Computational Systems Pharmacology, Molecular Docking and Experiments Reveal the Protective Mechanism of Li-Da-Qian Mixture in the Treatment of Glomerulonephritis

Luteolin: A promising multifunctional natural flavonoid for human diseases

Natural products are closely associated with human health. Luteolin (LUT), a flavonoid polyphenolic compound, is widely found in fruits, vegetables, flowers, and herbs. It is noteworthy that LUT exhibits a variety of beneficial pharmacological properties and holds significant potential for clinical applications, particularly in antitumor, anti-convulsion, diabetes control, anti-inflammatory, neuroprotection, anti-oxidation, anti-cardiovascular, and other aspects. The potential mechanism of action has been partially elucidated, including the mediation of NF-κB, toll-like receptor, MAPK, Wnt/β-catenin, PI3K/Akt, AMPK/mTOR, and Nrf-2, among others. The review that aimed to comprehensively consolidate essential information on natural sources, pharmacological effects, therapeutic and preventive potential, as well as potential mechanisms of LUT. The objective is to establish a theoretical basis for the continued development and application of LUT.

Dynamic changes in marker components during the stir-frying of Pharbitidis Semen, and network analysis of its potential effects on nephritis

Introduction: Pharbitidis Semen (PS) has been widely used in traditional Chinese medicine to treat several diseases such as nephritis. PS is usually stir-fried to enhance its therapeutic efficacy before use in clinical practice. However, the changes in phenolic acids during stir-frying and the mechanisms of their therapeutic effects on nephritis are still unclear.

Methods: Here, we studied the processing-induced chemical changes and elucidated the mechanism of PS in the treatment of nephritis. We determined the levels of the 7 phenolic acids in raw PS (RPS) and stir-fried PS (SPS) using high-performance liquid chromatography, analyzed the dynamic compositional changes during stir-frying, and used network analysis and molecular docking to predict and verify compound targets and pathways corresponding to nephritis.

Results: The dynamic changes in the 7 phenolic acids in PS during stir-frying are suggestive of a transesterification reaction. Pathway analysis revealed that the targets of nephritis were mainly enriched in the AGE-RAGE, hypoxia-inducible factor-1, interleukin-17, and tumor necrosis factor signaling pathways among others. Molecular docking results showed that the 7 phenolic acids had good binding ability with the key nephritic targets.

Discussion: The potential pharmaceutical basis, targets, and mechanisms of PS in treating nephritis were explored. Our findings provide a scientific basis for the clinical use of PS in treating nephritis.

Network pharmacology analysis and experimental verification reveal the mechanism of the traditional Chinese medicine YU-Pingfeng San alleviating allergic rhinitis inflammatory responses

YU-Pingfeng San (YPFS) can regulate inflammatory response to alleviate the symptoms of nasal congestion and runny rose in allergic rhinitis (AR). However, the mechanism of action remains unclear. In this study, 30 active ingredients of three effective herbs included in YPFS and 140 AR/YPFS-related genes were identified by database analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the targets were mainly enriched in immune inflammatory-related biological processes and pathways. Finally, three hub gene targeting epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), and protein kinase B1 (AKT1) related to YPFS and AR were identified by network pharmacology analysis. YPFS treatment decreased the expression of EGFR, MAPK1, and AKT1 in ovalbumin (OVA)-induced AR mice and impaired the production of inflammatory factors interleukin (IL)-4, IL-5, and IL-13, thus alleviating immunoglobulin E (IgE) production and the symptoms of scratching nose in AR. Through molecular docking analysis, we found that the active ingredients decursin, anomalin, and wogonin of YPFS could bind to EGFR, MAPK1, and AKT1 proteins. Moreover, decursin treatment impaired the expression of IL-4 and IL-5 in human PBMCs. These results suggested that YPFS could alleviate the AR inflammatory responses by targeting EGFR, MAPK1, and AKT1, showing the mechanism of action of YPFS in AR treatment.

Gene Identification and Potential Drug Therapy for Drug-Resistant Melanoma with Bioinformatics and Deep Learning Technology

Background. Melanomas are skin malignant tumors that arise from melanocytes which are primarily treated with surgery, chemotherapy, targeted therapy, immunotherapy, radiation therapy, etc. Targeted therapy is a promising approach to treating advanced melanomas, but resistance always occurs. This study is aimed at identifying the potential target genes and candidate drugs for drug-resistant melanoma effectively with computational methods. Methods. Identification of genes associated with drug-resistant melanomas was conducted using the text mining tool pubmed2ensembl. Further gene screening was carried out by GO and KEGG pathway enrichment analyses. The PPI network was constructed using STRING database and Cytoscape. GEPIA was used to perform the survival analysis and conduct the Kaplan-Meier curve. Drugs targeted at these genes were selected in Pharmaprojects. The binding affinity scores of drug-target interactions were predicted by DeepPurpose. Results. A total of 433 genes were found associated with drug-resistant melanomas by text mining. The most statistically differential functional enriched pathways of GO and KEGG analyses contained 348 genes, and 27 hub genes were further screened out by MCODE in Cytoscape. Six genes were identified with statistical differences after survival analysis and literature review. 16 candidate drugs targeted at hub genes were found by Pharmaprojects under our restrictions. Finally, 11 ERBB2-targeted drugs with top affinity scores were predicted by DeepPurpose, including 10 ERBB2 kinase inhibitors and 1 antibody-drug conjugate. Conclusion. Text mining and bioinformatics are valuable methods for gene identification in drug discovery. DeepPurpose is an efficient and operative deep learning tool for predicting the DTI and selecting the candidate drugs.