Drug Target Genes Research Articles

Molecular mechanism of Achyranthis bidentatae radix and Morindae officinalis radix in osteoporosis therapy: An investigation based on network pharmacology, molecular docking, and molecular dynamics simulations

ObjectiveTo investigate the targets and mechanism of Achyranthis bidentatae radix and Morindae officinalis radix (ABR-MOR) for the treatment of osteoporosis (OP) by utilizing network pharmacology, molecular docking technology (MDT) and molecular dynamics simulation (MDS). MethodsThe main drug active ingredients (DAIs) and target genes of ABR-MOR were screened by the TCMSP database. The relevant targets of OP were obtained from GeneCards, DisGeNET, and CTD databases. Venny mapping is used to determine the potential target of ABR-MOR in the treatment of OP. The potential targets were analyzed using a protein‒protein interaction network and the MCODE module, and were subjected to GO and KEGG enrichment analysis. The binding sites and conditions of potential key DAIs and core targets were verified through MDT and MDS. ResultThe 32 DAIs and 212 targets of ABR-MOR were screened; 1453 OP-related targets were obtained, and 118 targets were mapped. The results of GO and KEGG enrichment analysis showed that the targets of DAIs-OP were mainly enriched in biological processes such as response to hormones, peptides, oxygen levels and reactive oxygen species, and positive regulation of cell migration. The main signaling pathways enriched in the regulation of the immune-inflammatory response, cell proliferation, senescence, apoptosis, angiogenesis, and estrogen signaling pathway. Additionally, the targets were also enriched in bone metabolism-related cell differentiation biological processes and the osteoclast differentiation signaling pathway. MDT and MDS results showed that wogonin, beta-sitosterol, and americanin A, the core DAIs of ABR-MOR, were able to form good ligand‒protein complexes with key targets such as PTGS2, PTGS1, PRKACA, PGR, MAPK1, AKT1, and RELA. ConclusionThis study preliminarily investigated the key targets, biological processes, and signaling pathways involved in the combined application of ABR and MOR for the treatment of OP. The results revealed that ABR-MOR may play a therapeutic role mainly by regulating immune-inflammatory responses, cellular biological processes, and osteoblast differentiation, which provides a theoretical basis for further experimental validation and a new strategy for the treatment of OP.

STEM-02. SYNGN: A NOVEL EPIGENETIC PLATFORM FOR PATIENT-SPECIFIC DRUG-MATCHING IN GLIOBLASTOMA

Abstract The alteration of the glioblastoma genome by epigenetic mechanisms that share functions with normal developmental processes, such as self-renewal and fate specification of NSC, is a key piece of evidence that links brain cancer pathogenesis with dysregulated stem cell functions. A patient-specific comparison of glioblastoma cells with NSC, a putative cell of origin of at least a proportion of these tumours, is not feasible as patient-matched endogenous NSC are not surgically accessible and all epigenetic studies in glioblastoma have so far compared epigenetic changes of different tumours with each other or to comparators obtained from foetal brains or an unrelated donor. We reasoned that availability of syngeneic GSC and NSC pairs would allow to identify crucial epigenetic differences on a patient-specific basis and would provide essential therapeutic contrast to define disease-and patient-intrinsic biomarkers of drug response that are less confounded by germline variation. We have derived GSC from IDH-wildtype glioblastoma and harnessed state-of-the-art stem cell technologies to generate patient-matched fibroblast-derived EPSC, which were induced to NSC (iNSC). We demonstrate that integrated analysis of the transcriptome and DNA methylome of GSC/iNSC pairs identifies druggable target genes (PTGER4, ALDH3B1, NTRK2) in a proportion of patients and we validate this patient-specific prediction of drug response at pre-clinical level in 3D synGLICO and in in vivo models. Integration of small RNA regulation to the pipeline allows refined in silico prediction of drug responses on a patient-specific basis. Most recently we have added assessment of chromatin remodelling (H3K4me3, H3K27ac, H3K3me3, H3K27me3 and ATACSeq) to the pipeline and shown that redistribution of selected histone marks as well as shifts in chromatin states across the genome identifies known and novel druggable regulatory mechanisms in GSC, which are specific of the neoplastic context. In conclusion, SYNGN is an epigenetic platform which can identify patient-specific druggable targets in glioblastoma.

Investigating the mechanism of action of Yanghe Pingchuan Granule in the treatment of bronchial asthma based on bioinformatics and experimental validation

BackgroundYanghe Pingchuan Granule (YPG) is a patented Chinese medicine developed independently by the Anhui Provincial Hospital of Traditional Chinese Medicine. For many years, it has been used for the treatment of asthma with remarkable clinical effects. However, the composition of YPG is complex, and its potential active ingredients and mechanism of action for the treatment of asthma are unknown. Materials and methodsIn this study, we investigated the potential mechanism of action of YPG in the treatment of asthma through a combination of bioinformatics and in vivo experimental validation. We searched for active compounds in YPG and asthma targets from multiple databases and obtained common targets. Subsequently, a protein-protein interaction (PPI) network for compound disease was constructed using the protein interaction database for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, hematoxylin and eosin (H&E) staining, Masson staining, enzyme-linked immunosorbent assay (ELISA) analysis, immunofluorescence (IF) experiments, and Western blot (WB) experiments were performed to verify the possible mechanism of action of YPG for asthma treatment. ResultsWe obtained 72 active ingredients and 318 drug target genes that overlap with asthma. Serine/threonine-protein kinase (AKT1), tumor protein p53 (TP53), tumor necrosis factor (TNF), interleukin (IL)-6, IL-1β, vascular endothelial growth factor-A (VEGFA), prostaglandin-endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 3 (MAPK3) and epidermal growth factor receptor (EGFR) were the most relevant genes in the PPI network. KEGG analysis showed a high number of genes enriched for the nuclear factor kappa-B (NF-κB) signaling pathway. Animal experiments confirmed that YPG reduced inflammatory cell infiltration and down-regulated the expression of ovalbumin-induced inflammatory factors. Furthermore, YPG treatment decreased the protein expression of NFĸB1, nuclear factor kappa B kinase subunit beta (IKBKB), vascular endothelial growth factor (VEGF), and vascular endothelial growth factor receptor 2 (VEGFR2) in lung tissue. ConclusionYPG has a positive effect on asthma by interfering with multiple targets. Furthermore, YPG may significantly inhibit the follicle-induced inflammatory response through the NF-ĸB signaling pathway.

Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses

Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses. We identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case-control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses. We identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case-control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51-0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07-1.13), 1.16 (1.09-1.24), and 1.09 (1.05-1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design. This large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer. Swedish Research Council, Cancerfonden, Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 111 Project and MAS cancer.

Integrated genomic network analysis revealed potential of a druggable target for hemorrhoid treatment

Hemorrhoids are a prevalent medical condition that necessitates effective treatment options. The current options for treatment consist of oral medications, topical applications, or surgery, yet a scarcity of highly effective drugs still exists. Genetic markers provide promising avenues for investigating the treatment of hemorrhoids, as they may reveal intricate biological mechanisms and targeted drug therapies, ultimately enhancing more precise treatment tailored to the patient. This study aims to identify new drug candidates for treating hemorrhoids through a meticulous bioinformatics approach and integrated with genomic network analysis. After extracting 21 druggable target genes using DrugBank from 293 genes connected to hemorrhoids, 87 possible drugs were selected. Three of these drugs (ketamine, methylene blue, and fulvestrant) hold potential in addressing issues associated with hemorrhoids and have been supported by clinical or preclinical studies. Eighty-four compounds present new therapeutic possibilities for managing hemorrhoids. We highlight that our findings indicate that NOX1 and NOS3 genes are promising biomarkers, with NOS3 gaining significance owing to its robust systemic functional annotations. Sapropterin, an existing drug, is closely associated with NOS3, providing a clear target for biomarker-driven interventions. This study illustrates the potential of combining genomic network analysis with bioinformatics to repurpose drugs for treating hemorrhoids. Subsequent research will explore the mechanisms for utilizing NOS3 targeting in the treatment of hemorrhoids.

Anti-Viral Activity of Bioactive Molecules of Silymarin against COVID-19 via In Silico Studies.

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection drove the global coronavirus disease 2019 (COVID-19) pandemic, causing a huge loss of human life and a negative impact on economic development. It is an urgent necessity to explore potential drugs against viruses, such as SARS-CoV-2. Silymarin, a mixture of herb-derived polyphenolic flavonoids extracted from the milk thistle, possesses potent antioxidative, anti-apoptotic, and anti-inflammatory properties. Accumulating research studies have demonstrated the killing activity of silymarin against viruses, such as dengue virus, chikungunya virus, and hepatitis C virus. However, the anti-COVID-19 mechanisms of silymarin remain unclear. In this study, multiple disciplinary approaches and methodologies were applied to evaluate the potential mechanisms of silymarin as an anti-viral agent against SARS-CoV-2 infection. In silico approaches such as molecular docking, network pharmacology, and bioinformatic methods were incorporated to assess the ligand-protein binding properties and analyze the protein-protein interaction network. The DAVID database was used to analyze gene functions, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment. TCMSP and GeneCards were used to identify drug target genes and COVID-19-related genes. Our results revealed that silymarin compounds, such as silybin A/B and silymonin, displayed triplicate functions against SARS-CoV-2 infection, including directly binding with human angiotensin-converting enzyme 2 (ACE2) to inhibit SARS-CoV-2 entry into the host cells, directly binding with viral proteins RdRp and helicase to inhibit viral replication and proliferation, and regulating host immune response to indirectly inhibit viral infection. Specifically, the targets of silymarin molecules in immune regulation were screened out, such as proinflammatory cytokines TNF and IL-6 and cell growth factors VEGFA and EGF. In addition, the molecular mechanism of drug-target protein interaction was investigated, including the binding pockets of drug molecules in human ACE2 and viral proteins, the formation of hydrogen bonds, hydrophobic interactions, and other drug-protein ligand interactions. Finally, the drug-likeness results of candidate molecules passed the criteria for drug screening. Overall, this study demonstrates the molecular mechanism of silymarin molecules against SARS-CoV-2 infection.

VariantSurvival: a tool to identify genotype-treatment response.

Motivation: For a number of neurological diseases, such as Alzheimer's disease, amyotrophic lateral sclerosis, and many others, certain genes are known to be involved in the disease mechanism. A common question is whether a structural variant in any such gene may be related to drug response in clinical trials and how this relationship can contribute to the lifecycle of drug development. Results: To this end, we introduce VariantSurvival, a tool that identifies changes in survival relative to structural variants within target genes. VariantSurvival matches annotated structural variants with genes that are clinically relevant to neurological diseases. A Cox regression model determines the change in survival between the placebo and clinical trial groups with respect to the number of structural variants in the drug target genes. We demonstrate the functionality of our approach with the exemplary case of the SETX gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package.

Establishment of comorbidity target pools and prediction of drugs candidate for multiple sclerosis and autoimmune thyroid diseases based on GWAS and transcriptome data.

Clinical observation has revealed that multiple sclerosis (MS) and autoimmune thyroid disease (AITD) are strongly correlated. The aim of this study was to explore the shared molecular causes of MS and AITD, and to conduct drug rearrangement on this basis, search for comorbidity drugs and feasible drugs for mutual reference between the two diseases. Based on genome-wide association study (GWAS) data and transcriptome data, susceptibility genes and differentially expressed genes related to MS and AITD were identified by bioinformatics analysis. Pathway enrichment, gene ontology (GO), protein-protein interaction analysis, and gene-pathway network analysis of the above genes were performed to identify a common target pool, including common genes, common hub genes, and common pathways, and to explore the specific pathogenesis of the two diseases, respectively. Drugs that target the common pathways/genes were identified through the Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug-Gene Interaction (DGI) Database. Common hub genes were compared with the target genes of drugs approved for treating MS/AITD and drugs under investigation identified by DrugBank and ClinicalTrials, respectively. We identified a pool of shared targets containing genes and pathways, including 46 common genetic susceptibility pathways and 9 common differentially expressed pathways, including JAK-STAT signaling pathway, Th17 cell differentiation, Th1 and Th2 cell differentiation, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. In addition, a total of 29 hub genes, including TYK2, JAK1, STAT3, IL2RA, HLA-DRB1, and TLR3, were identified. Drugs approved for treating MS or AITD, such as methylprednisolone, cyclophosphamide, glatiramer, natalizumab, and methimazole, can target the shared genes and pathways, among which methylprednisolone and cyclophosphamide have been shown to be beneficial for the treatment of the two diseases, indicating that these drugs have the potential to become a priority in the treatment of comorbidities. Moreover, drugs targeting multiple common genes and pathways, including tacrolimus, deucravacitinib, and nivolumab, were identified as potential drugs for the treatment of MS, AITD, and their comorbidities. We observed that T-cell activation-related genes and pathways play a major role in the pathogenesis of both MS and AITD, which may be the molecular basis of the comorbidity. Moreover, we identified a variety of drugs which may be used as priority or potential treatments for comorbidities.

Therapeutic targeting of the TPX2/TTK network in colorectal cancer

BackgroundWhile the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of precision medicine, the identification of actionable novel therapeutic targets could ultimately offer an alternative treatment strategy for CRC.MethodsRNA-Seq was conducted using the illumina platform, while bioinformatics analyses were conducted using CLC genomics workbench and iDEP.951. Colony forming unit, flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. The growth potential of CRC cells under 3-dimensional (3D) conditions was assessed using Matrigel. STRING database (v11.5) and Ingenuity Pathway Analysis (IPA) tool were used for network and pathway analyses. CRISPR-Cas9 perturbational effects database was used to identify potential therapeutic targets for CRC, through integration with gene-drug interaction database. Structural modeling and molecular docking were used to assess the interaction between candidate drugs and their targets.ResultsIn the current study, we investigated the therapeutic potential of targeting TPX2, TTK, DDX39A, and LRP8, commonly upregulated genes in CRC identified through differential expression analysis in CRC and adjacent non-cancerous tissue. Targeted depletion of TPX2 and TTK impaired CRC proliferation, cell cycle progression, and organoid formation under 3D culture conditions, while suppression of DDX39A and LRP8 had modest effects on CRC colony formation. Differential expression analysis and bioinformatics on TPX2 and TTK-deficient cells identified cell cycle regulation as the hallmark associated with loss of TPX2 and TTK. Elevated expression of TPX2 and TTK correlated with an oncogenic state in tumor tissue from patients with colon adenocarcinoma, thus corroborating an oncogenic role for the TPX2/TTK network in the pathogenesis of CRC. Gene set enrichment and pathway analysis of TPX2high/TTKhigh CRC identified numerous additional gene targets as integral components of the TPX2/TTK network. Integration of TPX2/TTK enriched network with CRISPR-Cas9 functional screen data identified numerous novel dependencies for CRC. Additionally, gene-drug interaction analysis identified several druggable gene targets enriched in the TPX2/TTK network, including AURKA, TOP2A, CDK1, BIRC5, and many others.ConclusionsOur data has implicated an essential role for TPX2 and TTK in CRC pathogenesis and identified numerous potential therapeutic targets and their drug interactions, suggesting their potential clinical use as a novel therapeutic strategy for patients with CRC.8pAfbPjv5QF2m5WMY3QXvqVideo

Signaling-induced systematic repression of miRNAs uncovers cancer vulnerabilities and targeted therapy sensitivity

Targeted therapies are effective in treating cancer, but success depends on identifying cancer vulnerabilities. In our study, we utilize small RNA sequencing to examine the impact of pathway activation on microRNA (miRNA) expression patterns. Interestingly, we discover that miRNAs capable of inhibiting key members of activated pathways are frequently diminished. Building on this observation, we develop an approach that integrates a low-miRNA-expression signature to identify druggable target genes in cancer. We train and validate our approach in colorectal cancer cells and extend it to diverse cancer models using patient-derived invitro and invivo systems. Finally, we demonstrate its additional value to support genomic and transcriptomic-based drug prediction strategies in a pan-cancer patient cohort from the National Center for Tumor Diseases (NCT)/German Cancer Consortium (DKTK) Molecularly Aided Stratification for Tumor Eradication (MASTER) precision oncology trial. In conclusion, our strategy can predict cancer vulnerabilities with highsensitivity and accuracy and might be suitable for future therapy recommendations in a variety of cancer subtypes.

Identification of m6A methylation-related genes in cerebral ischaemia‒reperfusion of Breviscapus therapy based on bioinformatics methods

BackgroundCerebral ischaemia‒reperfusion (I/R) frequently causes late-onset neuronal damage. Breviscapine promotes autophagy in microvascular endothelial cells in I/R and can inhibit oxidative damage and apoptosis. However, the mediation mechanism of breviscapine on neuronal cell death is unclear.MethodsFirst, transcriptome sequencing was performed on three groups of mice: the neuronal normal group (Control group), the oxygen-glucose deprivation/ reoxygenation group (OGD/R group) and the breviscapine administration group (Therapy group). Differentially expressed genes (DEGs) between the OGD/R and control groups and between the Therapy and OGD/R groups were obtained by the limma package. N6-methyladenosine (m6A) methylation-related DEGs were selected by Pearson correlation analysis. Then, prediction and confirmation of drug targets were performed by Swiss Target Prediction and UniProt Knowledgebase (UniProtKB) database, and key genes were obtained by Pearson correlation analysis between m6A-related DEGs and drug target genes. Next, gene set enrichment analysis (GSEA) and Ingenuity pathway analysis (IPA) were used to obtain the pathways of key genes. Finally, a circRNA-miRNA‒mRNA network was constructed based on the mRNAs, circRNAs and miRNAs.ResultsA total of 2250 DEGs between the OGD/R and control groups and 757 DEGs between the Therapy and OGD/R groups were selected by differential analysis. A total of 7 m6A-related DEGs, including Arl4d, Gm10653, Gm1113, Kcns3, Olfml2a, Stk26 and Tfcp2l1, were obtained by Pearson correlation analysis. Four key genes (Tfcp2l1, Kcns3, Olfml2a and Arl4d) were acquired, and GSEA showed that these key genes significantly participated in DNA repair, e2f targets and the g2m checkpoint. IPA revealed that Tfcp2l1 played a significant role in human embryonic stem cell pluripotency. The circRNA-miRNA‒mRNA network showed that mmu_circ_0001258 regulated Tfcp2l1 by mmu-miR-301b-3p.ConclusionsIn conclusion, four key genes, Tfcp2l1, Kcns3, Olfml2a and Arl4d, significantly associated with the treatment of OGD/R by breviscapine were identified, which provides a theoretical basis for clinical trials.

Constitutively Synergistic Multiagent Drug Formulations Targeting MERTK, FLT3, and BCL-2 for Treatment of AML.

Although high-dose, multiagent chemotherapy has improved leukemia survival rates, treatment outcomes remain poor in high-risk subsets, including acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) in infants. The development of new, more effective therapies for these patients is therefore an urgent, unmet clinical need. The dual MERTK/FLT3 inhibitor MRX-2843 and BCL-2 family protein inhibitors were screened in high-throughput against a panel of AML and MLL-rearranged precursor B-cell ALL (infant ALL) cell lines. A neural network model was built to correlate ratiometric drug synergy and target gene expression. Drugs were loaded into liposomal nanocarriers to assess primary AML cell responses. MRX-2843 synergized with venetoclax to reduce AML cell density in vitro. A neural network classifier based on drug exposure and target gene expression predicted drug synergy and growth inhibition in AML with high accuracy. Combination monovalent liposomal drug formulations delivered defined drug ratios intracellularly and recapitulated synergistic drug activity. The magnitude and frequency of synergistic responses were both maintained and improved following drug formulation in a genotypically diverse set of primary AML bone marrow specimens. We developed a nanoscale combination drug formulation that exploits ectopic expression of MERTK tyrosine kinase and dependency on BCL-2 family proteins for leukemia cell survival in pediatric AML and infant ALL cells. We demonstrate ratiometric drug delivery and synergistic cell killing in AML, a result achieved by a systematic, generalizable approach of combination drug screening and nanoscale formulation that may be extended to other drug pairs or diseases in the future.

TNF inhibitors associated with cardiovascular diseases and cardiometabolic risk factors: a Mendelian randomization study.

There is still disagreement about whether anti-tumor necrosis factor (TNF) therapy is beneficial or detrimental to cardiovascular conditions. This two-sample Mendelian randomization (MR) study aimed to evaluate the effects of long-term tumor necrosis factor (TNF) inhibition on cardiovascular diseases (CVDs) and cardiometabolic risk factors via genetically proxied inhibition of tumor necrosis factor receptor 1 (TNFR1) and TNF. Two genetic instruments were examined to mimic the long-term effect of TNF inhibitors. The first were single-nucleotide polymorphisms (SNPs) within or nearby drug-target genes TNFRSF1A and TNF (encoding TNFR1 and TNF) associated with circulating CRP levels. The other instruments were the expression quantitative trait loci (eQTLs) near the genes. Inverse variance-weighted MR (IVW-MR) and summary-based MR (SMR) methods were employed to estimate causal effects. In IVW-MR analysis, TNF-mediated circulating CRP levels were significantly associated with 4 out of 12 CVDs, including hypertension [odds ratio (OR) = 1.13; 95% CI, 1.09-1.18], coronary artery disease (OR = 3.18; 95% CI, 1.77-5.71), coronary atherosclerosis (OR = 1.05; 95% CI, 1.02-1.08) and type 2 diabetes (OR = 3.48; 95% CI, 1.98-6.10). These findings were also validated in the FinnGen study. Moreover, TNF inhibition was also associated with total cholesterol, triglycerides, apolipoprotein B, systolic blood pressure, serum cystatin C, height, weight, and body mass index. In this study, the decrease in several CVDs and cardiometabolic risk factors has been found to be causally associated with genetically proxied TNF inhibitors.

The mechanism of dehydroandrographolide inhibiting metastasis in gastric cancer based on network pharmacology and bioinformatics.

Gastric cancer (GC) is the most aggressive malignant tumor of the digestive tract. However, there is still a lack of effective treatment methods in clinical practice. Studies have shown that dehydroandrographolide (DA) has been shown to have anti-cancer activity in a variety of cancers, but it has not been reported in GC. Firstly, we obtained data on DA target genes, GC-related genes, and differentially expressed genes (DEGs) from the PharmMapper, GeneCards, and GEO databases, respectively. Then, the STRING database was used to construct the protein-protein interaction network of intersection genes, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of intersection genes were performed. Finally, 8 hub target genes were identified by analyzing their expression and prognostic survival, and molecular docking between the hub genes and DA was performed. In this study, 293 DA drug target genes, 11,366 GC-related genes, and 3184 DEGs were identified. Gene Ontology and KEGG analysis showed that the intersection genes of DA targets and GC-related genes were mainly related to cancer pathways involving apoptosis and cell adhesion. The intersection genes of DEGs, DA targets, and GC-related genes were also mainly related to cancer pathways involving chemical carcinogenesis, and drug metabolism. The molecular docking results showed that the 8 hub target genes had an apparent affinity for DA, which could be used as potential targets for DA treatment of GC. The results of this study show that the molecular mechanism by which DA inhibits GC metastasis involves multiple target genes. It may play an essential role in inhibiting the invasion and metastasis of GC by regulating the expression and polymorphism of hub target genes, such as MMP9, MMP12, CTSB, ESRRG, GSTA1, ADHIC, CA2, and AKR1C2.

Horizontal Gene Transfer and Drug Resistance Involving Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) acquires drug resistance at a rate comparable to that of bacterial pathogens that replicate much faster and have a higher mutation rate. One explanation for this rapid acquisition of drug resistance in Mtb is that drug resistance may evolve in other fast-replicating mycobacteria and then be transferred to Mtb through horizontal gene transfer (HGT). This paper aims to address three questions. First, does HGT occur between Mtb and other mycobacterial species? Second, what genes after HGT tend to survive in the recipient genome? Third, does HGT contribute to antibiotic resistance in Mtb? I present a conceptual framework for detecting HGT and analyze 39 ribosomal protein genes, 23S and 16S ribosomal RNA genes, as well as several genes targeted by antibiotics against Mtb, from 43 genomes representing all major groups within Mycobacterium. I also included mgtC and the insertion sequence IS6110 that were previously reported to be involved in HGT. The insertion sequence IS6110 shows clearly that the Mtb complex participates in HGT. However, the horizontal transferability of genes depends on gene function, as was previously hypothesized. HGT is not observed in functionally important genes such as ribosomal protein genes, rRNA genes, and other genes chosen as drug targets. This pattern can be explained by differential selection against functionally important and unimportant genes after HGT. Functionally unimportant genes such as IS6110 are not strongly selected against, so HGT events involving such genes are visible. For functionally important genes, a horizontally transferred diverged homologue from a different species may not work as well as the native counterpart, so the HGT event involving such genes is strongly selected against and eliminated, rendering them invisible to us. In short, while HGT involving the Mtb complex occurs, antibiotic resistance in the Mtb complex arose from mutations in those drug-targeted genes within the Mtb complex and was not gained through HGT.

Lipids, lipid-modifying drug target genes and migraine: a Mendelian randomization study

IntroductionMigraine, a prevalent headache disorder with unclear mechanisms and limited treatments, may be influenced by dyslipidemia and genetic factors. Statins and emerging lipid-modifying agents show potential but lack evidence for migraine management. Mendelian Randomization analysis offers insights into causal relationships and therapeutic targets. This study aims to explore genetically predicted lipid traits, drug targets, and their association with migraine risk.MethodWe conducted Mendelian randomization (MR) analyses utilizing genetic variants associated with lipid traits and variants in genes encoding the protein targets of various classes of lipid-lowering drugs. The specific drug classes investigated included HMGCR, PCSK9, NPC1L1, ABCG5/ABCG8, LDLR, LPL, ANGPTL3, APOB, CETP, and APOC3. To determine the effects on migraine risk, we meta-analyzed MR estimates for regional variants using data from two large sample sets. The genetic variants were weighted based on their associations with specific lipid traits, such as low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), Apolipoprotein A1, and Apolipoprotein B. To obtain association weights, we utilized data from lipid genetics consortia. For lipid-modifying drug targets that exhibited suggestive significance, we further employed expression quantitative trait locus (eQTL) data. Additionally, we performed colocalization analysis to assess genetic confounding.ResultThe use of genetic proxies for HMGCR inhibition demonstrated a significant association with a decreased risk of migraine in the FinnGen dataset (OR = 0.64, 95% CI: 0.46–0.88, p = 0.0006) and a nearly significant association in the Choquet dataset (OR = 0.78, 95% CI: 0.60–1.01, p = 0.06). When pooling the estimates, the overall effect size showed a reduced risk of migraine (OR = 0.73, 95% CI: 0.60–0.89, p = 0.0016). Similarly, genetic mimicry of LPL enhancement was associated with a lower risk of migraine in the FinnGen dataset (OR = 0.82, 95% CI: 0.69–0.96, p = 0.01) and the Choquet dataset (OR = 0.91, 95% CI: 0.83–0.99, p = 0.03). Pooling the estimates showed a consistent effect size (OR = 0.89, 95% CI: 0.83–0.96, p = 0.002). Sensitivity analyses yielded no statistically significant evidence of bias arising from pleiotropy or genetic confounding.ConclusionIn the study, it was observed that among the 10 lipid-lowering drug targets investigated, LPL and HMGCR showed significant associations with migraine risk. These findings indicate that LPL and HMGCR have the potential to serve as candidate drug targets for the treatment or prevention of migraines.

Effects of Dietary Inclusion of Asiaticoside on Growth Performance, Lipid Metabolism, and Gut Microbiota in Yellow-Feathered Chickens.

Excessive abdominal fat deposition in chickens is a major concern in the poultry industry. Nutritional interventions are a potential solution, but current options are limited. Asiaticoside (Asi), a herbal extract, has shown positive effects in animals, but its impact on poultry lipid metabolism is still unknown. In this study, the effects of dietary Asi on yellow-feathered chicken lipid metabolism and its potential mechanisms were investigated. A total of 120 chickens were randomly divided into three groups, with five replicates per group and 8 chickens per replicate. The chickens were fed a basal diet supplemented with 0, 0.01, or 0.05% Asi for 6 wk. The results showed that Asi down-regulated lipogenic gene expression and up-regulated lipid-breakdown-related genes in both the liver and fat tissues of the chickens, which resulted in a half reduction in abdominal fat while not affecting meat yield. Mechanistically, the hepatic and adipose PI3K/AKT pathway may be involved in Asi-induced fat loss in chickens as revealed by computer-aided reverse drug target prediction and gene expression analysis. Moreover, Asi ingestion also significantly modified the cecal microbiota of the chickens, resulting in a reduced Firmicutes to Bacteroidetes ratio and decreased abundance of bacteria positively correlated with abdominal fat deposition such as Ruminococcus, while increasing the abundance of bacteria inversely correlated with abdominal fat deposition such as Lactobacillus, Bacteroides, and Blautia. Collectively, these data suggest that Asi could ameliorate the abdominal fat deposition in yellow-feathered chickens, probably through modulating the PI3K/AKT pathway and gut microbiota function.

Investigation of the Underlying Mechanism of Zhibai Dihuang Pill in Treating Osteoporosis by using Network Pharmacology and Molecular Dynamics Simulation.

With society aging, the rising prevalence of osteoporosis (OP) has enormous social and economic implications. At present, the Zhibai Dihuang pill has been clinically applied in OP treatment and shown significant efficacy, but its underlying mechanism remains unclear. This study was designed to explore the mechanism of the Zhibai Dihuang pill treating OP. In this study, the active ingredients and corresponding targets in the Zhibai Dihuang pill were searched using the TCMSP platform. Based on the mRNA expression data of OP patients in the GEO database, differential expression analysis was conducted by bioinformatics means. By using the differentially expressed genes (DEGs), protein-protein interaction (PPI) network was constructed, and random walk with restart (RWR) analysis based on seed genes intersected from DEGs and drug target genes was conducted. On this basis, the drug-active ingredient-gene interaction network was built. The topological property of the network (degree) was statistically analyzed to find the key therapeutic target AKT1 for the treatment of OP. Molecular docking between AKT1 and the active ingredients was conducted, and according to the affinity score, diosgenin was determined as the key small molecule of the Zhibai Dihuang pill in OP treatment. Based on molecular dynamics simulation and cellular thermal shift assay validation, it was found that diosgenin had a good binding ability with AKT1. Cell experiments showed that diosgenin could affect the expression of bone markers and the mineralization of extracellular matrix in mouse osteoblasts by inhibiting the phosphorylation of AKT1, thus achieving the effect of OP treatment. Based on network pharmacology, this study clarified the key small molecule compounds in the Zhibai Dihuang pill and their action targets and preliminarily analyzed the molecular mechanism of the Zhibai Dihuang pill treating OP, providing a theoretical basis for the clinical use of the Zhibai Dihuang pill.

Molecular and Clinical Features of Fluconazole Non-susceptible Candida albicans Bloodstream Isolates Recovered in Korean Multicenter Surveillance Studies.

Acquired fluconazole resistance (FR) in bloodstream infection (BSI) isolates of Candida albicans is rare. We investigated the FR mechanisms and clinical features of 14 fluconazole non-susceptible (FNS; FR and fluconazole-susceptible dose-dependent) BSI isolates of C. albicans recovered from Korean multicenter surveillance studies during 2006-2021. Mutations causing amino acid substitutions (AASs) in the drug-target gene ERG11 and the FR-associated transcription factor genes TAC1, MRR1, and UPC2 of the 14 FNS isolates were compared with those of 12 fluconazole-susceptible isolates. Of the 14 FNS isolates, eight and seven had Erg11p (K143R, F145L, or G464S) and Tac1p (T225A, R673L, A736T, or A736V) AASs, respectively, which were previously described in FR isolates. Novel Erg11p, Tac1p, and Mrr1p AASs were observed in two, four, and one FNS isolates, respectively. Combined Erg11p and Tac1p AASs were observed in seven FNS isolates. None of the FR-associated Upc2p AASs were detected. Of the 14 patients, only one had previous azole exposure, and the 30-day mortality rate was 57.1% (8/14). Our data show that Erg11p and Tac1p AASs are likely to contribute to FR in C. albicans BSI isolates in Korea and that most FNS C. albicans BSIs develop without azole exposure.

Transcriptomics-driven drug repositioning for the treatment of diabetic foot ulcer

Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU.