Julio Peironcely @ ICCS 2011

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Talk given at the 9th International Conference on Chemical Structures, June 9th. How metabolomics and metabolite identification can be improved by chemoinformatics.

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Julio Peironcely @ ICCS 2011

  1. 1. Improving Metabolite Identificationwith ChemoinformaticsJulio E. Peironcely  @peyronPhD student at Leiden University and TNOJune 9th 2011ICCS 2011
  2. 2. Metabolome all low molecular weight molecules (metabolites) in cells, body fluids, tissues, etc.Metabolomics the quantitative and qualitative analysis of all metabolites in samples of cells, body fluids, tissues, etc. June 9th 2011 ICCS 2011 Julio E. Peironcely
  3. 3. Metabolomics Genome Transcripts Proteins Metabolites Phenotype June 9th 2011 ICCS 2011 Julio E. Peironcely
  4. 4. Metabolomics Experi- BiologicalBiological Sample Data Data pre- Data mental Sampling inter-question preparation acquisition processing analysis design pretation Metabolites Relevant biomolecules/ List of Samples Raw data connectivities Protocol peaks/ & biomolecules Models June 9th 2011 ICCS 2011 Julio E. Peironcely
  5. 5. LC-MS and Metabolite Identification RPLC-microTOF (Bruker) LC MS MSpeak = m/z@rt = metabolite Kloet et al, Metabolomics 2011 June 9th 2011 ICCS 2011 Julio E. Peironcely
  6. 6. When all you have is a mass anda “window” List of Elemental Compositions ChemSpider MS Mass + KEGG HMDB Window PubChem List of Molecules Measured Mass + Mass Window = Multiple Elemental Compositions June 9th 2011 ICCS 2011 Julio E. Peironcely
  7. 7. nWhen you have MS Measured Mass + Mass Window + Fragments = Single Elemental Composition ChemSpider n Mass + KEGG HMDB MS Window 1 EC fragments PubChem List of Molecules Use the expert system June 9th 2011 ICCS 2011 Julio E. Peironcely
  8. 8. The expert system Dr. Ronnie van Doorn Dr. Albert Tas June 9th 2011 ICCS 2011 Julio E. Peironcely
  9. 9. Bottlenecks in MetaboliteIdentification Many metabolites in LC-MS not identified HighRes MS can obtain 1 EC = many structures No tools for automatic identification Takes long for the expert to identify metabolites Julio E. Peironcely
  10. 10. Challenges Analytical methods Software Databases Julio E. Peironcely
  11. 11. Our approachExperimental 1 Data 1.1 1.1 1.2 1.2 1.1. 1.2. 1.2.Processing 1.1.1 1 1.2.1 1 1.2.2 2Data Trees present Identity assignment n MSFind Similar Trees Database absent Generate Elemental Formula Structure + Structures Fragments generator Filter Metabolite- Structures likeness June 9th 2011 ICCS 2011 Julio E. Peironcely
  12. 12. Our approachExperimental 1 Data 1.1 1.1 1.2 1.2 1.1. 1.2. 1.2.Processing 1.1.1 1 1.2.1 1 1.2.2 2Data Trees present Identity assignment n MSFind Similar Trees Database absent Generate Elemental Formula Structure + Structures Fragments generator Filter Metabolite- Structures likeness June 9th 2011 ICCS 2011 Julio E. Peironcely
  13. 13. Our approachExperimental 1 Data 1.1 1.1 1.2 1.2 1.1. 1.2. 1.2.Processing 1.1.1 1 1.2.1 1 1.2.2 2Data Trees present Identity assignment n MSFind Similar Trees Database absent Generate Elemental Formula Structure + Structures Fragments generator Filter Metabolite- Structures likeness June 9th 2011 ICCS 2011 Julio E. Peironcely
  14. 14. Our approachExperimental 1 Data 1.1 1.1 1.2 1.2 1.1. 1.2. 1.2.Processing 1.1.1 1 1.2.1 1 1.2.2 2Data Trees present Identity assignment n MSFind Similar Trees Database absent Generate Elemental Formula Structure + Structures Fragments generator Filter Metabolite- Structures likeness June 9th 2011 ICCS 2011 Julio E. Peironcely
  15. 15. From data to information
  16. 16. MEF: spectral to fragmentation tree Experimental Data Processing Data Trees CML Find Similar XCMS Trees CDK Generate Structures MEF Filter StructuresRojas-Cherto et al. Bioinformatics (submitted) June 9th 2011 ICCS 2011 Julio E. Peironcely
  17. 17. MEF: spectral to fragmentation tree Experimental full Data Peak scan MS Parent Ion Mass EC Processing … Data Trees Reaction Noise 1 Neutral Find Similar υ Trees Fragments loss Generate Structures MS2 1.1 1.2 1.3 υ υ υυ 1.1 1.2 1.3 Filter Structures MS3 1.1.1 1.2.1 1.2.2 1.2.3 1.3.1 1.3.2 1.1.1 1.2.1 1.2.2 1.2.3 1.3.1 1.3.2 Spectral Tree Fragmentation TreeRojas-Cherto et al. Bioinformatics (submitted) June 9th 2011 ICCS 2011 Julio E. Peironcely
  18. 18. Extracting more information from your data
  19. 19. Fragmentation tree fingerprintsExperimental 1 Data Processing Data Trees 1.1 1.1 1.2 1.2 1.3 1.3Find Similar 1.1. 1.2. 1.2. 1.2. 1.3. 1.3. Trees 1.1.1 1 1.2.1 1 1.2.2 2 1.2.3 3 1.3.1 1 1.3.2 2 Generate Structures Filter StructuresPoster 59Miguel Rojas-Cherto, Leiden University June 9th 2011 ICCS 2011 Julio E. Peironcely
  20. 20. Fragmentation tree fingerprintsresults“unknown” Most similar trees MCSExperimental Data Processing Data TreesFind Similar Trees Generate Structures Filter StructuresPoster 59Miguel Rojas-Cherto, Leiden University June 9th 2011 ICCS 2011 Julio E. Peironcely
  21. 21. De-novo identification
  22. 22. Structure GeneratorExperimental Data Elemental Fragments Formula Processing Data TreesFind Similar Generate Trees Keep molecules if Generate canonical Structures augmentation CDK Nauty Filter Structures All non-duplicated molecules Poster 38In collaboration with Jean-Loup Faulon, Evry University June 9th 2011 ICCS 2011 Julio E. Peironcely
  23. 23. Structure Generator Results MOLGEN same # of moleculesExperimental Data Processing Data Trees p-Cresol Glycine Phenylalanine Malic acid D-CysteineFind Similar sulfate Trees Elemental C2H5NO2 C9H11NO2 C4H6O5 C3H7NO2S C7H8O3S Composition Generate # Output 84 277,810,163 8,070 3,838 10,203,389 Structures Molecules 6 4,037,499 1,601 100 19,940 Filter 1 Fragment Structures 93,137 948 2 Fragments 584 3 Fragments 278Poster 38In collaboration with Jean-Loup Faulon, Evry University June 9th 2011 ICCS 2011 Julio E. Peironcely
  24. 24. Lots of candidates structures
  25. 25. Metabolite-likeness HMDB 8K ZINC 21MExperimental Data Atom Counts Physicochemical desc. Standardization Processing MDL Public Keys Data Trees FCFP_4 ECFP_4 Diversity SelectionFind Similar Trees Training Set Test Set Generate 532 + 532 6.4K + 6.4K Structures 5-fold CV Metabolite Filter likeness Structures SVM RF BCIn collaboration with Andreas Bender, Cambridge Univ. June 9th 2011 ICCS 2011 Julio E. Peironcely
  26. 26. Metabolite-likeness HMDB 8K ZINC 21MExperimental Data Atom Counts Physicochemical desc. Standardization Processing MDL Public Keys Data Trees FCFP_4 ECFP_4 Diversity SelectionFind Similar Trees Training Set Test Set Generate 532 + 532 6.4K + 6.4K Structures 5-fold CV Metabolite Filter likeness Structures SVM RF BC 1st RF – MDLPublicKeys 2nd RF – ECFP_4 Sensitivity Specificity AUC Sensitivity Specificity AUC 99.84% 87.52% 99.20% 99.77% 86.36% 99%In collaboration with Andreas Bender, Cambridge Univ. June 9th 2011 ICCS 2011 Julio E. Peironcely
  27. 27. Metabolite-likeness, externalvalidationExperimental Data HMDB External DrugBank ChEMBL validation set Processing Data Trees Random SelectionFind Similar Trees Generate Standardization Structures Filter Metabolite RF – MDLPublicKeys Structures likeness RF – ECFP_4In collaboration with Andreas Bender, Cambridge Univ. June 9th 2011 ICCS 2011 Julio E. Peironcely
  28. 28. Metabolite-likeness, externalvalidationExperimental Data Processing Data TreesFind Similar Trees Generate Structures Filter StructuresIn collaboration with Andreas Bender, Cambridge Univ. June 9th 2011 ICCS 2011 Julio E. Peironcely
  29. 29. From information to knowledge
  30. 30. www.MetiTree.nl ICCS 2011Group DatabaseUpload and organize your own treesVisualize treesFind similar trees(to be added: Struct. Gen, Met-likeness) June 9th 2011 ICCS 2011 Julio E. Peironcely
  31. 31. Conclusions Chemoinformatics plays a crucial role in the metabolite identification pipeline Now it is the time to challenge this pipeline with real cases Expert is still needed June 9th 2011 ICCS 2011 Julio E. Peironcely
  32. 32. Acknowledgements TNO Quality of Life Leon Coulier Albert Tas Leiden University Miguel Rojas-Cherto Piotr Kasper Michael van Vliet University of Cambridge Theo Reijmers Andreas Bender Rob Vreeken Ronnie van Doorn Thomas Hankemeier Evry University Jean-Loup Faulon Davide Fichera Wageningen University/ HMP University of PRI Alberta Egon Willighangen David Wishart Justin van der Hooft Ying (Edison) Dong Ric de Vos Jacques Vervoort June 9th 2011 ICCS 2011 Julio E. Peironcely

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