped by panel each panel can be made up of several cell lines GI 50 of 10-7 M used as hit criteria Leukemia panel hits used as test set 1,603 hits staurosporins: 4 steroids: 74

19 Scaffold Filter APT: Average Pair wise Tanimoto APT is a measure of the overall structural similarity of the compounds in the scaffold class

20 structural hierarchy

21 structural hierarchy

22 about 3 minutes per 1,000 compounds computation time varies with type of compounds

23 Significant APT

24 Significant APT fast scaffold navigation

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26 optimizing HTS hit picking goal of HTS identify a diverse set of active compounds as candidates for lead optimization scaffold enrichment may indicate desirable activity may also result from undesirable activity aggregation patented/well-known scaffold class shared synthetic impurities fluorescent features HierS can hedge bets by removing compounds from over-represented scaffold classes fill openings with under-represented compounds

27 Auto Mark Options dialog appears when scaffolds are present

28 total Marked compounds Marked compound count for each scaffold class Starting point for manual editing of compound list

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31 summary HierS process recursively identify all ring-delimited scaffolds build hierarchical relationships between scaffolds compounds accumulate in interesting and/or overrepresented scaffolds Visualization web interface interactively traverse hierarchy HTS hit pick optimization Auto Marking capability can be used to remove overrepresented compounds replace with novel actives

32 implementation 100% Java JChem provides chemistry functionality ( chemistry metaphors fingerprinting, atom-atom matching image generation Open Source components Apache Tomcat servlet container Jakarta Struts MVC framework JFreeChart Borland JBuilder IDE scales linearly with the number of compounds