Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data.

Liquid chromatography coupled with high-resolution mass spectrometry data-independent acquisition (LC-HRMS/DIA), including MSE, enable comprehensive metabolomics analyses though they pose challenges for data processing with automatic annotation and molecular networking (MN) implementation. This motivated the present proposal, in which we introduce DIA-IntOpenStream, a new integrated workflow combining open-source software to streamline MSE data handling. It provides 'in-house' custom database construction, allows the conversion of raw MSE data to a universal format (.mzML) and leverages open software (MZmine 3 and MS-DIAL) all advantages for confident annotation and effective MN data interpretation. This pipeline significantly enhances the accessibility, reliability and reproducibility of complex MSE/DIA studies, overcoming previous limitations of proprietary software and non-universal MS data formats that restricted integrative analysis. We demonstrate the utility of DIA-IntOpenStream with two independent datasets: dataset 1 consists of new data from 60 plant extracts from the Ocotea genus; dataset 2 is a publicly available actinobacterial extract spiked with authentic standard for detailed comparative analysis with existing methods. This user-friendly pipeline enables broader adoption of cutting-edge MS tools and provides value to the scientific community. Overall, it holds promise for speeding up metabolite discoveries toward a more collaborative and open environment for research.

Chalcones Acting as Inhibitors of Cholinesterases, ß-Secretase and ß- Amyloid Aggregation and other Targets for Alzheimer's Disease: A Critical Review.

BACKGROUND: Alzheimer's disease (AD) involves an irreversible and progressive neurodegeneration, with multifactorial pathophysiology, including the cholinergic deficit, amyloid plaques, neurofibrillary tangles, oxidative stress, and neurodegeneration. Despite the severity of the disease, the therapeutic arsenal is limited, arousing the interest of researchers to search for substances that can act on these markers. OBJECTIVE: In this review, we highlight some relevant points, such as the ability of chalcones to act on different targets related to the pathophysiology of Alzheimer's disease; cholinesterases, amyloid peptide, beta-secretase and other biomarkers. METHOD: This mini-review covered the literature concerning chalcones bioactivity from 2010 until now. In addition to the theoretical review, we included the prediction of physicochemical properties using SwissADME software. RESULTS: We found that the majority of the chalcones have been tested against cholinesterases, with moderate to good potencies, but in recent years, the number of publications related to targets of the amyloid hypothesis has been growing. Regarding the physicochemical properties, chalcones have a good profile, except for the water solubility, which is not favorable. CONCLUSION: The most important characteristic of these molecules is that many of the examples mentioned here act on more than one target, characterizing them as multi-target compounds. Regarding predicted properties, solubility stands out as the most problematic one; however, these structures can incorporate functional groups that circumvent this problem of solubility without interfering in the biological activity.

Antimicrobial Isoflavones and Derivatives from Erythrina (Fabaceae): Structure Activity Perspective (Sar & Qsar) on Experimental and Mined Values Against Staphylococcus Aureus.

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).

Study of chromatographic retention of natural terpenoids by chemoinformatic tools.

The study of chromatographic retention of natural products can be used to increase their identification speed in complex biological matrices. In this work, six variables were used to study the retention behavior in reversed phase liquid chromatography of 39 sesquiterpene lactones (SL) from an in-house database using chemoinformatics tools. To evaluate the retention of the SL, retention parameters on an ODS C-18 column in two different solvent systems were experimentally obtained, namely, MeOH-H2O 55:45 and MeCN-H2O 35:75. The chemoinformatics approach involved three descriptor type sets (one 2D and two 3D) comprising three groups of each (four, five, and six descriptors), two different training and test sets, four algorithms for variable selection (best first, linear forward, greedy stepwise, and genetic algorithm), and two modeling methods (partial least-squares regression and back-propagation artificial neural network). The influence of the six variables used in this study was assessed in a holistic context, and influences on the best model for each solvent system were analyzed. The best set for MeOH-H2O showed acceptable correlation statistics with training R(2) = 0.91, cross-validation Q(2) = 0.88, and external validation P(2) = 0.80, and the best MeCN-H2O model showed much higher correlation statistics with training R(2) = 0.96, cross-validation Q(2) = 0.92, and external validation P(2) = 0.91. Consensus models were built for each chromatographic system, and although all of them showed an improved statistical performance, only one for the MeCN-H2O system was able to separate isomers as well as to improve the performance. The approach described herein can therefore be used to generate reproducible and robust models for QSRR studies of natural products as well as an aid for dereplication of complex biological matrices using plant metabolomics-based techniques.

Preliminary antifungal and cytotoxic evaluation of synthetic cycloalkyl[b]thiophene derivatives with PLS-DA analysis.

A series of 2-[(arylidene)amino]-cycloalkyl[b]thiophene-3-carbonitriles (2a-x) was synthesized by incorporation of substituted aromatic aldehydes in Gewald adducts (1a-c). The title compounds were screened for their antifungal activity against Candida krusei and Criptococcus neoformans and for their antiproliferative activity against a panel of 3 human cancer cell lines (HT29, NCI H-292 and HEP). For antiproliferative activity, the partial least squares (PLS) methodology was applied. Some of the prepared compounds exhibited promising antifungal and proliferative properties. The most active compounds for antifungal activity were cyclohexyl[b]thiophene derivatives, and for antiproliferative activity cycloheptyl[b]thiophene derivatives, especially 2-[(1H-indol-2-yl-methylidene)amino]- 5,6,7,8-tetrahydro-4H-cyclohepta[b]thiophene-3-carbonitrile (2r), which inhibited more than 97 % growth of the three cell lines. The PLS discriminant analysis (PLS-DA) applied generated good exploratory and predictive results and showed that the descriptors having shape characteristics were strongly correlated with the biological data.