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The collection, curation and modeling of Open Melting Point measurements

The collection, curation and modeling of Open Melting Point measurements. 5 th Meeting on U.S. Government Chemical Databases and Open Chemistry. Jean-Claude Bradley. Andrew Lang. Antony Williams. Department of Chemistry Drexel University. ChemSpider Royal Society of Chemistry.

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The collection, curation and modeling of Open Melting Point measurements

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  1. The collection, curation and modeling of Open Melting Point measurements 5th Meeting on U.S. Government Chemical Databases and Open Chemistry Jean-Claude Bradley Andrew Lang Antony Williams Department of Chemistry Drexel University ChemSpider Royal Society of Chemistry Department of Mathematics Oral Roberts University August 26, 2011

  2. The Problem of Data Quality in Chemistry • Lack of provenance • Reliance on a system of “trusted sources” In the case of melting points: • CRC Handbook • Merck Index • Chemical Vendor Catalogs (e.g. Sigma-Aldrich) • Peer-Reviewed Journals

  3. Strategy for the curation of melting points Rely on redundancy when possible Provide the maximum level of provenance when necessary (Open Notebook Science) Adhere to Open Data, Open Descriptors and Open Algorithms for measurements and modeling Using technology, we can begin to replace the “trusted source” model with one based on transparency and provenance

  4. The Chemical Information Validation Sheet 567 curated and referenced measurements from Fall 2010 Chemical Information Retrieval course

  5. Investigating the m.p. inconsistencies of EGCG

  6. Most popular data sources

  7. Alfa Aesar donates melting points to the public

  8. Open Melting Point Explorer

  9. Outliers EPA/PhysProp (donated all data to public also) MDPI dataset

  10. Outliers for ethanol: Alfa Aesar and Oxford MSDS

  11. Inconsistencies and SMILES problems within MDPI dataset

  12. MDPI Dataset labeled with High Trust Level

  13. EPA/PHYSPROP Structure Errors (Incorrect Valence): 2315 out of 43543 were contained pentavalentnitrogens

  14. EPA/PHYSPROP Errors: Structure displayed is for the neutral compound dopamine but the associated CAS Number and chemical name in the file are for the hydrobromidesalt.

  15. Common errors in datasets multiple melting points for the same compound in the same database stereochemistry issues sign inversion conversion errors (Kelvin/CelciusFahrenheit/Celcius) bad SMILES (non-rendering) salts associated with SMILES for free base using boiling point for melting point

  16. Open melting point datasets Double+ validated: 2706 compounds (7413 highly curated measurements. range: 0.01-5 C. Compounds that had at least one chiral center, possessed cis/trans isomerism, were inorganic or a salt removed.) Entire dataset: 19933 unique compounds (27684 measurements – no inorganics or salts)

  17. Open Models with Open Data Using Open Descriptors (CDK)

  18. Modeling Results

  19. Melting point prediction service

  20. Melting point predictions and measurements on iPhone/iPad(Alex Clark)

  21. Publication of double+ validated melting point dataset to Nature Precedings and LuLu

  22. For all Formats of ONS Projects

  23. Open Melting Point Datasets Currently 20,000 compounds with Open MPs

  24. Some melting points can’t be resolved only with literature: 4-benzyltoluene

  25. Motivation: Faster Science,Better Science

  26. Open Lab Notebook page measuring the melting point of 4-benzyltoluene

  27. Using melting point for temperature dependent solubility prediction

  28. Crowdsourcing Solubility Data

  29. Integration of Multiple Web Services to Recommend Solvents for Reactions

  30. All ONS web services

  31. Google Apps Scripts web services

  32. Google Apps Scripts for conveniently exploring melting point data

  33. Comparison of model with triple validated measurements Straight chain carboxylic acids from 1 to 10 carbons Straight chain alcohols from 1 to 10 carbons

  34. Cyclic primary amines from 3 to 6 carbons (cyclobutylamine flagged for validation – only single source available)

  35. Google Apps Scripts for planning reactions and creating schemes

  36. Open Melting Points in Supplementary Data Pages of Wikipedia (Martin Walker)

  37. Conclusions • For science to progress quickly there is great benefit in moving away from a “trusted source” model to one based on transparency and data provenance • Open Notebook Science offers an efficient way to make research transparent and discoverable

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