Flavonoids have demonstrated in vivo and in vitro leishmanicidal, trypanocidal, antioxidant, and prooxidant properties. The chemotherapy of trypanosomiasis and leishmaniasis lacks efficacy, presents high toxicity, and is related to the development of drug resistance. Thus, a series of 40 flavonoids were investigated with the purpose of correlating these properties via structure and activity analyses based on integrated networks and QSAR models. The classical groups for the antioxidant activity of flavonoids were combined in order to explain the influence of antioxidant and prooxidant activities on the antiparasitic properties. These analyses become useful for the development of efficient treatments for leishmaniasis and trypanosomiasis. Finally, the dual activity of flavonoids presenting both anti‐ and prooxidant activities revealed that the existence of a balance between these two features could be important to the development of adequate therapeutic strategies.

Nonsteroidal anti-inflammatory drugs are the most used anti-inflammatory medicines in the world. Side effects still occur, however, and some inflammatory pathologies lack efficient treatment. Cyclooxygenase and lipoxygenase pathways are of utmost importance in inflammatory processes; therefore, novel inhibitors are currently needed for both of them. Dual inhibitors of cyclooxygenase-1 and 5-lipoxygenase are anti-inflammatory drugs with high efficacy and low side effects. In this work, 57 leaf extracts (EtOH-H₂O 7 : 3, v/v) from Asteraceae species with in vitro dual inhibition of cyclooxygenase-1 and 5-lipoxygenase were analyzed by high-performance liquid chromatography-high-resolution-ORBITRAP-mass spectrometry analysis and subjected to in silico studies using machine learning algorithms. The data from all samples were processed by employing differential expression analysis software coupled to the Dictionary of Natural Products for dereplication studies. The 6052 chromatographic peaks (ESI positive and negative modes) of the extracts were selected by a genetic algorithm according to their respective anti-inflammatory properties; after this procedure, 1241 of them remained. A study using a decision tree classifier was carried out, and 11 compounds were determined to be biomarkers due to their anti-inflammatory potential. Finally, a model to predict new biologically active extracts from Asteraceae species using liquid chromatography-mass spectrometry information with no prior knowledge of their biological data was built using a multilayer perceptron (artificial neural networks) with the back-propagation algorithm using the biomarker data. As a result, a new and robust artificial neural network model for predicting the anti-inflammatory activity of natural compounds was obtained, resulting in a high percentage of correct predictions (81 %), high precision (100 %) for dual inhibition, and low error values (mean absolute error = 0.3), as also shown in the validation test. Thus, the biomarkers of the Asteraceae extracts were statistically correlated with their anti-inflammatory activities and can therefore be useful to predict new anti-inflammatory extracts and their anti-inflammatory compounds using only liquid chromatography-mass spectrometry data.

The traditional work of a natural products researcher consists in large part of time-consuming experimental work, collecting biota to prepare and analyze extracts and to identify innovative metabolites. However, along this long scientific path, much information is lost or restricted to a specific niche. The large amounts of data already produced and the science of metabolomics reveal new questions: Are these compounds known or new? How fast can this information be obtained? To answer these and other relevant questions, an appropriate procedure to correctly store information on the data retrieved from the discovered metabolites is necessary. The SistematX (http://sistematx.ufpb.br) interface is implemented considering the following aspects: (a) the ability to search by structure, SMILES (Simplified Molecular-Input Line-Entry System) code, compound name and species; (b) the ability to save chemical structures found by searching; (c) compound data results include important characteristics for natural products chemistry; and (d) the user can find specific information for taxonomic rank (from family to species) of the plant from which the compound was isolated, the searched-for molecule, and the bibliographic reference and Global Positioning System (GPS) coordinates. The SistematX homepage allows the user to log into the data management area using a login name and password and gain access to administration pages. In this article, we introduced a modern and innovative web interface for the management of a secondary metabolite database. With its multiplatform design, it is able to be properly consulted via the internet and managed from any accredited computer. The interface provided by SistematX contains a wealth of useful information for the scientific community about natural products, highlighting the locations of species from which compounds are isolated.

Cyclooxygenase and 5-lipoxygenase are enzymes that catalyze important inflammatory pathways, suggesting that dual cyclooxygenase/lipoxygenase inhibitors should be more efficacious as anti-inflammatory medicines with lower side effects than the currently available nonsteroidal anti-inflammatory drugs. Many plants from the family Asteraceae have anti-inflammatory activities, which could be exerted by inhibiting the cyclooxygenase-1 and 5-lipoxygenase enzymes. Nevertheless, only a small number of compounds from this family have been directly evaluated for their ability to inhibit the enzymes in cell-free assays. Therefore, this study systematically evaluated 57 Asteraceae extracts in vitro in enzyme activity experiments to determine whether any of these extracts exhibit dual inhibition of cyclooxygenase-1 and 5-lipoxygenase. The chemical profiles of the extracts were obtained by the high-performance liquid chromatography-ultraviolet-diode array detector method, and their major constituents were dereplicated. Of the 57 tested extracts, 13 (26.6 %, IC₅₀ range from 0.03–36.2 µg/mL) of them displayed dual inhibition. Extracts from known anti-inflammatory herbs, food plants, and previously uninvestigated species are among the most active. Additionally, the extract action was found to be specific with IC₅₀ values close to or below those of the standard inhibitors. Thus, the active extracts and active substances of these species are potent inhibitors acting through the mechanism of dual inhibition of cyclooxygenase-1 and 5-lipoxygenase. The extracts were prepared for this study using nontoxic extraction solvents (EtOH-H₂O), requiring only a small amount of plant material to carry out the bioassays and the phytochemical analyses. In summary, this study demonstrated the potential of the investigated species as dual inhibitors, revealing their potential as pharmaceuticals or nutraceuticals.

Prenylated (iso)flavonoids, -flavans and pterocarpans from taxa in Erythrina are repeatedly flagged as potent antimicrobial compounds. In the current study, bark from E. lysistemon was extracted and seven isoflavone derivatives were purified: erybraedin A (1), phaseollidin (2), abyssinone V-4′ methyl ether (3), eryzerin C (4), alpumisoflavone (5), cristacarpin (6) and lysisteisoflavone (7). Minimum inhibition concentration (MIC) values were determined against a range of species of bacteria (skin pathogens), then values for another 67 derivatives from Erythrina, only against Staphylococcus aureus, were mined from the literature. Of the seven isolates, MIC values widely ranged from 1–600 μg/mL, with no obvious pattern of selectivity for Gram-types. Nevertheless, using the mined and experimentally determined values against S. aureus, Klekota-Roth fragments (Structure Activity Relationship: SAR) were determined then used as molecular descriptors to make a ‘decision tree’ based on structural characters inspired by the classes of antimicrobial potency (classes A-D). Furthermore, to make quantitative predictions of MIC values (Quantitative SAR: QSAR) ‘pace regression’ was utilized and validated (R² = 0.778, Q² = 0.727 and P² = 0.555). Evidently, the position and degree of prenylation is important; however, the presence of hydroxyl groups at positions 5 and 7 in ring A and 4′ in ring B is associated with lower MIC values. While antimicrobial results continue to validate the traditional use of E. lysistemon extracts (or Erythrina generally) in therapeutic applications consistent with anti-infection, it is surprising that this class of compound is not being utilized more often in general industry applications, such as food or cosmetic preservation, or in topical antimicrobial creams. Prenylated (iso)flavonoids are derived from several other Genera, such as Dorstenia (Moraceae), Ficus (Moraceae), Glycyrrhiza (Fabaceae), Paulownia (Lamiales) or Pomifera (Moraceae).