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.
Background: The emergence of a new coronavirus (CoV), named 2019-nCoV, in an outbreak located in the city of Wuhan, China, has resulted in the death more than 3,400 people this year alone and has caused worldwide alarm, particularly following previous CoV epidemics, including the Severe Acute Respiratory Syndrome (SARS) in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012. No treatment currently exists for infections caused by CoVs; however, some natural products may represent potential treatment resources, such as those that contain diterpenes. Objective: This study aimed to use computational methods to perform a virtual screen (VS) of candidate diterpenes with the potential to act as CoV inhibitors. Methods: 1,955 diterpenes, derived from a Nepetoideae subfamily (Lamiaceae), were selected using the SistematX tool (https://sistematx.ufpb.br), which were used to make predictions. From the ChEMBL database, 3 sets of chemical structures were selected for the construction of predictive models. Results: The chemical structures of molecules with known activity against SARS CoV, two of which were tested for activity against specific viral proteins and one of which was tested for activity against the virus itself, were classified according to their pIC50 values [-log IC50 (mol/l)]. Conclusion: The consensus analysis approach, combining both ligand- and structure-based VSs, 19 compounds were selected as potential CoV inhibitors, including isotanshinone IIA (01), tanshinlactone (02), isocryptotanshinone (03), and tanshinketolactone (04), which did not present toxicity within the evaluated parameters.
: The increasing number of computational studies in medicinal chemistry involving molecular docking has put the technique forward as promising in the design of Computer-Aided Drug Design. Considering the main method in the virtual screening based on the structure, consensus analysis of docking has been applied in several studies to overcome limitations of algorithms of different programs and mainly to increase the reliability of the results and reduce the number of false positives. However, some consensus scoring strategies are difficult to apply and in some cases are not reliable because of the small number of datasets tested. Thus, for such a methodology to be successful, it is necessary to understand why, when and how to use consensus docking. Therefore, the present study aims to present different approaches to docking consensus, applications and several scoring strategies that have been successful and can be applied in future studies.
Background: The growing demand for agricultural products has led to the misuse/overuse of insecticides; resulting in the use of higher concentrations and the need for ever more toxic products. Ecologically, bioinsecticides are considered better and safer than synthetic insecticides; they must be toxic to the target organism, yet with low or no toxicity to non-target organisms. Many plant extracts have seen their high insecticide potential confirmed under laboratory conditions, and in the search for plant compounds with bioinsecticidal activity, the Lamiaceae family has yielded satisfactory results. Objective: The aim of our study was to develop computer-assisted predictions for compounds with known insecticidal activity against Aphis gossypii and Drosophila melanogaster. Results and conclusion: Structure analysis revealed ent-kaurane, kaurene, and clerodane diterpenes as the most active, showing excellent results. We also found that the interactions formed by these compounds were more stable, or presented similar stability to the commercialized insecticides tested. Overall, we concluded that the compounds bistenuifolin L (1836) and bistenuifolin K (1931), were potentially active against A. gossypii enzymes; and salvisplendin C (1086) and salvixalapadiene (1195), are potentially active against D. melanogaster. We observed and highlight that the diterpenes bistenuifolin L (1836), bistenuifolin K (1931), salvisplendin C (1086), and salvixalapadiene (1195), present a high probability of activity and low toxicity against the species studied.
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