An efficient, catalyst-free, one-pot synthesis of 4H-chromene derivatives and investigating their biological activities and mode of interactions using molecular docking studies

Exploring the molecular mechanism of Dioscorea alata L. for the treatment of menstrual disorders using network pharmacology and molecular docking

Menstrual disorders (MDs), including premenstrual syndrome, amenorrhea, and dysmenorrhea, affect women globally. Dioscorea alata L., a traditional yam species, has been used medicinally, but its potential in treating MDs remains understudied. This study employs a network pharmacology approach to examine the effects of D. alata's secondary metabolites on MDs via multi-target mechanisms. Compounds were identified from literature and PubChem, while disease-related targets were gathered from GeneCards, DisGeNET, and CTD databases. Swiss target prediction was used to link compounds to targets. A protein-protein interaction (PPI) network was constructed using STRING, and Gene Ontology (GO) and KEGG enrichment analyses were conducted to predict functional pathways. Eighteen bioactive compounds and 120 therapeutic targets specific to MDs were identified. KEGG analysis revealed 20 significant pathways related to menstrual disturbances. Among the 120 targets, TNF α, PPARG, ESR1, and AKT1 were highlighted as key therapeutic targets. Molecular docking showed strong interactions between Daidzein and ESR1, Diosgenin and TNF α, Alatanin and AKT1, and PPARG. The findings suggest that D. alata's bioactive compounds, such as Diosgenin, Daidzein, Genistin, Cycloartane, and Alatanin, could modulate pathways involved in ovarian follicle formation, hormone regulation, estrogen receptor signaling, and the stress-activated MAP kinase pathway. This study provides new insights into the multi-target potential of D. alata for treating menstrual disorders, supporting further investigation and therapeutic development.

Recent Applications of Heteropolyacids and Related Compounds in Heterocycle Synthesis. Contributions between 2010 and 2020

Over the past two decades, polyoxometalates (POM) have received considerable attention as solid catalysts, due to their unique physicochemical characteristics, since, first, they have very strong Bronsted acidity, approaching the region of a superacid, and second, they are efficient oxidizers that exhibit rapid redox transformations under fairly mild conditions. Their structural mobility is also highlighted, since they are complex molecules that can be modified by changing their structure or the elements that compose them to model their size, charge density, redox potentials, acidity, and solubility. Finally, they can be used in substoichiometric amounts and reused without an appreciable loss of catalytic activity, all of which postulate them as versatile, economic and ecological catalysts. Therefore, in 2009, we wrote a review article highlighting the great variety of organic reactions, mainly in the area of the synthesis of bioactive heterocycles in which they can be used, and this new review completes that article with the contributions made in the same area for the period 2010 to 2020. The synthesized heterocycles to be covered include pyrimidines, pyridines, pyrroles, indoles, chromenes, xanthenes, pyrans, azlactones, azoles, diazines, azepines, flavones, and formylchromones, among others.

SAR and QSAR research on tyrosinase inhibitors using machine learning methods

Tyrosinase is a key rate-limiting enzyme in the process of melanin synthesis, which is closely related to human pigmentation disorders. Tyrosinase inhibitors can down-regulate tyrosinase to effectively reduce melanin synthesis. In this work, we conducted structure-activity relationship (SAR) study on 1097 diverse mushroom tyrosinase inhibitors. We applied five kinds of machine learning methods to develop 15 classification models. Model 5B built by fully connected neural networks and ECFP4 fingerprints achieved the highest prediction accuracy of 91.36% and Matthews correlation coefficient (MCC) of 0.81 on the test set. The applicability domains (AD) of classification models were defined by d S T D - P R O method. Moreover, we clustered the 1097 inhibitors into eight subsets by K-Means to figure out inhibitors' structural features. In addition, 10 quantitative structure-activity relationship (QSAR) models were constructed by four machine learning methods based on 813 inhibitors. Model 6 J, the best QSAR model, was developed by fully connected neural networks with 50 RDKit descriptors. It resulted in a coefficient of determination (r ²) of 0.770 and a root mean squared error (RMSE) of 0.482 on the test set. The AD of Model 6 J was visualized by Williams plot. The models built in this study can be obtained from the authors.

2H/4H-Chromenes-A Versatile Biologically Attractive Scaffold

2H/4H-chromene (2H/4H-ch) is an important class of heterocyclic compounds with versatile biological profiles, a simple structure, and mild adverse effects. Researchers discovered several routes for the synthesis of a variety of 2H/4H-ch analogs that exhibited unusual activities by multiple mechanisms. The direct assessment of activities with the parent 2H/4H-ch derivative enables an orderly analysis of the structure-activity relationship (SAR) among the series. Additionally, 2H/4H-ch have numerous exciting biological activities, such as anticancer, anticonvulsant, antimicrobial, anticholinesterase, antituberculosis, and antidiabetic activities. This review is consequently an endeavor to highlight the diverse synthetic strategies, synthetic mechanism, various biological profiles, and SARs regarding the bioactive heterocycle, 2H/4H-ch. The presented scaffold work compiled in this article will be helpful to the scientific community for designing and developing potent leads of 2H/4H-ch analogs for their promising biological activities.

Structural basis of quinolone derivatives, inhibition of type I and II topoisomerases and inquiry into the relevance of bioactivity in odd or even branches with molecular docking study

The structural modification of quinolone derivatives has been a hot spot in recent years, especially the modification of the N-1 position, which is the part that this article focuses on. In this paper, series of synthesized quinoline quaternary ammonium salts with odd and even carbon number alkyl groups in N-1 position were used to explain the influence of the alkyl side chain on activity. With respect to all the recently synthesized twenty products, the biological activity results exhibited significant antitumor and antibacterial activity with obvious differences in the target alkyliodine substituted compounds and the antibacterial activities apparently had the prominent odd-carbon number predominance. Compound 8-((4-(benzyloxy)phenyl)amino)-7-(ethoxycarbonyl)-5-propyl-[1,3]dioxolo[4,5-g]quinolin-5-ium (4d) was found to be the most potent derivative with IC₅₀ values of 4 ± 0.88, 4 ± 0.42, 14±1.96, and 32±3.66 against A-549, Hela, SGC-7901, and L-02 cells, respectively, stronger than the positive control 5-FU and MTX. Furthermore, it had the most potent bacterial inhibitory activity of MIC value against E. coli (ATCC 29213) and Staphylococcus aureus (ATCC 8739) at 3.125 nmol mL⁻¹. With respect to molecular simulations, in order to illustrate the possible mechanism of the difference between the series of compounds in the even or odd carbon chain alkyliodine substitution, this paper simulated the conceivable mode and explained the main interactions. Finally, we could find that the position and proportion of hydrogen bonds and other interactions in each series were regarded as the main reasons for this difference in activity.