Current medicinal chemistry最新文献

Mangosteens, a prominent component of Garcinia mangostana, have been ex-tensively studied for their biological activities and structural modifications. Chemical methods, including cyclization reactions under acidic conditions, have yielded many de-rivatives, which often exhibit enhanced pharmacological properties compared to itself. Enzymatic biotransformation, such as glycosylation and oxidation mediated by fungal species and enzymes like horseradish peroxidase, have provided regioselective pathways to functionalized mangostin derivatives. These studies highlight the versatility of mangos-tin as a scaffold for designing compounds with tailored biological functions. Overall, mangosteen represents a promising platform for developing compounds with enhanced pharmacological activities, paving the way for innovative approaches in biomedicine and pharmaceutical sciences. This review provides a comprehensive examination of the chem-istry of mangosteens, detailing their total synthesis and the derivatives obtained through both chemical and enzymatic methodologies.

Introduction: Diabetic Retinopathy (DR) is a common microvascular issue caused by diabetes. Idebenone (IDE) is a coenzyme Q10 analog and antioxidant that has been utilized in the treatment of neurodegenerative diseases.

Method: Our goal was to investigate how IDE might treat diabetic retinopathy. An in vivo DR model was established by injecting a single dose of streptozotocin (STZ). Rats were treated with IDE, and their vascular function was measured by ultrasound. The retina structure was checked by haematoxylin and eosin (HE) staining. The expression of biomarkers of autophagy and apoptosis was measured by western blotting assay. The retina endothelial cell line RF/6A was stimulated with high glucose (HG) and treated with IDE. Cell proliferation and apoptosis were assessed using the Edu assay, TUNEL assay, and flow cytometry, respectively.

Result: Reduced peak systolic velocity (PSV), mean velocity (MV), end-diastolic velocity (EDV), and increased pulsatility index (PI) and resistance index (RI) were observed in diabetic rats; however, these traits were reversed by IDE therapy. IDE alleviated the STZ-induced disordered retina structure. The IDE administration suppressed DR-induced apoptosis and autophagy both in vivo and in vitro. IDE suppressed the activation of Phosphatidylinositol 3 kinase (PI3K) signaling. Activation of PI3K abolished the IDE-alleviated retina damage and cell death.

Conclusion: IDE regulated the autophagy of retina cells to alleviate diabetic retinopathy via regulating the PI3K signaling pathway.

Background: Astragalus membranaceus has shown positive clinical efficacy in treating colorectal cancer (CRC).

Objective: This study aimed to identify the key active components of Astragalus and determine effective targets of these components in CRC patients.

Methods: We identified active components of Astragalus membranaceus and differentially expressed genes in traditional Chinese medicine systems pharmacology database and The Cancer Genome Atlas. Additionally, the enrichment analysis of differential target genes (DTGs) was performed using the R-package clusterProfiler. Immunocyte correlation analysis and non-coding regulatory network construction were performed for biomarkers using Spearman's method and NetworkAnalyst. Finally, molecular docking of biomarkers and their corresponding molecule drugs was done with Autodock Vina software.

Results: We identified 20 active components of Astragalus membranaceus and 1 403 target genes through screening. A total of 2 300 differentially expressed genes, and 3 035 hub genes in CRC were screened. The integration of the target genes with the significantly differentially expressed genes and Hub genes identified resulted in a total of 86 DTGs. Subsequently, the results showed 828 enriched GO biological processes, 184 enriched GO molecular functions, 59 enriched GO cellular components, and 46 enriched KEGG pathways. We also obtained a total of 143 PPI pairs involving 67 nodes. Additionally, we constructed 45 mRNA-TF pairs, 101 miRNA-mRNA pairs, and 200 miRNA- mRNA-TF triplets. Finally, molecular docking was performed for the active component quercetin with F2 and UGT1A1 and formic acid with FGA, AHSG, and KNG1.

Conclusion: This study identified the active components of Astragalus membranaceus and their corresponding targets in CRC. These findings provide robust evidence for precision drug therapy in patients with CRC.

Background: The role of LNX1 antisense RNA 2 (LNX1-AS2) in lung adenocarcinoma (LUAD) remains unclear.

Objective: This study aimed to investigate the association between LNX1-AS2 and LUAD by employing bioinformatics analysis and experimental validation.

Methods: Statistical analysis and database interrogation were utilized to assess correlations among LNX1-AS2 expression, clinical characteristics of LUAD patients, prognostic factors, regulatory networks, and immune infiltration. LNX1-AS2 expression in LUAD cell lines was quantified using quantitative real-time polymerase chain reaction (qRT-PCR).

Results: The study found significantly elevated levels of LNX1-AS2 expression in patients with LUAD. Furthermore, elevated LNX1-AS2 expression in LUAD patients did not significantly correlate with gender (p = 0.041) or race (p = 0.049). Importantly, high LNX1-AS2 expression levels were associated with poorer overall survival (OS, p = 0.042) and disease-specific survival (DSS, p = 0.040) in LUAD patients. Additionally, high LNX1-AS2 expression (p = 0.015) was independently correlated with OS in LUAD patients. The phenotype characterized by high LNX1-AS2 expression was also found to be enriched for asthma, allograft rejection, drug metabolism cytochrome P450, metabolism of xenobiotics by cytochrome P450, olfactory transduction, renin-angiotensin system, retinol metabolism, pentose and glucuronate interconversions, and porphyrin and chlorophyll metabolism. A significant correlation was identified between the expression levels of LNX1-AS2 and immune infiltration in the context of LUAD. Elevated expression of LNX1-AS2 was notably detected in LUAD cell lines as opposed to Beas-2B.

Conclusion: A noteworthy relationship was established among increased LNX1-AS2 expression in LUAD patients, unfavorable prognosis, and heightened immune infiltration. These findings suggest that the LNX1-AS2 gene could serve as a valuable prognostic indicator for LUAD and a potential predictor of response to immunotherapy.

Introduction: Triple-Negative Breast Cancer (TNBC) is the most common type of breast cancer (BC). In order to develop effective treatments for TNBC, it is vital to identify potential therapeutic targets. Angiogenesis stimulates tumor growth and metastasis in TNBC, and miR-155 plays a crucial role in this process. The exosome is a nano-sized vesicle that carries many cargoes, including miRNAs. The present study investigated the effect of exosomal delivery of miR-155 antagomir on tumor migration, invasion, and angiogenesis in TNBC.

Materials and methods: From MDA-MB-231 cells, exosomes were extracted, characterized, and loaded with miR-155 antagomir using electroporation. The expression of miR-155 and its target genes, including PTEN and DUSP14, was analyzed using RTqPCR. The wound-healing and transwell assays were used to measure cell migration and invasion. Furthermore, angiogenesis was evaluated by tube formation and chorioallantoic membrane (CAM) assays.

Results: The results indicated that exosomal delivery of miR-155 antagomir to HUVEC cells significantly suppressed miR-155 expression while upregulating PTEN and DUSP14. The tube formation properties of HUVEC cells were also significantly reduced following treatment with exosomes containing miR-155 antagomirs, and these results were confirmed using CAM assay. The migration and invasion of MDA-MB-231 cells were significantly reduced after treatment with miR-155 antagomir-loaded exosomes.

Conclusion: It was found that miR-155 antagomir delivery using exosomes can inhibit migration, invasion, and angiogenesis viaPTEN and DUSP14 in TNBC.

SARS-CoV-2-induced COVID-19 has been a serious public health problem, resulting in millions of lives lost over the previous three years. Although the direct infection caused by virus invasion is important for the pathobiology of COVID-19, the hyperinflammatory response and tissue injury are major contributors in critically ill patients. As a host sensor, toll-like receptor 2 (TLR2) recognizes multiple pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMPs), producing various inflammatory cytokines and inflammatory cell death signals, which are central to the inflammatory pathology observed in COVID-19. The objectives of this narrative review are to summarize the role of TLR2 activation during SARS-CoV-2 infection and emphasize the importance of SARS-CoV-2 viral proteins in TLR2 activation. Additionally, we presented some compounds related to TLR2 regulation clinically or experimentally, which may provide new insights into targets for pharmaceutical discovery and development.

Background: Parkinson's disease (PD) is a multifaceted disease that is influenced by both genetic and environmental parameters. Non-coding RNAs have been shown to be ideal biomarkers for several diseases, including PD. This study was conducted to evaluate the expression levels of NEAT1, hsa-let-7a-5p, and miR-506-3p in individuals with PD to assess their efficacy for early-stage PD diagnosis.

Methods: Twenty-four patients with PD and 29 healthy individuals participated in this study. The IntaRNA tool was used to predict potential base pairings between NEAT1 and let-7a-5p, and NEAT1 and miR-506-3p. RT-qPCR was employed to measure the relative expression of tyrosine hydroxylase (TH), as well as nuclear enriched abundant transcript 1 (NEAT1), hsa-let-7a-5p, and miR-506-3p levels in both groups. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic value.

Results: The PD group exhibited significantly elevated NEAT1 expression levels compared to the healthy control group. While the PD group exhibited an insignificant decreased TH expression level relative to the healthy group. Furthermore, the levels of hsa-let-7a-5p and miR-506-3p expression were seen to be decreased in patients with PD in comparison to the control group. Integration of NEAT1, hsa-let-7a-5p, and miR-506-3p levels significantly enhanced diagnostic capabilities and increased the AUC to 0.9501 (95% confidence interval: 0.8978-1.000, p < .0001).

Conclusions: The elevated NEAT1 expression and the decreased expression of hsalet- 7a-5p and miR-506-3p in PD patients indicate that these factors might contribute to the disease's pathogenesis. Combining the ROC curves of NEAT1 and hsa-let-7a-5p with miR-506-3p showed improved sensitivity and specificity, facilitating more accurate PD diagnosis. More importantly, they may contribute as promising non-invasive biomarkers for PD diagnosis.

Diabetic kidney disease is a devastating diabetic complication, affecting up to half of people suffering from diabetes. The global burden of diabetic kidney disease is steadily increasing worldwide along with the growing prevalence of type 2 diabetes. The epidemic rise of type 2 diabetes is primarily observed in Asia, including the East Asian regions. It is generally accepted that heredity is one of the main determinants in the pathogenesis of diabetic kidney disease. Since the advent of genome-wide association studies, numerous studies have been published to identify the genetic loci susceptible to diabetic kidney disease among diverse populations. Although genome-wide association studies exploring diabetic kidney disease susceptibility loci have focused primarily on populations of European descent, a number of novel genetic variants associated with diabetic kidney disease have also been successfully revealed among East Asians. A comprehensive analysis of the genetic architecture and pathophysiological pathways of diabetic kidney disease may allow the identification of new potential therapeutic targets. This review aimed to summarize genome-wide association studies examining genetic variants associated with diabetic kidney disease in the populations of East Asian ancestry with type 2 diabetes and presented our perspective on the future of this field.

Structure-based drug discovery methods, such as molecular docking and virtual screening, have become invaluable tools in developing novel drugs. At the core of these methods are Scoring Functions (SFs), which predict the binding affinity between ligands and protein targets. This study aims to review and contextualize the challenges and best practices in training novel scoring functions to improve their accuracy and generalizability in predicting protein-ligand binding affinities. Effective training of scoring functions requires careful attention to the quality of training data and methodologies. We emphasize the need for robust training strategies to produce consistent and generalizable SFs. Key considerations include addressing hidden biases and overfitting in machine-learning models, as well as ensuring the use of high-quality, unbiased datasets for both training and evaluation of SFs. Innovative hybrid methods, combining the advantages of empirical and machine-learning approaches, hold promise for outperforming current scoring functions while displaying greater generalizability and versatility.