BACE1 Inhibition Utilizing Organic Compounds Holds Promise as a Potential Treatment for Alzheimer's and Parkinson's Diseases.

Background: Neurological disorders like Alzheimer's disease (AD) and Parkinson's disease (PD) manifest through gradually deteriorating cognitive functions. An encouraging strategy for addressing these disorders involves the inhibition of precursor-cleaving enzyme 1 (BACE1). Objectives: In the current research, a virtual screening technique was employed to identify potential BACE1 inhibitors among selected herbal isolates. Methods: This study evaluated 79 flavonoids, anthraquinones (AQs), and cinnamic acid derivatives for their potential blood-brain barrier (BBB) permeability. Using the AutoDock 4.0 tool, molecular docking analysis was conducted to determine the binding affinity of BBB permeable compounds to the BACE1 active site. Molecular dynamics (MD) simulations were performed to assess the stability of the docked poses of the most potent inhibitors. The interactions between the most effective plant-based inhibitors and the residues within the BACE1 catalytic site were examined before and after MD simulations. Results: Ponciretin, danthron, chrysophanol, and N-p-coumaroyltyramine were among the highest-ranking BACE1 inhibitors, with inhibition constant values calculated in the nanomolar range. Furthermore, during 10 ns simulations, the docked poses of these ligands were observed to be stable. Conclusion: The findings propose that ponciretin, danthron, chrysophanol, and N-p-coumaroyltyramine might serve as potential choices for the treatment of AD and PD, laying the groundwork for the creation of innovative BACE1 inhibitors.

Different Gene Expression Patterns of IL-1 Family Members in Parkinson's Disease: Results from Bayesian Regression Model.

Parkinson's disease, the second most prevalent neurodegenerative disorder lacking a recognized etiology, is influenced by oxidative stress and alterations in inflammatory cytokine levels. This study aimed to investigate the expression levels of Interleukin(IL)1 receptor accessory protein (IL-1RAcP), IL1ß, IL1α, IL33, and IL36 genes in blood cells and serum IL-1ß levels in Parkinson's disease patients compared to healthy controls (HCs).I n this case-control study, 44 Parkinson's disease patients and 44 age- and sex-matched HCs were included. Gene expression levels were assessed using Quantitative Real-time PCR, and serum IL-1ß levels were measured via enzyme-linked immunosorbent assay. Advanced statistical analyses using the Bayesian regression model in R software were employed. Parkinson's disease patients exhibited elevated expression levels of IL-1RAcP and IL1ß genes  but decreased levels of IL1α, IL33, and IL36 compared to HCs. Age-based differences were not significant. Regarding gender, IL33 transcript levels were significantly higher in males, and serum IL-1ß levels were increased in patients. Subgroup analysis by gender indicated alterations in IL1ß and IL-1RAcP expression in both genders, while IL1α, IL33, and IL36 showed reduced expression only in males. Remarkably, only female patients displayed significantly higher serum IL-1ß levels than female HCs. These findings suggest that dysregulation of immune-related factors plays a crucial role in Parkinson's disease.

Role of microbiota short-chain fatty acids in the pathogenesis of autoimmune diseases.

There is emerging evidence that microbiota and its metabolites play an important role in helath and diseases. In this regard, gut microbiota has been found as a crucial component that influences immune responses as well as immune-related disorders such as autoimmune diseases. Gut bacterial dysbiosis has been shown to cause disease and altered microbiota metabolite synthesis, leading to immunological and metabolic dysregulation. Of note, microbiota in the gut produce short-chain fatty acids (SCFAs) such as acetate, butyrate, and propionate, and remodeling in these microbiota metabolites has been linked to the pathophysiology of a number of autoimmune disorders such as type 1 diabetes, multiple sclerosis, inflammatory bowel disease, rheumatoid arthritis, celiac disease, and systemic lupus erythematosus. In this review, we will address the most recent findings from the most noteworthy studies investigating the impact of microbiota SCFAs on various autoimmune diseases.

Cinnamic acid derivatives as potential matrix metalloproteinase-9 inhibitors: molecular docking and dynamics simulations.

Matrix metalloproteinase-9 (MMP-9) is a zinc and calcium-dependent proteolytic enzyme involved in extracellular matrix degradation. Overexpression of MMP-9 has been confirmed in several disorders, including cancers, Alzheimer's disease, autoimmune diseases, cardiovascular diseases, and dental caries. Therefore, MMP-9 inhibition is recommended as a therapeutic strategy for combating various diseases. Cinnamic acid derivatives have shown therapeutic effects in different cancers, Alzheimer's disease, cardiovascular diseases, and dental caries. A computational drug discovery approach was performed to evaluate the binding affinity of selected cinnamic acid derivatives to the MMP-9 active site. The stability of docked poses for top-ranked compounds was also examined. Twelve herbal cinnamic acid derivatives were tested for possible MMP-9 inhibition using the AutoDock 4.0 tool. The stability of the docked poses for the most potent MMP-9 inhibitors was assessed by molecular dynamics (MD) in 10 nanosecond simulations. Interactions between the best MMP-9 inhibitors in this study and residues incorporated in the MMP-9 active site were studied before and after MD simulations. Cynarin, chlorogenic acid, and rosmarinic acid revealed a considerable binding affinity to the MMP-9 catalytic domain (ΔGbinding < -10 kcal/ mol). The inhibition constant value for cynarin and chlorogenic acid were calculated at the picomolar scale and assigned as the most potent MMP-9 inhibitor from the cinnamic acid derivatives. The root-mean-square deviations for cynarin and chlorogenic acid were below 2 Å in the 10 ns simulation. Cynarin, chlorogenic acid, and rosmarinic acid might be considered drug candidates for MMP-9 inhibition.

An inclusive study on cytokine gene expression in Parkinson's disease: Advanced analysis using Bayesian regression model.

BACKGROUND: Parkinson's disease (PD) is the second most prevalent neurodegenerative disease throughout the globe whose specific pathophysiology is unknown. Researchers believe that inflammation and oxidative stress contribute to PD development. Also, alterations in cytokines production appear to have a key role in the pathogenesis of PD. The aim of the current study was to evaluate gene expression levels of nine cytokines in the peripheral blood of PD patients compared to a healthy control group. METHODS: Real-time PCR was used to analyze cytokines gene expression followed by advanced statistical analysis performed using Bayesian regression model in R (version 4.1.0) statistical software. RESULTS: TNF-α, IL-1ß, IL-2, IL-4, IFN-γ, IL-17 and IL-6 transcript levels were upregulated in patients compared to healthy controls. However, CXCL8 expression was downregulated in patients compared to controls and IFN-ß expression was not statistically different between the two groups. While we found no significant difference between the groups based on gender and age regarding TNF-α, IL-1ß, CXCL8, IL-2, IL-4, IFN-γ and IFN-ß gene expression, IL-6 and IL-17 transcript levels showed significant upregulations in older subjects and in females, respectively. In addition, we found that the interaction effects between gender and group on gene expression levels were not significant. In this way, the subgroup analysis within gender revealed that in each gender, expression levels of TNF-α, IL-2, IL-4, IL-6, IFN-γ and IL-17 were significantly higher in patients than controls. However, IFN-ß expression level did not show any significant difference between groups and subgroups. CONCLUSION: The present study provides evidence on significant alterations in cytokine expression with different patterns and points to immune system dysregulation in PD.

Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson's Diseases and Improving the Disease Classification Using Support Vector Machine.

Background: Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the main cause of this disease. The purpose of this research was to discover genes involved in PD development. Methods: In this study, the microarray dataset (GSE22491) provided by GEO was used for further analysis. The Limma package under R software was used to examine and assess gene expression and identify DEGs. The DAVID online tool was used to accomplish GO enrichment analysis and KEGG pathway for DEGs. Furthermore, the PPI network of these DEGs was depicted using the STRING database and analyzed through the Cytoscape to identify hub genes. Support vector machine (SVM) classifier was subsequently employed to predict the accuracy of genes. Result: PPI network consisted of 264 nodes as well as 502 edges was generated using the DEGs recognized from the Limma package under the R software. Moreover, three genes were identified as hubs: GNB5, GNG11, and ELANE. By using 3-gene combination, SVM found that prediction accuracy of 88% can be achieved. Conclusion: According to the findings of the study, the 3 hub genes GNB5, GNG11, and ELANE may be used as PD detection biomarkers. Moreover, the results obtained from SVM with high accuracy can be considered as PD biomarkers in further investigations.