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Approach to Improving the Quality of Open Data in the Universe of Small Molecules

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Business Information Systems Workshops (BIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 373))

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Abstract

We describe an approach to improving the quality and interoperability of open data related to small molecules, such as metabolites, drugs, natural products, food additives, and environmental contaminants. The approach involves computer implementation of an extended version of the IUPAC International Chemical Identifier (InChI) system that utilizes the three-dimensional structure of a compound to generate reproducible compound identifiers (standard InChI strings) and universally reproducible designators for all constituent atoms of each compound. These compound and atom identifiers enable reliable federation of information from a wide range of freely accessible databases. In addition, these designators provide a platform for the derivation and promulgation of information regarding the physical properties of these molecules. Examples of applications include, compound dereplication, derivation of force fields used in determination of three-dimensional structures and investigations of molecular interactions, and parameterization of NMR spin system matrices used in compound identification and quantification. We are developing a data definition language (DDL) and STAR-based data dictionary to support the storage and retrieval of these kinds of information in digital resources. The current database contains entries for more than 90 million unique compounds.

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References

  1. Dashti, H., Westler, W.M., Markley, J.L., Eghbalnia, H.R.: Unique identifiers for small molecules enable rigorous labeling of their atoms. Sci. Data 4, 170073 (2017)

    Article  Google Scholar 

  2. Wilkinson, M.D., et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016)

    Article  Google Scholar 

  3. Dashti, H., Wedell, J.R., Westler, W.M., Markley, J.L., Eghbalnia, H.R.: Automated evaluation of consistency within the PubChem compound database. Sci. Data 6, 190023 (2019)

    Article  Google Scholar 

  4. Ulrich, E.L., Argentar, D., Klimowicz, A., Markley, J.L.: STAR/CIF macromolecular NMR data dictionaries and data file formats. Acta Crystallogr. A 52(a1), C577–C577 (1996)

    Article  Google Scholar 

  5. Ulrich, E.L., et al.: NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments. J. Biomol. NMR 73, 5–9 (2019)

    Article  Google Scholar 

  6. Hall, S.R., Spadaccini, N.: The STAR file: detailed specifications. J. Chem. Inf. Comput. Sci. 34, 505–508 (1994)

    Article  Google Scholar 

  7. Hall, S.R., Cook, A.P.F.: STAR dictionary definition language: initial specification. J. Chem. Inf. Comput. Sci. 35, 819–825 (1995)

    Article  Google Scholar 

  8. Spadaccini, N., Hall, S.R.: Extensions to the STAR file syntax. J. Chem. Inf. Model. 52, 1901–1906 (2012)

    Article  Google Scholar 

  9. Bourne, P.E., Berman, H.M., McMahon, B., Watenpaugh, K.D., Westbrook, J.D., Fitzgerald, P.M.D.: The macromolecular crystallographic information file (mmCIF). Meth. Enzymol. 277, 571–590 (1997)

    Article  Google Scholar 

  10. Dashti, H., Westler, W.M., Tonelli, M., Wedell, J.R., Markley, J.L., Eghbalnia, H.R.: Spin system modeling of nuclear magnetic resonance spectra for applications in metabolomics and small molecule screening. Anal. Chem. 89, 12201–12208 (2017)

    Article  Google Scholar 

  11. Dashti, H., et al.: Applications of parametrized NMR spin systems of small molecules. Anal. Chem. 90, 10646–10649 (2018)

    Article  Google Scholar 

  12. Pupier, M., et al.: NMReDATA, a standard to report the NMR assignment and parameters of organic compounds. Magn. Reson. Chem. 56, 703–715 (2018)

    Article  Google Scholar 

  13. Cornilescu, G., et al.: Progressive stereo locking (PSL): a residual dipolar coupling based force field method for determining the relative configuration of natural products and other small molecules. ACS Chem. Biol. 12, 2157–2163 (2017)

    Article  Google Scholar 

  14. Dashti, H., et al.: Robust nomenclature and software for enhanced reproducibility in molecular modeling of small molecules. bioRxiv, 429530 (2018)

    Google Scholar 

  15. Maciejewski, M.W., et al.: NMRbox: a resource for biomolecular NMR computation. Biophys. J. 112, 1529–1534 (2017)

    Article  Google Scholar 

  16. Ulrich, E.L., et al.: BioMagResBank. Nucleic Acids Res. 36, 402–408 (2008)

    Article  Google Scholar 

  17. Le Guennec, A., Tayyari, F., Edison, A.S.: Alternatives to nuclear overhauser enhancement spectroscopy presat and carr-purcell-meiboom-gill presat for NMR-based metabolomics. Anal. Chem. 89, 8582–8588 (2017)

    Article  Google Scholar 

  18. Burley, S.K., Berman, H.M., Kleywegt, G.J., Markley, J.L., Nakamura, H., Velankar, S.: Protein data bank (PDB): the single global macromolecular structure archive. Meth. Mol. Biol. 1607, 627–641 (2017)

    Article  Google Scholar 

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Acknowledgments

This work was funded in part by NIH Grants P41GM103399 in support of the National Magnetic Resonance Facility at Madison (NMRFAM), R01GM 109046 in support of the Biological Magnetic Resonance data Bank (BMRB), and P41GM111135 in support of the NMRbox project.

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Correspondence to John L. Markley .

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Markley, J.L., Dashti, H., Wedell, J.R., Westler, W.M., Ulrich, E.L., Eghbalnia, H.R. (2019). Approach to Improving the Quality of Open Data in the Universe of Small Molecules. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems Workshops. BIS 2019. Lecture Notes in Business Information Processing, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-030-36691-9_44

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  • DOI: https://doi.org/10.1007/978-3-030-36691-9_44

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  • Online ISBN: 978-3-030-36691-9

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