Computer-Aided Chemotaxonomy and Bioprospecting Study of Diterpenes of the Lamiaceae Family

• Published in: Molecules (Basel, Switzerland) Vol. 24; no. 21; p. 3908
• Main Authors: Barbosa Silva Cavalcanti, Andreza, Costa Barros, Renata Priscila, Costa, Vicente Carlos de Oliveira, Sobral da Silva, Marcelo, Fechine Tavares, Josean, Scotti, Luciana, Scotti, Marcus Tullius
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.10.2019; MDPI
• Subjects: Algorithms; Angiosperms; Biological activity; Bioprospecting; chemotaxonomic; Chemotaxonomy; Classification; Databases as Topic; Diterpenes; Diterpenes - chemistry; Diterpenes - classification; Genera; Geographical locations; Lamiaceae; Lamiaceae - classification; Localization; Machine Learning; Metabolites; Natural products; Phylogenetics; Phylogeny; Secondary metabolites; Self organizing maps; Software; soms; Support vector machines; Taxonomy; database; Lamiaceae; chemotaxonomic; diterpenes; SOMs
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules24213908

Lamiaceae is one of the largest families of angiosperms and is classified into 12 subfamilies that are composed of 295 genera and 7775 species. It presents a variety of secondary metabolites such as diterpenes that are commonly found in their species, and some of them are known to be chemotaxonomic markers. The aim of this work was to construct a database of diterpenes and to use it to perform a chemotaxonomic analysis among the subfamilies of Lamiaceae, using molecular descriptors and self-organizing maps (SOMs). The 4115 different diterpenes corresponding to 6386 botanical occurrences, which are distributed in eight subfamilies, 66 genera, 639 different species and 4880 geographical locations, were added to SistematX. Molecular descriptors of diterpenes and their respective botanical occurrences were used to generate the SOMs. In all obtained maps, a match rate higher than 80% was observed, demonstrating a separation of the Lamiaceae subfamilies, corroborating with the morphological and molecular data proposed by Li et al. Therefore, through this chemotaxonomic study, we can predict the localization of a diterpene in a subfamily and assist in the search for secondary metabolites with specific structural characteristics, such as compounds with potential biological activity.