Matevž Pesek (Author), Andraž Juvan (Author), Jure Jakoš (Author), Janez Košmrlj (Author), Matija Marolt (Author), Martin Gazvoda (Author)

Abstract

Herein, we report a computational algorithm that follows a spectroscopist-driven elucidation process of the structure of an organic molecule based on IR, $^1$H and $^{13}$C NMR, and MS tabular data. The algorithm is independent from database searching and is based on a bottom-up approach, building the molecular structure from small structural fragments visible in spectra. It employs an analytical combinatorial approach with a graph search technique to determine the connectivity of structural fragments that is based on the analysis of the NMR spectra, to connect the identified structural fragments into a molecular structure. After the process is completed, the interface lists the compound candidates, which are visualized by the WolframAlpha computational knowledge engine within the interface. The candidates are ranked according to the predefined rules for analyzing the spectral data. The developed elucidator has a user-friendly web interface and is publicly available (http://schmarnica. si).

Keywords

algoritem;organske molekule;infrardeča spektroskopija;molekulska struktura;jedrska magnetna resonanca;NMR;algorithm;organic molecules;infrared spectroscopy;molecular structure;nuclear magnetic resonance spectroscopy;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FKKT - Faculty of Chemistry and Chemical Technology
UDC: 547:544.1:004.65
COBISS: 49245187 Link will open in a new window
ISSN: 1549-9596
Views: 26
Downloads: 4
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary keywords: algoritem;organske molekule;infrardeča spektroskopija;molekulska struktura;jedrska magnetna resonanca;NMR;
Type (COBISS): Article
Pages: str. 756-763
Volume: ǂVol. ǂ61
Issue: ǂiss. ǂ2
Chronology: 22 Feb. 2021
DOI: 10.1021/acs.jcim.0c01332
ID: 18198308