title: Automated structure elucidation of organic molecules from (13)c NMR spectra using genetic algorithms and neural networks.
abstract: The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using (13)C NMR spectrum as readily obtainable information. (13)C NMR chemical shift, intensity, and multiplicity information is available from (13)C NMR DEPT spectra. By means of artificial neural networks a fast and accurate method for calculating the (13)C NMR spectrum of the generated structures exists. The approach is limited by the size of the constitutional space that has to be searched and by the accuracy of the shift prediction for the unknown substance. The method is implemented and tested successfully for organic molecules with up to 20 non-hydrogen atoms.
authors.affiliation: Institute of Organic Chemistry, Marie-Curie-Strasse 11, Universität Frankfurt, D-60439 Frankfurt, Germany. jens@jens-meiter.de
authors.forename: J
authors.initials: J
authors.lastname: Meiler
authors.forename: M
authors.initials: M
authors.lastname: Will
mesh_terms: D000465:Algorithms; D002247:Carbon Isotopes; D009682:Magnetic Resonance Spectroscopy; D015394:Molecular Structure; D016571:Neural Networks, Computer; D009930:Organic Chemicals / Q000737:chemistry*
chemical_list: D002247:Carbon Isotopes; D009930:Organic Chemicals