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September 10-13, 2018
University of Leipzig, Leipzig, Germany

Related Materials

Related presentations, posters, and scientific talks from this event have been posted here for your reference. Please click the associated link to download.

Using Predicted 13C NMR Spectra with Open Resources for Structure Dereplication, D. Argyropoulos, S. Golotvin, R. Pol, J. DiMartino, A. Moser and B. Pautler

Poster Schedule

Using Predicted 13C NMR Spectra with Open Resources for Structure Dereplication
Michel Riese, Dimitris Argyropoulos, Sergey Golotvin, Rostislav Pol, Joe DiMartino, Arvin Moser
Poster #: 15

Abstract: For successful natural product-based drug discovery, it is critical to reliably separate and identify active components in natural product mixtures. Dereplication is the practice of screening active compounds early in the development process, to recognize and eliminate compounds that have been previously studied. This enables scientists to focus on testing truly 'unknown' compounds. For efficient dereplication, one must be able to easily identify characteristic spectral "fingerprints" of compounds in order to identify their structure and have access to databases containing known structures. The 13C NMR spectrum of a compound can be considered a fingerprint since it is virtually unaffected by conditions such as pH, concentration, and solvent effects. It is also largely magnetic field independent, since there are no couplings that could cause variations in stronger or weaker fields. As a result, it is very easy and accurate to predict. To identify experimental 13C spectra, one can consider predicting the 13C spectra of known chemical structures found in "open" databases (e.g. PubChem[1]) and seeing if there is a match. Predicted spectra benefit from being magnetic field independent, can be adjusted for solvents, and can be very accurate if the correct algorithms are used [2].

Here we explore the possibilities and limitations of using predicted 13C spectra for structures from open databases for dereplication.

  1. Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, Han L, He J, He S, Shoemaker BA, Wang J, Yu B, Zhang J, Bryant SH. PubChem Substance and Compound databases. Nucleic Acids Res. 2016 Jan 4; 44(D1):D1202-13. Epub 2015 Sep 22 [PubMed PMID: 26400175] doi: 10.1093/nar/gkv951.
  2. Data presented by Burkhard Kirste, FU Berlin, 38th FGNMR Meeting, Sept. 2016, Dusseldorf