Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.CNPqCNPqUEPBUEP

Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones

Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (similar to 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons. (C) 2008 Elsevier Masson SAS. All rights reserved

Gastmans, Application of Artificial Intelligence in Organic Chemistry. Part XIX. Pattern recognition and structural determination of flavonoids using

Abstract. 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) 13 C 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 NMR 13 C 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

Self-organizing maps in chemotaxonomic studies of Asteraceae: a classification oftribes using flavonoid data

Flavonoids have shown good chemical markers for Asteraceae. In this paper, 4,700 occurrences of flavonoids (about 800 compounds) were considered in an expert system developed for taxonomic purposes. Through the use of Self-Organizing Maps (SOM) phylogenetic relationships among the subfamilies and tribes of Asteraceae were established. These taxa were classified on the basis of their occurrences and oxidation patterns of the flavonoids. The obtained results show the separation between the two subfamilies of Asteraceae the correlation among the tribes of the Cichiroideae subfamily according to the topological tree proposed by Karis the clustering of the tribes according to the tree proposed by Jansen based on CpDNA and the separation of the tribes classified in the Asteroideae subfamily as well as the tribes based on the methoxylation x glycosylation level in flavonoids. From these results one can affirm that the method applied with chemical data can be used as a complementary tool in plant classification

Pattern Recognition of Guaiane Sesquiterpenes BioChem Press 13 C NMR Pattern Recognition of Guaiane Sesquiterpenes

Abstract Motivation. Sesquiterpenes are a class of naturally occurring substances that show various biological and pharmacological properties such as inhibitors of cell growth, antifungal, antibacterial, antimalarial, antiviral, etc activities. However, jointly with many biological properties, this class exhibits a greater diversity and complexity of structures, becoming a great challenge in the structural elucidation of its compounds for spectroscopists. Thus, the development of an expert system containing a set of rules for structural pattern recognition, based on 13 C NMR spectral data, for new compounds is of utmost importance for the natural product researchers. Method. SISTEMAT is an expert system developed to aid in the structural determination of natural products. In this study we have investigated the application of system for the 13 C NMR pattern recognition of guaiane sesquiterpenes. By using a database containing 200 substances, and the programs of the system SISTEMAT, various 13 C NMR heuristic rules for structural elucidation were obtained. These rules were evaluated with a set of 25 new guaianes recently published in literature. Results. The prediction performance of the system from the tests executed with the compounds shows that the system was able to propose substructures in 96.0% of the studied cases, where in 98.1% of these are overlapping substructures. Conclusions. SISTEMAT is a powerful tool for structural elucidation with many potential applications in natural products' field. In the present study we have demonstrated the predictive ability and applicability of a 13 C NMR pattern recognition method for the guaiane sesquiterpenes. Availability. The software used in this study can be consulted by contacting the corresponding author

Computer-Assisted Approach to Structural Elucidation of Lignans

This paper reports an expert system (SISTEMAT) developed for structural determination of diverse chemical classes of natural products, including lignans, based mainly on 13C NMR and 1H NMR data of these compounds. The system is composed of five programs that analyze specific data of a lignan and shows a skeleton probability for the compound. At the end of analyses, the results are grouped, the global probability is computed, and the most probable skeleton is exhibited to the user. SISTEMAT was able to properly predict the skeletons of 80% of the 30 lignans tested, demonstrating its advantage during the structural elucidation course in a short period of time.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP

Computer-aided Structure Elucidation of Neolignans

This paper describes a new module of the expert system SISTEMAT used for the prediction of the skeletons of neolignans by (13)C NMR, (1)H NMR and botanical data obtained from the literature. SISTEMAT is composed of MACRONO, SISCONST, C13MACH, H1MACH and SISOCBOT programs, each analyzing data of the neolignan in question to predict the carbon skeleton of the compound. From these results, the global probability is computed and the most probable skeleton predicted. SISTEMAT predicted the skeletons of 75% of the 20 neolignans tested, in a rapid and simple procedure demonstrating its advantage for the structural elucidation of new compounds.CNPqConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPES

Withanolides from Aureliana fasciculata var. fasciculata

In the first phytochemical study of the Aureliana genus (Solanaceae), two new withanolides, 1 and 2, together with two known sterols, were isolated from the MeOH extract of the leaves of Aureliana fasciculata var. fasciculata. The structures were established as (4S,22R)-16 alpha-acetoxy-5 beta,6 beta-epoxy-4 beta,17 alpha-dihydroxy-1-oxowitha-2,24-dienolide (aurelianolide A) and (4S,22R)-16 alpha-acetoxy-4 beta,17 alpha-dihydroxy-1-oxowitha-2,5,24-trienolide (aurelianolide B). The new compounds possessed the unusual 16 alpha,17 alpha-dioxygenated group and were fully characterized by spectroscopic techniques, including (1)H- and (13)C-NMR (DEPT), as well as 2D-NMR (HMBC, HMQC, (1)H, (1)H-COSY, NOESY) experiments, and HR-MS.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)CNPqFAPERJFAPERJFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPES