This work describes the new improvements of the SISlEMAT project, one system for structural elucidation mainly in the field of Natural Products Chemistry. Some examples of the resolution of problems using13C Nuclear Magnetic Resonance and Mass Spectroscopy are given. Programs to discover new heuristic rules for structure generation are discussed. The data base contains about 100013C NMR spectra.
This work describes the creation of heuristics rules based on13C-NMR spectroscopy that characterize several skeletal types of diterpenes. Using a collection of 2745 spectra we built a database linked to the expert system SISTEMAT. Several programs were applied to the database in order to discover characteristic signals that identify with a good performance, a large diversity of skeletal types. The heuristic approach used was able to differentiate groups of skeletons based firstly on the number of primary, secondary, tertiary and quaternary carbons, and secondly the program searches, for each group, if there are ranges of chemical shifts that identifies specific skeletal type. The program was checked with 100 new structures recently published and was able to identify the correct skeleton in 65 of the studied cases. When the skeleton has several hundreds of compounds, for example, the labdanes, the program employs the concept of subskeletal, and does not classify in the same group labdanes with double bounds at different positions. The chemical shift ranges for each subskeletal types and the structures of all skeletal types are given. The consultation program can be obtained from the authors.
This essay describes another improvement to the expert system named SISTEMAT. The purpose of such improvement is to help chemists who work with natural products to figure out chemical structures. SISTEMAT uses Nuclear Magnetic Resonance (NMR)13C data to ensemble compatible substructures according to related spectra. The system also is able to suggest a list of probable carbon skeletons. Those will work as models to structure generating programs, reducing the combinatorial explosion problem. This is the first essay from our research group which shows our system applications to aromatic compounds. A database with 700 NMR13C spectra of flavonoids obtained from the literature was used. We applied heuristic SISTEMAT in order to discover ranges of chemical shifts that characterise several skeleton types. The diversity of flavonoid structures is due to several oxidation patterns at rings A and B. This phenomenon causes a great complexity in the absorptions at the aromatic region. Heuristic SISTEMAT was able to discover more accurate rules that differentiate specific patterns of oxidation for some skeleton types. The performance of the software was checked against a higher complex structure of a dimeric flavonoid recently isolated. The system gives only two possibilities of skeleton types (among 70 others). Both substructures found by the program showed correct linkages between carbons 2 and 7″and 4 and 8″of the monomers.
A procedure for the identification of substituent groups (viz. angelate, tiglate, etc.) attached to any of the atoms in the conventional skeleton of a natural product is described. It consists in the use of the program MACRONO, which was developed for finding subspectra due to the carbons in the said substituent groups amid the raw13C NMR spectroscopic data from any given natural product (by means of comparisons of all possible subsets of the observed chemical shifts with those contained in an apposite database, built with literature13C NMR spectroscopic data regarding those groups). This procedure enables one to expunge the chemical shifts not due to skeletal carbons from the initial dataset, which then can be input to the expert system SISTEMAT, for skeletal identification.
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