An In Silico and an In Vitro Inhibition Analysis of Glycogen Phosphorylase by Flavonoids,Styrylchromones, and Pyrazoles

Glycogen phosphorylase (GP) is a key enzyme in the glycogenolysis pathway. GP inhibitors are currently under investigation as a new liver-targeted approach to managing type 2 diabetes mellitus (DM). The aim of the present study was to evaluate the inhibitory activity of a panel of 52 structurally related chromone derivatives; namely, flavonoids, 2-styrylchromones, 2-styrylchromone-related derivatives [2-(4-arylbuta-1,3-dien-1-yl)chromones], and 4- and 5-styrylpyrazoles against GP, using in silico and in vitro microanalysis screening systems. Several of the tested compounds showed a potent inhibitory effect. The structure–activity relationship study indicated that for 2-styrylchromones and 2-styrylchromone-related derivatives, the hydroxylations at the A and B rings, and in the flavonoid family, as well as the hydroxylation of the A ring, were determinants for the inhibitory activity. To support the in vitro experimental findings, molecular docking studies were performed, revealing clear hydrogen bonding patterns that favored the inhibitory effects of flavonoids, 2-styrylchromones, and 2-styrylchromone-related derivatives. Interestingly, the potency of the most active compounds increased almost four-fold when the concentration of glucose increased, presenting an IC₅₀ < 10 µM. This effect may reduce the risk of hypoglycemia, a commonly reported side effect of antidiabetic agents. This work contributes with important considerations and provides a better understanding of potential scaffolds for the study of novel GP inhibitors.     

Clay Mineral Minerals as a Strategy for Biomolecule Incorporation: Amino Acids Approach

The potential use of amino acids by ruminal microorganisms converting them into microbial protein for ruminants makes it challenging to supplement these nutrients in an accessible form in animals’ diets. Several strategies to protect amino acids from ruminal degradation were reported, producing amino acids available for the protein used in the intestine called “bypass.” The intercalation of biomolecules in clay mineral minerals has gained notoriety due to its ability to support, protect, transport, physicochemical properties and non-toxicity. This study aimed to investigate the incorporation of L-lysine (Lys), L-methionine (Met), and L-tryptophan (Trp) amino acids in the clay minerals sepiolite (Sep) and Veegum^® (Veg) using the adsorption method. The characterization techniques of X-ray diffraction and infrared spectroscopy indicated the presence of biomolecules in the inorganic matrices. Elemental and thermal analyzes monitored the percentages of incorporated amino acids. They showed better incorporation capacities for Veg, such as Met-Veg < Lys-Veg < Trp-Veg and Lys-Sep < Met-Sep < Trp-Sep for sepiolite, except for the incorporation of Met. Matrices provide a promising alternative for planning the administration of biomolecules, using essential amino acids as models, and may offer an alternative to improve functional diet strategies.     

Protective effects of beet (Beta vulgaris) leaves extract against oxidative stress in endothelial cells in vitro

Beetroot is an herb used worldwide as a food product, raw material for food industry, ethanol production and source of food coloring. Beet leaves are an unconventional food with antioxidant properties, which might neutralize reactive oxygen species (ROS) induced by oxidized Low‐Density Lipoprotein (LDL) present in dyslipidemias. This study aimed to elucidate the effects of beet leaves on the suppression of LDL oxidative processes. Beet leaves extract was produced, characterized, and tested for its antioxidant capacity using endothelial cells in vitro. A model of human umbilical vein endothelial cells was used in various tests, including viability assay, molecular analysis of antioxidant genes, ROS labeling, and macrophage adhesion assay. The extract improved the antioxidative protection of endothelial cells against different agents including oxidized LDL‐cholesterol and H₂O₂. It acted on ROS directly due to its high content of natural antioxidants, but also due to the activation and improvement of cellular defenses such as Superoxide dismutase 1, Superoxide dismutase 2, and catalase. The inhibition of LDL‐mediated oxidative effects on endothelial cells may turn this unconventional food a functional food with great potential for phytotherapy of atherosclerosis as an adjuvant for medicinal treatments.     

Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

Advances in imaging acquisition techniques allow multiple imaging modalities to be collected from the same subject. Each individual modality offers limited yet unique views of the functional, structural, or dynamic temporal features of the brain. Multimodal fusion provides effective ways to leverage these complementary perspectives from multiple modalities. However, the majority of current multimodal fusion approaches involving functional magnetic resonance imaging (fMRI) are limited to 3D feature summaries that do not incorporate its rich temporal information. Thus, we propose a novel three‐way parallel group independent component analysis (pGICA) fusion method that incorporates the first‐level 4D fMRI data (temporal information included) by parallelizing group ICA into parallel ICA via a unified optimization framework. A new variability matrix was defined to capture subject‐wise functional variability and then link it to the mixing matrices of the other two modalities. Simulation results show that the three‐way pGICA provides highly accurate cross‐modality linkage estimation under both weakly and strongly correlated conditions, as well as comparable source estimation under different noise levels. Results using real brain imaging data identified one linked functional–structural–diffusion component associated to differences between schizophrenia and controls. This was replicated in an independent cohort, and the identified components were also correlated with major cognitive domains. Functional network connectivity revealed visual–subcortical and default mode‐cerebellum pairs that discriminate between schizophrenia and controls. Overall, both simulation and real data results support the use of three‐way pGICA to identify multimodal spatiotemporal links and to pursue the study of brain disorders under a single unifying multimodal framework.     

Applicability of forensic facial approximation in the recognition process of unclaimed victims

BackgroundIdentifying bodies in a state of putrefaction, skeletonization or mutilation is often difficult. In these cases, it is possible to use auxiliary methods such as forensic facial approximation, considering the possibility of recognition by a relative or acquaintance, helping to obtain ante-mortem data for the identification process. The aims of the present study were to evaluate the capacity of recognition of individuals from digital facial approximation and to verify the association between the level of understanding of the issue by evaluators and the recognition success index.Methods16 skulls with previous photographic records were selected and then utilized for three-dimensional approximation using the digital technique, scanned by photogrammetry, and reconstructed by computerized method using open-source software. Twenty evaluators tried to recognize the facial approximation performed from images present in the photospreads.ResultsThe mean overall score was 23.75%, and it was observed that in only five approximations (31.24%) the option of correct recognition of the victim was the one that obtained the highest number of selections. False positives and negatives corresponded, respectively, to 11.56% and 12.5%.ConclusionsIt can be concluded that the methodology can provide recognition albeit in low numbers, and permitting the acquisition of ante-mortem data for the proper process of human identification through primary methods.     

Stability of neutral molecular polynitrogens: energy content and decomposition mechanisms

The potential application of all-nitrogen molecules as high energy density materials (HEDMs) has been attracting considerable scientific effort. If stable enough to be synthesized and stored, these systems may be used as a green source of energy. However, it is very difficult to obtain these structures under mild experimental conditions. Theoretical chemistry may aid in the search for polynitrogens that are more likely to have experimental usability. The barriers towards decomposition are an effective way to assess their stability, but these have not been thoroughly studied. Most of the previous effort in this direction focus on a single N_x case, each employing different accuracy levels, and the decomposition of caged structures has been little explored. Here we explore the stability and decomposition of several neutral molecular polynitrogens of different sizes and shapes using a common and accurate theoretical framework in order to compare among them, search for patterns and identify potential candidates for synthesis. We focus especially on new caged geometries, and our results indicate that the prismatic ones can be expected to present higher energy densities and be very stable with respect to unimolecular decomposition. It is shown that the energy content can be clearly stratified between chain, ring, cage and prismatic cage structures.

All-nitrogen molecules may provide green energy sources, releasing large amounts of energy without polluting byproducts. Here we predict the stability towards unimolecular decomposition of several structures and discuss their unusual chemistry.     

Drug repurposing and computational modeling for discovery of inhibitors of the main protease (Mpro) of SARS-CoV-2

The main protease (M^pro or 3CL^pro) is a conserved cysteine protease from the coronaviruses and started to be considered an important drug target for developing antivirals, as it produced a deadly outbreak of COVID-19. Herein, we used a combination of drug reposition and computational modeling approaches including molecular docking, molecular dynamics (MD) simulations, and the calculated binding free energy to evaluate a set of drugs in complex with the M^pro enzyme. Particularly, our results show that darunavir and triptorelin drugs have favorable binding free energy (−63.70 and −77.28 kcal mol⁻¹, respectively) in complex with the M^pro enzyme. Based on the results, the structural and energetic features that explain why some drugs can be repositioned to inhibit M^pro from SARS-CoV-2 were exposed. These features should be considered for the design of novel M^pro inhibitors.

Structural and energetic features explain why some drugs can be repositioned to inhibit M^pro from SARS-CoV-2.     

UHPLC-HRMS/MS on untargeted metabolomics: a case study with Copaifera (Fabaceae)

Untargeted metabolomics is a powerful tool in chemical fingerprinting. It can be applied in phytochemistry to aid species identification, systematic studies and quality control of bioproducts. This approach aims to produce as much chemical information as possible, without focusing on any specific chemical class, thus, requiring extensive chemometric effort. This study aimed to evaluate the feasibly of an untargeted metabolomics method in phytochemistry by a study case of the Copaifera genus (Fabaceae). This genus contains significant medicinal species used worldwidely. Copaifera exploitation issues include a lack of chemical data, ambiguous species identification methods and absence of quality control for its bioproducts. Different organs of five Copaifera species were analysed by UHPLC-HRMS/MS, GNPS platform and chemometric tools. Untargeted metabolomics enabled the identification of 19 chemical markers and 29 metabolites, distinguishing each sample by species, plant organs, and biome type. Chemical markers were classified as flavonoids, terpenoids and condensed tannins. The applied method provided reliable information about species chemodiversity using fast workflow with little sampling size. The untargeted approach by UHPLC-HRMS/MS proved to be a promising tool for species identification, pharmacological prospecting and in the future for the quality control of extracts used in the manufacture of bioproducts.

UHPLC-HRMS/MS untargeted metabolomics enabled distinction of Copaifera extracts by species, vegetative parts, and biome of origin based on 19 chemical markers.