The Role of Inflammasome in Abdominal Aortic Aneurysm and Its Potential Drugs.

Abdominal aortic aneurysm (AAA) has been recognized as a serious chronic inflammatory degenerative aortic disease in recent years. At present, there is no other effective intervention except surgical treatment for AAA. With the aging of the human population, its incidence is increasing year by year, posing a serious threat to human health. Modern studies suggest that vascular chronic inflammatory response is the core process in AAA occurrence and development. Inflammasome, a multiprotein complex located in the cytoplasm, mediates the expression of various inflammatory cytokines like interleukin (IL)-1ß and IL-18, and thus plays a pivotal role in inflammation regulation. Therefore, inflammasome may exert a crucial influence on the progression of AAA. This article reviews some mechanism studies to investigate the role of inflammasome in AAA and then summarizes several potential drugs targeting inflammasome for the treatment of AAA, aiming to provide new ideas for the clinical prevention and treatment of AAA beyond surgical methods.

Role of mitochondrial stress and the NLRP3 inflammasome in lung diseases.

BACKGROUND: As an organelle essential for intracellular energy supply, mitochondria are involved in intracellular metabolism and inflammation, and cell death. The interaction of mitochondria with the NLRP3 inflammasome in the development of lung diseases has been extensively studied. However, the exact mechanism by which mitochondria mediate the activation of the NLRP3 inflammasome and trigger lung disease is still unclear. METHODS: The literatures related to mitochondrial stress, NLRP3 inflammasome and lung diseases were searched in PubMed. RESULTS: This review aims to provide new insights into the recently discovered mitochondrial regulation of the NLRP3 inflammasome in lung diseases. It also describes the crucial roles of mitochondrial autophagy, long noncoding RNA, micro RNA, altered mitochondrial membrane potential, cell membrane receptors, and ion channels in mitochondrial stress and regulation of the NLRP3 inflammasome, in addition to the reduction of mitochondrial stress by nuclear factor erythroid 2-related factor 2 (Nrf2). The effective components of potential drugs for the treatment of lung diseases under this mechanism are also summarized. CONCLUSION: This review provides a resource for the discovery of new therapeutic mechanisms and suggests ideas for the development of new therapeutic drugs, thus promoting the rapid treatment of lung diseases.

Integrated analysis of diagnostic, prognostic value and potential drug treatment of GSDME in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSC) poses a global health challenge. Effective biomarkers for early detection are necessary to improve the survival rate of HNSC patient. The purpose of this study was using integrated bioinformatic analysis to investigate the potential biological roles of GSDME in HNSC. METHODS: The Gene Expression Omnibus (GEO) and Cancer Gnome Atlas (TCGA) databases were used to analyze the expression of GSDME in different cancer types. The correlation between GSDME expression and immune cell infiltration or immune checkpoint genes was examined by Spearman correlation analysis. DNA methylation analysis of the GSDME gene was conducted using the MethSurv database. Kaplan-Meier (K-M) survival curves, diagnostic receiver operating characteristic (ROC) curves, nomogram model, and Cox regression analysis were chosen to evaluate the diagnostic and prognostic predictive value of GSDME. Connectivity Map (Cmap) online platform, Protein Data Bank (PDB) database and Chem3D, AutoDock Tool and PyMol software were used to predict and visualize potential molecular drugs aimed for GSDME. RESULTS: GSDME expression level in HNSC was significantly higher than in the controls (p < 0.001). Differentially expressed genes (DEGs) correlation with GSDME were enriched in the GO pathways, such as protein activation cascade, complement activation and classical pathway (p < 0.05). According to GSEA, GSDME-associated differentially expressed genes were significantly enriched in KRAS signaling pathway and cytokine signaling molecule (p < 0.05). There is a significant relation between GSDME expression and immune cell infiltration in HNSC tissues, as well as immune checkpoint genes expression (p < 0.001). DNA methylation status of cg17790129 CpG islands of GSDME gene is correlated with HNSC prognosis (p < 0.05). Based on Cox regression analysis of HNSC patients, GSDME as a potential risk gene has high correlation with overall survival (OS) and disease specific survival (DSS) (p < 0.05). In a ROC curve analysis, HNSC tissues were differentiated from adjacent peritumoral tissues based on GSDME expression levels (AUC = 0.928). Totally six potential drugs targeted for GSDME were screened and the molecular docking tests between GSDME protein and candidate drugs were conducted. CONCLUSIONS: GSDME is a promising therapeutic target as well as a potential clinical biomarker in HNSC patients.

Mitochondrial Dynamics in Neurodegenerative Diseases: Unraveling the Role of Fusion and Fission Processes.

Neurodegenerative diseases (NDs) are a diverse group of disorders characterized by the progressive degeneration and death of neurons, leading to a range of neurological symptoms. Despite the heterogeneity of these conditions, a common denominator is the implication of mitochondrial dysfunction in their pathogenesis. Mitochondria play a crucial role in creating biomolecules, providing energy through adenosine triphosphate (ATP) generated by oxidative phosphorylation (OXPHOS), and producing reactive oxygen species (ROS). When they're not functioning correctly, becoming fragmented and losing their membrane potential, they contribute to these diseases. In this review, we explore how mitochondria fuse and undergo fission, especially in the context of NDs. We discuss the genetic and protein mutations linked to these diseases and how they impact mitochondrial dynamics. We also look at the key regulatory proteins in fusion (MFN1, MFN2, and OPA1) and fission (DRP1 and FIS1), including their post-translational modifications. Furthermore, we highlight potential drugs that can influence mitochondrial dynamics. By unpacking these complex processes, we aim to direct research towards treatments that can improve life quality for people with these challenging conditions.

Bioinformatics methods in biomarkers of preeclampsia and associated potential drug applications.

BACKGROUND: Preeclampsia is a pregnancy-related condition that causes high blood pressure and proteinuria after 20 weeks of pregnancy. It is linked to increased maternal mortality, organ malfunction, and foetal development limitation. In this view, there is a need critical to identify biomarkers for the early detection of preeclampsia. The objective of this study is to discover critical genes and explore medications for preeclampsia treatment that may influence these genes. METHODS: Four datasets, including GSE10588, GSE25906, GSE48424 and GSE60438 were retrieved from the Gene Expression Omnibus database. The GSE10588, GSE25906, and GSE48424 datasets were then removed the batch effect using the "sva" R package and merged into a complete dataset. The differentially expressed genes (DEGs) were identified using the "limma" R package. The potential small-molecule agents for the treatment of PE was further screened using the Connective Map (CMAP) drug database based on the DEGs. Further, Weight gene Co-expression network (WGNCA) analysis was performed to identified gene module associated with preeclampsia, hub genes were then identified using the logistic regression analysis. Finally, the immune cell infiltration level of genes was evaluated through the single sample gene set enrichment analysis (ssGSEA). RESULTS: A total of 681 DEGs (376 down-regulated and 305 up-regulated genes) were identified between normal and preeclampsia samples. Then, Dexamethasone, Prednisone, Rimexolone, Piretanide, Trazodone, Buflomedil, Scoulerin, Irinotecan, and Camptothecin drugs were screened based on these DEGs through the CMAP database. Two modules including yellow and brown modules were the most associated with disease through the WGCNA analysis. KEGG analysis revealed that the chemokine signaling pathway, Th1 and Th2 cell differentiation, B cell receptor signalling pathway and oxytocin signalling pathway were significantly enriched in these modules. Moreover, two key genes, PLEK and LEP were evaluated using the univariate and multivariate logistic regression analysis from the hub modules. These two genes were further validated in the external validation cohort GSE60438 and qRT-PCR experiment. Finally, we evaluated the relationship between immune cell and two genes. CONCLUSION: In conclusion, the present study investigated key genes associated with PE pathogenesis that may contribute to identifying potential biomarkers, therapeutic agents and developing personalized treatment for PE.

Identification of Novel Hub Genes Associated with Psoriasis Using Integrated Bioinformatics Analysis.

Psoriasis is a chronic, prolonged, and recurrent inflammatory skin disease and the current therapeutics can only alleviate the symptoms rather than cure it completely. Therefore, we aimed to identify the molecular signatures and specific biomarkers of psoriasis to provide novel clues for psoriasis and targeted therapy. In the present study, the Gene Expression Omnibus (GEO) database was used to retrieve three microarray datasets (GSE166388, GSE50790 and GSE42632) and to explore the differentially expressed genes (DEGs) in psoriasis using the Affy package in R software. The gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment were utilized to determine the common DEGs and their capabilities. The STRING database was used to develop DEG-encoded proteins and a protein-protein interaction network (PPI) and the Cytohubba plugin to classify hub genes. Using the NetworkAnalyst platform, we detected transcription factors (TFs), microRNAs and drug candidates interacting with hub genes. In addition, the expression levels of hub genes in HaCaT cells were detected by western blot. We screened the up- and downregulated DEGs from the transcriptome microarrays of corresponding psoriasis patients. Functional enrichment of DEGs in psoriasis was mainly associated with positive regulation of leukocyte cell-cell adhesion and T cell activation, cytokine binding, cytokine activity and the Wnt signaling pathway. Through further data processing, we obtained 57 intersecting genes in the three datasets and probed them in STRING to determine the interaction of their expressed proteins and we obtained the critical 10 hub genes in the Cytohubba plugin, including TOP2A, CDKN3, MCM10, PBK, HMMR, CEP55, ASPM, KIAA0101, ESC02, and IL-1ß. Using these hub genes as targets, we obtained 35 TFs and 213 miRNAs that may regulate these genes and 33 potential therapeutic agents for psoriasis. Furthermore, the expression levels of TOP2A, MCM10, PBK, ASPM, KIAA0101 and IL-1ß were observably increased in HaCaT cells. In conclusion, we identified potential biomarkers, risk factors and drugs for psoriasis.

Targeting DNA Topoisomerase II in Antifungal Chemotherapy.

Topoisomerase inhibitors have been in use clinically for the treatment of several diseases for decades. Although those enzymes are significant molecular targets in antibacterial and anticancer chemotherapy very little is known about the possibilities to target fungal topoisomerase II (topo II). Raising concern for the fungal infections, lack of effective drugs and a phenomenon of multidrug resistance underlie a strong need to expand the range of therapeutic options. In this review paper, we discussed the usefulness of fungal topo II as a molecular target for new drug discovery. On the basis of previously published data, we described structural and biochemical differences between fungal and human enzymes as well as a molecular basis of differential sensitivity to known anticancer drugs targeting the latter. This review focuses especially on highlighting the differences that may underlie the selectivity of action of new inhibitors. Distinct sites within fungal topo II in comparison with human counterparts are observed and should be further studied to understand the significance of those sites and their possible usage in design of new drugs.

Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer.

BACKGROUND: Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. An effective prediction model is urgently needed for the accurate assessment of patients' prognosis to assist clinical decision-making. METHODS: Gene expression data and clinicopathological data of the samples were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differential expressed genes (DEGs) analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, random forest screening and multivariate Cox regression analysis were applied to construct the risk signature. The effectiveness and independence of the model were validated by time-dependent receiver operating characteristic (ROC) curve, Kaplan-Meier (KM) survival analysis and survival point graph in training set, test set, TCGA entire set and GSE57495 set. The validity of the core gene was verified by immunohistochemistry and our own independent cohort. Meanwhile, functional enrichment analysis of DEGs between the high and low risk groups revealed the potential biological pathways. Finally, CMap database and drug sensitivity assay were utilized to identify potential small molecular drugs as the risk model-related treatments for PC patients. RESULTS: Four histone modification-related genes were identified to establish the risk signature, including CBX8, CENPT, DPY30 and PADI1. The predictive performance of risk signature was validated in training set, test set, TCGA entire set and GSE57495 set, with the areas under ROC curve (AUCs) for 3-year survival were 0.773, 0.729, 0.775 and 0.770 respectively. Furthermore, KM survival analysis, univariate and multivariate Cox regression analysis proved it as an independent prognostic factor. Mechanically, functional enrichment analysis showed that the poor prognosis of high-risk population was related to the metabolic disorders caused by inadequate insulin secretion, which was fueled by neuroendocrine aberration. Lastly, a cluster of small molecule drugs were identified with significant potentiality in treating PC patients. CONCLUSIONS: Based on a histone modification-related gene signature, our model can serve as a reliable prognosis assessment tool and help to optimize the treatment for PC patients. Meanwhile, a cluster of small molecule drugs were also identified with significant potentiality in treating PC patients.

Marine-Derived Macrocyclic Alkaloids (MDMAs): Chemical and Biological Diversity.

The curiosity and attention that researchers have devoted to alkaloids are due to their bioactivities, structural diversity, and intriguing chemistry. Marine-derived macrocyclic alkaloids (MDMAs) are considered to be a potential source of drugs. Trabectedin, a tetrahydroisoquinoline derivative, has been approved for the treatment of metastatic soft tissue sarcoma and ovarian cancers. MDMAs displayed potent activities that enabled them to be used as anticancer, anti-invasion, antimalarial, antiplasmodial, and antimicrobial. This review presents the reported chemical structures, biological activities, and structure-activity relationships of macrocyclic alkaloids from marine organisms that have been published since their discovery until May 2020. This includes 204 compounds that are categorized under eight subclasses: pyrroles, quinolines, bis-quinolizidines, bis-1-oxaquinolizidines, 3-alkylpiperidines, manzamines, 3-alkyl pyridinium salts, and motuporamines.

Targeted Drug Designing for Treating Masticatory Myofascial Pain Dysfunction Syndrome: An In Silico Simulation Study.

Background Masticatory Myofascial Pain Dysfunction Syndrome (MMPDS) is a musculoligamentous disorder that shares similarities with temporomandibular joint pain and odontogenic pain. It manifests as dull or aching pain in masticatory muscles, influenced by jaw movement. Computer-aided drug design (CADD) encompasses various theoretical and computational approaches used in modern drug discovery. Molecular docking is a prominent method in CADD that facilitates the understanding of drug-bimolecular interactions for rational drug design, mechanistic studies & the formation of stable complexes with increased specificity and potential efficacy. The docking technique provides valuable insights into binding energy, free energy, and complex stability predictions. Aim The aim of this study was to use the docking technique for myosin inhibitors. Materials and methods Four inhibitors of myosin were chosen from the literature. These compound structures were retrieved from the Zinc15 database. Myosin protein was chosen as the target and was optimized using the RCSB Protein Data Bank. After pharmacophore modeling, 20 novel compounds were found and the SwissDock was used to dock them with the target protein. We compared the binding energies of the newly discovered compounds to those of the previously published molecules with the target. Results The results indicated that among the 20 molecules ZINC035924607 and ZINC5110352 exhibited the highest binding energy and displayed superior properties compared to the other molecules. Conclusion The study concluded that ZINC035924607 and ZINC5110352 exhibited greater binding affinity than the reported inhibitors of myosin. Therefore, these two molecules can be used as a potential and promising lead for the treatment of MMPDS and could be employed in targeted drug therapy.

Bioinformatics identifies key genes and potential drugs for energy metabolism disorders in heart failure with dilated cardiomyopathy.

Background: Dysfunction in myocardial energy metabolism plays a vital role in the pathological process of Dilated Cardiomyopathy (DCM). However, the precise mechanisms remain unclear. This study aims to investigate the key molecular mechanisms of energy metabolism and potential therapeutic agents in the progression of dilated cardiomyopathy with heart failure. Methods: Gene expression profiles and clinical data for patients with dilated cardiomyopathy complicated by heart failure, as well as healthy controls, were sourced from the Gene Expression Omnibus (GEO) database. Gene sets associated with energy metabolism were downloaded from the Molecular Signatures Database (MSigDB) for subsequent analysis. Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis were employed to identify key modules and genes related to heart failure. Potential biological mechanisms were investigated through Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the construction of a competing endogenous RNA (ceRNA) network. Molecular docking simulations were then conducted to explore the binding affinity and conformation of potential therapeutic drugs with hub genes. Results: Analysis of the left ventricular tissue expression profiles revealed that, compared to healthy controls, patients with dilated cardiomyopathy exhibited 234 differentially expressed genes and 2 genes related to myocardial energy metabolism. Additionally, Benzoylaconine may serve as a potential therapeutic agent for the treatment of dilated cardiomyopathy. Conclusion: The study findings highlight the crucial role of myocardial energy metabolism in the progression of Dilated Cardiomyopathy. Notably, Benzoylaconine emerges as a potential candidate for treating Dilated Cardiomyopathy, potentially exerting its therapeutic effects by targeted modulation of myocardial energy metabolism through NRK and NT5.

Multi-omics characterization of RNA binding proteins reveals disease comorbidities and potential drugs in COVID-19.

The COVID-19 has led to a devastating global health crisis, which emphasizes the urgent need to deepen our understanding of the molecular mechanism and identifying potential antiviral drugs. Here, we comprehensively analyzed the transcriptomic and proteomic profiles of 178 COVID-19 patients, ranging from asymptomatic to critically ill. Our analyses found that the RNA binding proteins (RBPs) were likely to be perturbed in infection. Interactome analysis revealed that RBPs interact with virus proteins and the viral interacting RBPs were likely to locate in central regions of human protein-protein interaction network. Functional enrichment analysis revealed that the viral interacting RBPs were likely to be enriched in RNA transport, apoptosis and viral genome replication-related pathways. Based on network proximity analyses of 299 human complex-disease genes and COVID-19-related RBPs in the human interactome, we revealed the significant associations between complex diseases and COVID-19. Network analysis also implicated potential antiviral drugs for treatment of COVID-19. In summary, our integrative characterization of COVID-19 patients may thus help providing evidence regarding pathophysiology and potential therapeutic strategies for COVID-19.

Copper in cancer: from limiting nutrient to therapeutic target.

As an essential nutrient, copper's redox properties are both beneficial and toxic to cells. Therefore, leveraging the characteristics of copper-dependent diseases or using copper toxicity to treat copper-sensitive diseases may offer new strategies for specific disease treatments. In particular, copper concentration is typically higher in cancer cells, making copper a critical limiting nutrient for cancer cell growth and proliferation. Hence, intervening in copper metabolism specific to cancer cells may become a potential tumor treatment strategy, directly impacting tumor growth and metastasis. In this review, we discuss the metabolism of copper in the body and summarize research progress on the role of copper in promoting tumor cell growth or inducing programmed cell death in tumor cells. Additionally, we elucidate the role of copper-related drugs in cancer treatment, intending to provide new perspectives for cancer treatment.

Advances in research on potential inhibitors of multiple myeloma.

Multiple myeloma (MM) is a common hematological malignancy. Although recent clinical applications of immunomodulatory drugs, proteasome inhibitors and CD38-targeting antibodies have significantly improved the outcome of MM patient with increased survival, the incidence of drug resistance and severe treatment-related complications is gradually on the rise. This review article summarizes the characteristics and clinical investigations of several MM drugs in clinical trials, including their structures, mechanisms of action, structure-activity relationships, and clinical study progress. Furthermore, the application potentials of the drugs that have not yet entered clinical trials are also reviewed. The review also outlines the future directions of MM drug development.

Exploratory Study of Differentially Expressed Genes of Peripheral Blood Monocytes in Patients with Carotid Atherosclerosis.

BACKGROUND: The abundance of circulating monocytes is closely associated with the development of atherosclerosis in humans. OBJECTIVE: This study aimed to further research into diagnostic biomarkers and targeted treatment of carotid atherosclerosis (CAS). METHODS: We performed transcriptomics analysis through weighted gene co-expression network analysis (WGCNA) of monocytes from patients in public databases with and without CAS. Differentially expressed genes (DEGs) were screened by R package limma. Diagnostic molecules were derived by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms. NetworkAnalyst, miRWalk, and StarBase databases assisted in the construction of diagnostic molecule regulatory networks. The DrugBank database predicted drugs targeting the diagnostic molecules. RT-PCR tested expression profiles. RESULTS: From 14,369 hub genes and 61 DEGs, six differentially expressed monocyte-related hub genes were significantly associated with immune cells, immune responses, monocytes, and lipid metabolism. LASSO and SVM-RFE yielded five genes for CAS prediction. RT-PCR of these genes showed HMGB1 was upregulated, and CCL3, CCL3L1, CCL4, and DUSP1 were down-regulated in CAS versus controls. Then, we constructed and visualized the regulatory networks of 9 transcription factors (TFs), which significantly related to 5 diagnostic molecules. About 11 miRNAs, 19 lncRNAs, and 39 edges centered on four diagnostic molecules (CCL3, CCL4, DUSP1, and HMGB1) were constructed and displayed. Eleven potential drugs were identified, including ibrutinib, CTI-01, roflumilast etc. Conclusion: A set of five biomarkers were identified for the diagnosis of CAS and for the study of potential therapeutic targets.

Potential alternative drug treatment for bone giant cell tumor.

Background: Bone giant cell tumor (BGCT) is one of the world's major disease types of locally aggressive bone tumors. In recent years, denosumab treatment has been introduced before curettage surgery. However, the current therapeutic was practical only sometimes, given the local recurrence effects after discontinuation of denosumab. Due to the complex nature of BGCT, this study aims to use bioinformatics to identify potential genes and drugs associated with BGCT. Methods: The genes that integrate BGCT and fracture healing were determined by text mining. The gene was obtained from the pubmed2ensembl website. We filtered out common genes for the function, and signal pathway enrichment analyses were implemented. The protein-protein interaction (PPI) networks and the hub genes were screened by MCODE built-in Cytoscape software. Lastly, the confirmed genes were queried in the Drug Gene Interaction Database to determine potential genes and drugs. Results: Our study finally identified 123 common specific genes in bone giant cell tumors and fracture healing text mining concepts. The GO enrichment analysis finally analyzed 115 characteristic genes in BP, CC, and MF. We selected 10 KEGG pathways and identified 68 characteristic genes. We performed protein-protein interaction analysis (PPI) on 68 selected genes and finally identified seven central genes. In this study, these seven genes were substituted into drug-gene interactions, and there were 15 antineoplastic drugs, 1 anti-involving drug, and 1 anti-influenza drug. Conclusion: The 7 genes (including ANGPT2, COL1A1, COL1A2, CTSK, FGFR1, NTRK2, and PDGFB) and 17 drugs, which have not been used in BGCT, but 6 of them approved by the FDA for other diseases, could be potential genes and drugs, respectively, to improve BGCT treatment. In addition, the correlation study and analysis of potential drugs through genes provide great opportunities to promote the repositioning of drugs and the study of pharmacology in the pharmaceutical industry.

A novel prognostic signature and potential therapeutic drugs based on tumor immune microenvironment characterization in breast cancer.

Tumor microenvironment (TME) is closely correlated to the occurrence and progression of breast cancer, however its potentiality in assisting diagnosis and therapeutic decision remains unclear. Therefore, the major aim of this study is to explore the prognostic value of TME related gene in breast cancer. Expression matrices and clinical data of breast cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 12-gene molecular classifier was generated through the utilization of differentially expressed genes identified between distinct Tumor Microenvironment (TME) clusters, coupled with correlative regression analysis. The performance of this TME-driven prognostic signature (TPS) were examined across both the training and validation cohorts. Furthermore, our study revealed that breast cancer cases classified as high-risk based on the TPS exhibited the phenotype with elevated immune cell infiltration, higher tumor mutational burden, and a notably worse overall prognostic outcome. To conclude, the novel TME-based TPS was able to serve as a superior prognosis indicator for breast cancer, alone or jointly with other clinical factors. Also, breast cancer patients belong to different risk subgroups of TPS were found potentially suitable for distinguished therapeutic agents, which might improve personalized treatment for breast cancer in the future.

Effect of arctigenin on neurological diseases: A review.

ETHNOPHARMACOLOGICAL RELEVANCE: Arctium lappa L. is a common specie of Asteraceae. Its main active ingredient, Arctigenin (AG), in mature seeds exerts pharmacological effects on the Central Nervous System (CNS). AIM OF THE STUDY: To review studies on the specific effects of the AG mechanism on various CNS diseases and elucidate signal transduction mechanisms and their pharmacological actions. MATERIALS AND METHODS: This investigation reviewed the essential role of AG in treating neurological disorders. Basic information on Arctium lappa L. was retrieved from the Pharmacopoeia of the People's Republic of China. The related articles from 1981 to 2022 on the network database (including CNKI, PubMed, and Wan Fang and so on) were reviewed using AG and CNS diseases-related terms such as Arctigenin and Epilepsy. RESULTS: It was confirmed that AG has a therapeutic effect on Alzheimer's disease, Glioma, infectious CNS diseases (such as Toxoplasma and Japanese Encephalitis Virus), Parkinson's disease, Epilepsy, etc. In these diseases, related experiments such as a Western blot analysis revealed that AG could alter the content of some key factors (such as the reduction of Aß in Alzheimer's disease). However, in-vivo AG's metabolic process and possible metabolites are still undetermined. CONCLUSION: Based on this review, the existing pharmacological research has indeed made objective progress to elucidate how AG prevents and treats CNS diseases, especially senile degenerative disease such as Alzheimer's diseases. It was revealed that AG could be used as a potential nervous system drug as it has a wide range of effects in theory with markedly high application value, especially in the elder group. However, the existing studies are limited to in-vitro experiments; therefore, little is known about how AG metabolizes and functions in-vivo, limiting its clinical application and requiring further research.

Developing CuS for Predicting Aggressiveness and Prognosis in Lung Adenocarcinoma.

Cuproptosis is a newfound cell death form that depends on copper (Cu) ionophores to transport Cu into cancer cells. Studies on the relationship have covered most common cancer types and analyzed the links between cuproptosis-related genes (CRGs) and various aspects of tumor characteristics. In this study, we evaluated the role of cuproptosis in lung adenocarcinoma (LUAD) and constructed the cuproptosis-related score (CuS) to predict aggressiveness and prognosis in LUAD, so as to achieve precise treatment for patients. CuS had a better predictive performance than cuproptosis genes, possibly due to the synergy of SLC family genes, and patients with a high CuS had a poor prognosis. Functional enrichment analysis revealed the correlation between CuS and immune and mitochondrial pathways in multiple datasets. Furthermore, we predicted six potential drugs targeting high-CuS patients, including AZD3759, which is a targeted drug for LUAD. In conclusion, cuproptosis is involved in LUAD aggressiveness, and CuS can accurately predict the prognosis of patients. These findings provide a basis for precise treatment of patients with high CuS in LUAD.

Subtractive proteomics analysis to uncover the potent drug targets for distinctive drug design of Candidaauris.

Candida auris is a serious health concern of the current world that possesses a serious global health threat and is emerging at a high rate. Available antifungal drugs are failing to combat this pathogen as they are growing resistant to those drugs and some strains have already shown resistance to all three available antifungal drugs in the market. Hence, finding alternative therapies is essential for saving lives from this enemy. To make the development of new treatments easier, we conducted some in silico study of this pathogen to discover possible targets for drug design and also recommended some possible metabolites to test in vivo circumstances. The complete proteome of the representative strain was retrieved, and the duplicate, non-essential, human homologous, non-metabolic, and druggable proteins were then eliminated. As a result, out of a total of 5441 C. auris proteins, we were able to isolate three proteins (XP 028890156.1, XP 028891672.1, and XP 028891858.1) that are crucial for the pathogen's survival as well as host-non-homolog, metabolic, and unrelated proteins to the human microbiome. Their subcellular locations and interactions with a large number of proteins (10 proteins) further point to them being good candidates for therapeutic targets. Following in silico docking of 29 putative antifungals of plant origin against the three proteins we chose, Caledonixanthone E, Viniferin, Glaucine, and Jatrorrhizine were discovered to be the most effective means of inhibiting those proteins since they displayed higher binding affinities (ranging from -28.97 kcal/mol to -51.99 kcal/mol) than the control fluconazole (which ranged between -28.84 kcal/mol and -41.15 kcal/mol). According to the results of MD simulations and MM-PBSA calculations, Viniferin and Caledonixanthone E are the most effective ligands for the proteins XP 028890156.1, XP 028891672.1, and XP 028891858.1. Furthermore, they were predicted to be safe and also showed proper ADME properties.