Current Medicinal Chemistry - Volume 32, Issue 29, 2025

Alzheimer's disease (AD) is the most common neurodegenerative disease in older people, characterized by the accumulation of beta-amyloid (Aβ) plaques and neurofibrillary tangles composed of aggregated of hyperphosphorylated tau protein, which normally helps stabilize microtubules in neurons.

Nowadays, artemisinin (ART) as well as its semisynthetic derivatives (ARTs) are seen as potential neuroprotectors. The goal of the present study is the assessment of neuroprotective, antibacterial activity of ART, as well as in silico studies of ART affinity to Aβ-peptides and the search of potential targets for ART. The study is referring to explores the impact of ART on an animal model of AD that is induced by the aggregated amyloidogenic peptide Aβ1-42 by electrophysiology and morphology analysis. Specifically, the focus is on the activation of the entorhinal cortex (ENT) as synaptic potentiation.

Electrophysiological and histochemical have demonstrated that therapeutic injection of ART or its derivatives acts as a neuroprotective This treatment appears to prevent or slow down damage to brain tissue, and it promotes the restoration of neurons and their surrounding environment. The protective effects of ART may involve various mechanisms, including antioxidant activity, anti-inflammatory effects, and the inhibition of apoptosis.

In silico studies revealed a direct, strong interaction of ART with the amyloidogenic peptides 5Aβ17-42, 12Aβ9-40, and 18Aβ9-40. In silico screening revealed several protein targets for ART, including cytochrome P-450 2B6 (CYP2B6). The highest binding affinity was found on the active site of CYP2B6. ART has great potential for discovering new drugs using combined therapies.

Fustin, a photogenic flavanol found in the plant Rhus verniciflua Stokes, has been involved in multiple disease ailments and has a beneficial pharmacological effect and a history of use in traditional medicine. The present research aimed to study the impact of fustin on scopolamine (SCOP)-induced memory impairment and neurodegeneration by modulating neuroinflammation and neurotransmitters in rats.

A total of 30 healthy wistar rats were allocated into five groups (n=6). Group I- served as control and received saline solution (1mL/kg i.p.), group -II- fustin (100 mg/kg, orally), group -III -SCOP (1 mg/kg, i.p.), and group -IV and V were given fustin (50 and 100 mg/kg/p.o.) with SCOP (1 mg/kg, i.p.) for 14-days. After 14 days, 2 hours after SCOP injection, the Y-maze and Morris water maze (MWM) tests were performed. After behavioral tests rats were subsequently euthanized, and brain supernatants were used to estimate choline-acetyltransferase (ChAT), acetylcholinesterase (AChE), antioxidant enzymes [superoxide dismutase (SOD), catalase (CAT), and glutathione (GSH)], and total protein, oxidative stress markers [nitrate and malondialdehyde (MDA)], pro-inflammatory markers [tumor necrosis factor (TNF-α), and Interleukins-1β (IL-1β) and IL-6]. Also, neurotransmitters such as serotonin (5-HT), dopamine (DA), ϒ-amino butyric acid (GABA), acetylcholine (Ach), and noradrenaline (NA) contents were performed.

Fustin exhibited substantial behavioral improvement in the Y-maze measures spontaneous alterations percentage (SA%) and decreased latency time following the acquisition and prolonged time spent in the probe trial in the MWM test. Moreover, fustin inhibits enhanced neuroinflammatory cytokines and oxidative stress markers and improves the neurotransmitters.

The findings of this study suggest that fustin inhibits SCOP impact on cognitive abilities in rats. The present investigation demonstrates that fustin, a potent phytochemical, effectively mitigated the behavioral and physiological changes induced by SCOP in rats. This was primarily achieved by modulating the levels of inflammatory response and neurotransmitters.

The inflammation phenotypes are often closely related to oxidative stress and autophagy pathway activation, which could be developed as a treatment target.

The aim of this study was to explore the underlying mechanism of inflammation in chronic obstructive pulmonary disease (COPD).

The lung tissue single-cell RNA-seq (scRNA-seq) dataset of GSE171541 was downloaded from the Gene Expression Omnibus (GEO) database. The marker genes were obtained from the CellMarker database. “Seurat” and “harmony” R packages were used for single-cell profiling analysis. Then, the “AUCell” R package was employed to calculate the reactive oxygen species (ROS) and autophagy pathway scores. Gene regulation network analysis was performed by applying the “SCENIC” package, followed by conducting correlation analysis with Spearman’s rank correlation method. The cigarettes were used to develop a COPD model in mice, and the expression of relevant genes was measured by qRT-PCR.

The scRNA-seq analysis classified 12 cell subgroups in which the contractility of myofibroblasts was closely associated with the progression of COPD. Further analysis showed that ROS and autophagy pathways were significantly activated in myofibroblasts and that the nuclear factor erythroid 2-related factor 2 (NRF2) and its mediated oxidative stress pathway were inhibited in myofibroblasts. In addition, the downregulated NRF2 gene was negatively correlated with the expression of autophagy and ROS activation. In the COPD mice model, NRF2 was downregulated in COPD mice but further elevated in the COPD+NRF2 mice group. Interestingly, the mRNA levels of Kelch- like ECH-associated protein 1 (Keap1), NADPH oxidase (NOX), and Cathepsin B (CTSB) were upregulated in COPD group in comparison to the control group but they were downregulated by NRF2. These results suggested that low-expressed NFR2 promoted autophagy and ROS pathway activation in myofibroblasts for COPD progression.

We identified a cell myofibroblast cluster closely associated with COPD progression using the scRNA-seq analysis. The downregulated NFR2, as a key risk factor, mediated myofibroblast death by activating the oxidative stress and autophagy pathway for COPD progression.

Due to the high heterogeneity of lung adenocarcinoma (LUAD), which restricts the effectiveness of therapy, precise molecular subgrouping of LUAD is of great significance. Clinical research has demonstrated the significant potential of DNA methylation as a classification indicator for human malignancies.

WGML framework (which was developed based on weighted gene correlation network analysis (WGCNA), Gene Ontology (GO), and machine learning) was developed to precisely subgroup molecular subtypes of LUAD. This framework included two parts: the WG algorithm and the machine learning part. The WG algorithm part was an original algorithm used to obtain a crucial module, which was characterized by weighted correlation network analysis, functional annotation, and mathematical algorithms. The machine learning part utilized the Boruta algorithm, random forest algorithm, and Gradient Boosting Regression Tree algorithm to select feature genes. Then, based on the results of the WGML framework, subtypes were computed by the hierarchical clustering algorithm. A series of analyses, including dimensionality reduction methods, survival analysis, clinical stage analysis, immune infiltration analysis, tumor environment analysis, immune checkpoints analysis, TIDE analysis, CYT analysis, somatic mutation analysis, and drug sensitivity analysis, were utilized to demonstrate the effectiveness of subgrouping. GEO datasets were used to externally validate the results. Meanwhile, another subgrouping method of LUAD from another study was employed to compare with the WGML framework.

By importing DNA methylation data into the WGML framework, nine genes were obtained to further subgroup LUAD. Three subtypes, the Carcinogenesis subtype, Immune-infiltration subtype, and Chemoresistance subtype, were identified. The dimensionality reduction method exhibited great distinctness between subtypes. A series of analyses were employed to exhibit the difference among the three subtypes and to demonstrate the accuracy of the definition of subtypes. Besides, the WGML framework was compared with a LUAD subgrouping method from another research, which demonstrated that WGML had better efficiency for subgrouping LUAD.

This study provides a novel LUAD subgrouping framework named WGML for the accurate subgrouping of lung adenocarcinoma.

In our quest to identify potent inhibitors against SARS-CoV-2, an extensive investigation was conducted for the binding and inhibitory efficacy of Rutin against nine SARS-CoV-2 proteins.

Structure Similarity, flexible alignment, Molecular Docking, molecular dynamics (MD) simulations and in vitro assays against the RdRp and SARS-CoV-2 have been conducted.

The first step of our analysis involved a comprehensive examination of structural similarity among the co-crystallized ligands associated with those proteins. A substantial structural similarity was observed between Rutin and Remdesivir, the ligand of the SARS-CoV-2 RNAdependent RNA polymerase (RdRp). This similarity was validated through a flexible alignment study. Molecular docking studies, involving superimposition, revealed a notable resemblance in the mode of binding between Rutin and Remdesivir inside the active site of the RdRp. A 200 ns MD simulation confirmed that the RdRp-Rutin complex is more stable than the RdRp-Remdesivir complex. The MM-GBSA studies showed that Rutin had much more favorable binding energies, with a significantly lower value of -7.76 kcal/mol compared to Remdesivir's -2.15 kcal/mol. This indicates that the RdRp-Rutin binding is more robust and stable. PLIP and ProLIF studies helped clarify the 3D binding interactions and confirmed the stable binding seen in MD simulations. PCAT gave more insights into the dynamic behavior of the RdRp-Rutin complex. In vitro tests showed that Rutin has a strong inhibitory effect on RdRp with an IC50 of 60.09 nM, significantly outperforming Remdesivir, which has an IC50 of 24.56 μM. Remarkably, against SARS-CoV-2, Rutin showed a superior in vitro IC50 of 0.598 μg/ml compared to Remdesivir (12.47 μg/ml). The values of the selectivity index underscored the exceptional margin of safety of Rutin (SI: 1078) compared to Remdesivir (SI: 5.8).

In conclusion, our comprehensive analysis indicates Rutin’s promising potential as a potent SARS-CoV-2 RdRp inhibitor, providing a valuable insight for developing an effective COVID-19 treatment.

microRNAs (miRNAs) are a class of non-coding RNAs that play important roles in gene regulation. miRNAs are transcribed from DNA sequences into primary miRNAs and then processed into precursor miRNAs and mature miRNAs. miRNA gene counts in chromosomes for different species have been studied.

Certain chromosomes have higher numbers of miRNA genes in all species, such as the X chromosome, while the Y chromosome has the fewest or no miRNA genes. miRNA counts in different chromosomes might have a positive correlation with coding gene counts in many species. In this study, a regression model was used to find the relationship between the miRNA count and the coding gene count across human chromosomes, and miRNA counts for 23 human chromosomes were predicted based on this regression model. In addition, the chromosome locations for the miRNA biomarkers of major depression, diabetes, Parkinson’s disease, and COVID-19 are discussed.

The results reveal that miRNA biomarkers of these diseases are located in various chromosomes. The dispersion of miRNA locations across different chromosomes might explain the complication of the pathology of these diseases. Moreover, diabetes and COVID-19 have the largest number of miRNA biomarkers from Chromosome X.

As Chromosome X is a sex chromosome, this phenomenon may explain the gender difference in the prevalence or severity of diabetes and COVID-19. The significant gender difference in the prevalence or severity of diabetes and COVID-19 might be due to the regulation function of their miRNA biomarkers from Chromosome X.

This study aimed to explore the potential causal relationship between dietary habits and Gastroesophageal Reflux Disease (GERD).

Using the inverse-variance weighted method, a two-sample Mendelian randomization (MR) analysis was performed to investigate the causal relationship between 22 dietary habits and GERD. The stability and reliability of the results were assessed using leave-one-out analysis, heterogeneity tests, and tests for horizontal pleiotropy based on the effect measure odds ratio (OR) and 95% confidence interval (CI).

The results of the MR analysis indicated a positive association between alcohol drinking (OR=1.472; 95% CI, 1.331 to 1.629; p<1.0×10^-3) and salt added to food (OR=1.270; 95% CI, 1.117 to 1.443; p<1.0×10^-3) with the risk of GERD. Conversely, bread intake (OR=0.613; 95% CI, 0.477 to 0.790; p<1.0×10^-3), cereal intake (OR=0.613; 95% CI, 0.391 to 0.677; p<1.0×10^-3), cheese intake (OR=0.709; 95% CI, 0.593 to 0.846; p<1.0×10^-3), dried fruit intake (OR=0.535; 95% CI, 0.404 to 0.709; p<1.0×10^-3), fresh fruit intake (OR=0.415; 95% CI, 0.278 to 0.619; p<1.0×10^-3), and oily fish intake (OR=0.746; 95% CI, 0.633 to 0.879; p<1.0×10^-3) were negatively associated with the risk of GERD. Sensitivity analysis showed no evidence of reverse causation, pleiotropy, or heterogeneity.

Alcohol and salt added to food raised GERD risk, while bread intake, cereal intake, cheese intake, intake of certain dried fruits and certain fresh fruits, and oily fish lowered it. Our study affirms the potential causal link between these diets and GERD, offering insights into targeted prevention strategies.