Robust anti-inflammatory activity of genistein against neutrophil elastase: a microsecond molecular dynamics simulation study

Chemical annotation of the infusion of Jungia floribunda Less and its inhibitory potential on the elastase enzyme

Jungia floribunda Less. is a shrub belonging to the Asteraceae. The infusion of its leaves has been used, in folk medicine of several South American countries, as anti-inflammatory and hypoglycaemic agent. In the present study, the infusion of leaves from J. floribunda was obtained and its chemical composition was determined by UHPLC-MS associated with molecular network allowing the annotation of flavonoids, sesquiterpene lactones, coumarins, and chlorogenic acid derivatives. Besides, in vitro elastase activity assay was carried out with the infusion. As observed, elastase was inhibited at concentrations ranging from 15 to 240 µg/mL, reaching to 71% of inhibition at the maximum of evaluated concentration. Given that species of plants are promising sources for the discovery of new drugs, these results corroborate the infusion of J. floribunda as a potential source of bioactive compounds for the discovery of new inhibitors for elastase, besides its ethnopharmacological aspects.

Exploring putative drug properties associated with TNF-alpha inhibition and identification of potential targets in cardiovascular disease using machine learning-assisted QSAR modeling and virtual reverse pharmacology approach

Cardiovascular disease is a chronic inflammatory disease with high mortality rates. TNF-alpha is pro-inflammatory and associated with the disease, but current medications have adverse effects. Therefore, efficient inhibitors are urgently needed as alternatives. This study represents a structural-activity relationship investigation of TNF-alpha, curated from the ChEMBL database. Exploratory data analysis was performed to visualize the physicochemical properties of different bioactivity groups. The extracted molecules were subjected to PubChem and SubStructure fingerprints, and a QSAR-based Random Forest (QSAR-RF) model was generated using the WEKA tool. The QSAR random Forest model was built based on the SubStructure fingerprint with a correlation coefficient of 0.992 and 0.716 as the respective tenfold cross-validation scores. The variance important plot (VIP) method was used to extract the important features for TNF-alpha inhibition. The Substructure-based QSAR-RF (SS-QSAR-RF) model was validated using molecules from PubChem and ZINC databases. The generated model also predicts the pIC50 value of the molecules selected from the docking study followed by molecular dynamic simulation with the time step of 100 ns. Through virtual reverse pharmacology, we determined the main drug targets from the top four hit compounds obtained via molecular docking study. Our analysis included an integrated bioinformatics approach to pinpoint crucial targets like EGRF, HSP900A1, STAT3, PSEN1, AKT1, and MDM2. Further, GO and KEGG pathways analysis identified relevant cardiovascular disease-related pathways for the hub gene involved. However, this study provides valuable insights, it is important to note that it lacks experimental application. Future research may benefit from conducting in-vitro and in-vivo studies.

The obesogenic side of Genistein

Genistein (GN) has been highly recommended for its medicinal properties like anticancer, antidiabetic, antihyperlipidemic, antiviral, and antioxidant activities among others. Recently, scientists realized that Genistein is an endocrine disruptor. It is an obesogen that interferes with the endocrine system causing obesity through many mechanisms like inducing adipocyte differentiation, lipid accumulation, and transformation of some stem cells into adipocytes (bone marrow mesenchymal stem cells for example) in vitro. Animal studies show that GN upregulates genes associated with adipogenesis like CCAAT/enhancer binding protein alpha (Cebpα), CCAAT/enhancer binding protein beta (Cebpβ), and PPARγ. In silico studies reveal a strong binding affinity for estrogen receptors. All these findings were contingent on concentration and tissues. It is beyond dispute that obesity is one of the most frustrating medical conditions under the sun. The pathophysiology of this disease was first attributed to a high-calorie diet and lack of physical activity. However, studies proved that these two factors are not enough to account for obesity in both children and adults. This mini review highlights how Genistein interaction with the peroxisome proliferator-activated receptor gamma protein can cause obesity.

Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease

Acute respiratory distress syndrome (ARDS) is intricately linked with SARS-CoV-2-associated disease severity and mortality, especially in patients with co-morbidities. Lung tissue injury caused as a consequence of ARDS leads to fluid build-up in the alveolar sacs, which in turn affects oxygen supply from the capillaries. ARDS is a result of a hyperinflammatory, non-specific local immune response (cytokine storm), which is aggravated as the virus evades and meddles with protective anti-viral innate immune responses. Treatment and management of ARDS remain a major challenge, first, because the condition develops as the virus keeps replicating and, therefore, immunomodulatory drugs are required to be used with caution. Second, the hyperinflammatory responses observed during ARDS are quite heterogeneous and dependent on the stage of the disease and the clinical history of the patients. In this review, we present different anti-rheumatic drugs, natural compounds, monoclonal antibodies, and RNA therapeutics and discuss their application in the management of ARDS. We also discuss on the suitability of each of these drug classes at different stages of the disease. In the last section, we discuss the potential applications of advanced computational approaches in identifying reliable drug targets and in screening out credible lead compounds against ARDS.