Drug Targets Research Articles

Neem Leaf Glycoprotein Disrupts Exhausted CD8+ T-Cell-Mediated Cancer Stem Cell Aggression.

Targeting exhausted CD8+ T-cell (TEX)-induced aggravated cancer stem cells (CSC) holds immense therapeutic potential. In this regard, immunomodulation via Neem Leaf Glycoprotein (NLGP), a plant-derived glycoprotein immunomodulator is explored. Since former reports have proven immune dependent-tumor restriction of NLGP across multiple tumor models, we hypothesized that NLGP might reprogram and rectify TEX to target CSCs successfully. In this study, we report that NLGP's therapeutic administration significantly reduced TEX-associated CSC virulence in in vivo B16-F10 melanoma tumor model. A similar trend was observed in in vitro generated TEX and B16-F10/MCF7 coculture setups. NLGP rewired CSCs by downregulating clonogenicity, multidrug resistance phenotypes and PDL1, OCT4, and SOX2 expression. Cell cycle analysis revealed that NLGP educated-TEX efficiently pushed CSCs out of quiescent phase (G0G1) into synthesis phase (S), supported by hyper-phosphorylation of G0G1-S transitory cyclins and Rb proteins. This rendered quiescent CSCs susceptible to S-phase-targeting chemotherapeutic drugs like 5-fluorouracil (5FU). Consequently, combinatorial treatment of NLGP and 5FU brought optimal CSC-targeting efficiency with an increase in apoptotic bodies and proapoptotic BID expression. Notably a strong nephron-protective effect of NLGP was also observed, which prevented 5FU-associated toxicity. Furthermore, Dectin-1-mediated NLGP uptake and subsequent alteration of Notch1 and mTOR axis were deciphered as the involved signaling network. This observation unveiled Dectin-1 as a potent immunotherapeutic drug target to counter T-cell exhaustion. Cumulatively, NLGP immunotherapy alleviated exhausted CD8+ T-cell-induced CSC aggravation. Implications: Our study recommends that NLGP immunotherapy can be utilized to counter ramifications of T-cell exhaustion and to target therapy elusive aggressive CSCs without evoking toxicity.

Plasma Proteomics to Identify Drug Targets and Potential Drugs for Retinal Artery Occlusion: An Integrated Analysis in the UK Biobank.

Retinal artery occlusion (RAO), which is positively correlated with acute ischemic stroke (IS) and results in severe visual impairment, lacks effective intervention drugs. This study aims to perform integrated analysis using UK Biobank plasma proteome data of RAO and IS to identify potential targets and preventive drugs. A total of 7191 participants (22 RAO patients, 1457 IS patients, 8 individuals with both RAO and IS, and 5704 healthy age-gender-matched controls) were included in this study. Unique 1461 protein expression profiles of RAO, IS, and the combined data set, extracted from UK Biobank Plasma proteomics projects, were analyzed using both differential expression analysis and elastic network regression (Enet) methods to identify shared key proteins. Subsequent analyses, including single cell type expression assessment, pathway enrichment, and druggability analysis, were conducted for verifying shared key proteins and discovery of new drugs. Five proteins were found to be shared among the samples, with all of them showing upregulation. Notably, adhesion G-protein coupled receptor G1 (ADGRG1) exhibited high expression in glial cells of the brain and eye tissues. Gene set enrichment analysis revealed pathways associated with lipid metabolism and vascular regulation and inflammation. Druggability analysis unveiled 15 drug candidates targeting ADGRG1, which demonstrated protective effects against RAO, especially troglitazone (-8.5 kcal/mol). Our study identified novel risk proteins and therapeutic drugs associated with the rare disease RAO, providing valuable insights into potential intervention strategies.

Infection-Sensitive SPION/PLGA Scaffolds Promote Periodontal Regeneration via Antibacterial Activity and Macrophage-Phenotype Modulation.

Inflammation caused by a bacterial infection and the subsequent dysregulation of the host immune-inflammatory response are detrimental to periodontal regeneration. Herein, we present an infection-sensitive scaffold prepared by layer-by-layer assembly of Feraheme-like superparamagnetic iron oxide nanoparticles (SPIONs) on the surface of a three-dimensional-printed polylactic-co-glycolic acid (PLGA) scaffold. The SPION/PLGA scaffold is magnetic, hydrophilic, and bacterial-adhesion resistant. As indicated by gene expression profiling and confirmed by quantitative real-time reverse transcription polymerase chain reaction and flow cytometry analysis, the SPION/PLGA scaffold facilitates macrophage polarization toward the regenerative M2 phenotype by upregulating IL-10, which is the molecular target of repair promotion, and inhibits macrophage polarization toward the proinflammatory M1 phenotype by downregulating NLRP3, which is the molecular target of anti-inflammation. As a result, macrophages modulated by the SPS promote osteogenic differentiation of bone marrow mesenchymal stromal cells (BMSCs) in vitro. In a rat periodontal defect model, the SPION/PLGA scaffold increased IL-10 secretion and decreased NLRP3 and IL-1β secretion with Porphyromonas gingivalis infection, achieving superior periodontal regeneration than the PLGA scaffold alone. Therefore, this antibacterial SPION/PLGA scaffold has anti-inflammatory and bacterial antiadhesion properties to fight infection and promote periodontal regeneration by immunomodulation. These findings provide an important strategy for developing engineered scaffolds to treat periodontal defects.

A Quantitative Adverse Outcome Pathway for Embryonic Activation of the Aryl Hydrocarbon Receptor of Fishes by Polycyclic Aromatic Hydrocarbons Leading to Decreased Fecundity at Adulthood.

Quantitative adverse outcome pathways (qAOPs) describe the response-response relationships that link the magnitude and/or duration of chemical interaction with a specific molecular target to the probability and/or severity of the resulting apical-level toxicity of regulatory relevance. The present study developed the first qAOP for latent toxicities showing that early life exposure adversely affects health at adulthood. Specifically, a qAOP for embryonic activation of the aryl hydrocarbon receptor 2 (AHR2) of fishes by polycyclic aromatic hydrocarbons (PAHs) leading to decreased fecundity of females at adulthood was developed by building on existing qAOPs for (1) activation of the AHR leading to early life mortality in birds and fishes, and (2) inhibition of cytochrome P450 aromatase activity leading to decreased fecundity in fishes. Using zebrafish (Danio rerio) as a model species and benzo[a]pyrene as a model PAH, three linked quantitative relationships were developed: (1) plasma estrogen in adult females as a function of embryonic exposure, (2) plasma vitellogenin in adult females as a function of plasma estrogen, and (3) fecundity of adult females as a function of plasma vitellogenin. A fourth quantitative relationship was developed for early life mortality as a function of sensitivity to activation of the AHR2 in a standardized in vitro AHR transactivation assay to integrate toxic equivalence calculations that would allow prediction of effects of exposure to untested PAHs. The accuracy of the predictions from the resulting qAOP were evaluated using experimental data from zebrafish exposed as embryos to another PAH, benzo[k]fluoranthene. The qAOP developed in the present study demonstrates the potential of the AOP framework in enabling consideration of latent toxicities in quantitative ecological risk assessments and regulatory decision-making. Environ Toxicol Chem 2024;00:1-12. © 2024 SETAC.

Unveiling Resistance and Virulence Mechanisms under Darwinian Positive Selection for Novel Drug Discovery for Gardnerella vaginalis

Gardnerella vaginalis is a Gram-variable bacillus capable of causing bacterial vaginosis, a condition prevalent in reproductive-age women, this bacterium is present in almost 100% of cases and is also considered a gateway to various sexually transmitted infections. This organism exhibits high pathogenicity linked to virulence and resistance genes acquired throughout evolution, showcasing elevated resistance to a broad spectrum of drug classes. This study conducted comparative genomic analyses to identify these genes and correlate their presence with positive Darwinian selection. Additionally, new drug targets were selected through docking and molecular modeling, guided by the heightened antimicrobial resistance exhibited by this microbial species. The available genomes of G. vaginalis were analyzed, and the orthologous genes were delineated and positively selected, whereby 29 groups were found. Of these genes, one of great importance was predicted, Mef(A), which is related to resistance to the macrolide group of antibiotics, which are one of the main choices for the treatment of sexually transmitted infections. Additionally, two potential protein candidates were selected as drug targets. These proteins were linked with a natural compound each and are considered good potential drug targets. The analyses in this study contribute to analyzing the evolution of the species and how resistance genes are related to their permanence as a potential pathogen.

Exploring the causal effect between lipid-modifying drugs and idiopathic pulmonary fibrosis: a drug-target Mendelian randomization study

BackgroundIdiopathic pulmonary fibrosis (IPF) is a respiratory disorder of obscure etiology and limited treatment options, possibly linked to dysregulation in lipid metabolism. While several observational studies suggest that lipid-lowering agents may decrease the risk of IPF, the evidence is inconsistent. The present Mendelian randomization (MR) study aims to determine the association between circulating lipid traits and IPF and to assess the potential influence of lipid-modifying medications for IPF.MethodsSummary statistics of 5 lipid traits (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride, apolipoprotein A, and apolipoprotein B) and IPF were sourced from the UK Biobank and FinnGen Project Round 10. The study’s focus on lipid-regulatory genes encompassed PCSK9, NPC1L1, ABCG5, ABCG8, HMGCR, APOB, LDLR, CETP, ANGPTL3, APOC3, LPL, and PPARA. The primary effect estimates were determined using the inverse-variance-weighted method, with additional analyses employing the contamination mixture method, robust adjusted profile score, the weighted median, weighted mode methods, and MR-Egger. Summary-data-based Mendelian randomization (SMR) was used to confirm significant lipid-modifying drug targets, leveraging data on expressed quantitative trait loci in relevant tissues. Sensitivity analyses included assessments of heterogeneity, horizontal pleiotropy, and leave-one-out methods.ResultsThere was no significant effect of blood lipid traits on IPF risk (all P＞0.05). Drug-target MR analysis indicated that genetic mimicry for inhibitor of NPC1L1, PCSK9, ABCG5, ABCG8, and APOC3 were associated with increased IPF risks, with odds ratios (ORs) and 95% confidence intervals (CIs) as follows: 2.74 (1.05–7.12, P = 0.039), 1.36 (1.02–1.82, P = 0.037), 1.66 (1.12–2.45, P = 0.011), 1.68 (1.14–2.48, P = 0.009), and 1.42 (1.20–1.67, P = 3.17×10-5), respectively. The SMR method identified a significant association between PCSK9 gene expression in whole blood and reduced IPF risk (OR = 0.71, 95% CI: 0.50–0.99, P = 0.043). Sensitivity analyses showed no evidence of bias.ConclusionsSerum lipid traits did not significantly affect the risk of idiopathic pulmonary fibrosis. Drug targets MR studies examining 12 lipid-modifying drugs indicated that PCSK9 inhibitors could dramatically increase IPF risk, a mechanism that may differ from their lipid-lowering actions and thus warrants further investigation.

Metabolomics: Recent Advances and Future Prospects Unveiled

Abstract: In the era of genomics, fueled by advanced technologies and analytical tools, metabolomics has become a vital component in biomedical research. Its significance spans various domains, encompassing biomarker identification, uncovering underlying mechanisms and pathways, as well as the exploration of new drug targets and precision medicine. This article presents a comprehensive overview of the latest developments in metabolomics techniques, emphasizing their wide-ranging applications across diverse research fields and underscoring their immense potential for future advancements.

Network Pharmacology Combined with GEO Analysis of the Mechanism of Qing-Jin-Hua-Tan Decoction in the Treatment of Non-small Cell Lung Cancer.

Non-small-cell lung cancer (NSCLC) is one of the most prevalent malignancies and poses a significant threat to human health. Qing-Jin-Hua-Tan (QJHT) decoction is a classical herbal remedy that has demonstrated therapeutic effects in various diseases, including NSCLC, and can improve the quality of life of patients with respiratory conditions. However, the mechanism underlying the effect of the QJHT decoction on NSCLC remains unclear and requires further investigation. We collected NSCLC-related gene datasets from the GEO database and performed differential gene analysis, followed by using WGCNA to identify the core set of genes associated with NSCLC development. The TCMSP and HERB databases were searched to identify the active ingredients and drug targets, and the core gene target datasets related to NSCLC were merged to identify the intersecting targets of drugs and diseases for GO and KEGG pathway enrichment analysis. We then constructed a protein-protein interaction (PPI) network map of drug diseases using the MCODE algorithm and identified key genes using topology analysis. The disease-gene matrix underwent immunoinfiltration analysis, and we analyzed the association between intersecting targets and immunoinfiltration. We obtained the GSE33532 dataset that met the screening criteria, and a total of 2211 differential genes were identified using differential gene analysis. We performed GSEA analysis and WGCNA analysis for a crossover with differential genes, resulting in 891 key targets for NSCLC. The drug database was screened to obtain 217 active ingredients and 339 drug targets of QJHT. By constructing a PPI network, the active ingredients of QJHT decoction were intersected with the targets of NSCLC, resulting in 31 intersected genes. Enrichment analysis of the intersection targets showed that 1112 biological processes, 18 molecular functions, and 77 cellular compositions were enriched in GO functions, and 36 signaling pathways were enriched in KEGG pathways. Based on immune-infiltrating cell analysis, we found that the intersection targets were significantly associated with multiple infiltrating immune cells. Our analysis using network pharmacology and mining of the GEO database revealed that QJHT decoction can potentially treat NSCLC through multi-target and multi-signaling pathways, while also regulating multiple immune cells.

New Insights on the Therapeutic Potential of Runt-Related Transcription Factor2 for Osteoarthritis: Evidence from Mendelian Randomization.

Research has highlighted the role of runt-related transcription factor2 (Runx2) in the development of osteoarthritis (OA); however, its causal association remains unclear. This study aimed to explore whether Runx2 expression is causally associated with OA and assess its therapeutic potential for OA. Genetic proxy instruments for Runx2 expression were obtained from gene expression quantitative trait locus (eQTLs) study of eQTLGen Consortium (n = 31,684). Aggregated genome-wide association study (GWAS) data for OA (including all OA [177,517 cases and 649,173 controls], knee OA (KOA) [62,497 cases and 333,557 controls], and hip OA (HOA) [36,445 cases and 316,943 controls]) were extracted from the Genetics of Osteoarthritis Consortium. We integrated eQTLs data with OA GWAS data to estimate their causal association and to estimate the potential of Runx2 as a drug target in the treatment of OA using summary data-based Mendelian randomization (SMR) analysis. Furthermore, different OA GWAS data (including all OA [77,052 cases and 378,169 controls], KOA [24,955 cases and 378,169 controls], and HOA [15,704 cases and 378,169 controls]) derived from the GWAS Catalog database were used for replication study. SMR analysis showed that high expression levels of Runx2 were associated with an increased risk of all OA [odds ratio (OR) 1.044, 95% confidence interval (CI) 1.023-1.067; P = 5.03 × 10-5], KOA (OR1.040, 95%CI 1.006-1.075; P = 0.021), and HOA (OR1.067, 95%CI 1.022-1.113; P = 0.003). This suggests that Runx2 inhibitors may have promising potential for the treatment of OA. Notably, the causal effects of Runx2 with all OA (OR1.053, 95%CI 1.027-1.079; P = 3.95 × 10-5) and KOA (OR1.043, 95%CI 1.001-1.087; P = 0.045) were repeated in the replication study, but limited evidence supported the association of Runx2 expression levels with HOA (OR1.045, 95%CI 0.993-1.101; P = 0.094). Our analyses indicate a positive correlation between Runx2 expression and OA risk across all three phenotypes, suggesting the potential of Runx2 inhibitors in the treatment of OA and providing evidence from a genetic perspective.

Glucose Transporter and Sensor Mechanisms in Fungal Pathogens as Potential Drug Targets.

Fungal infections are emerging as major health challenges in recent years. The development of resistance against existing antifungal agents needs urgent attention and action. The limited classes of antifungal drugs available, their tendency to cause adverse effects, lack of effectiveness, etc., are the major limitations of current therapy. Thus, there is a pressing demand for new antifungal drug classes to cope with the present circumstances. Glucose is the key source of energy for all organisms, including fungi. Glucose plays a crucial role as a source of carbon and energy for processes like virulence, growth, invasion, biofilm formation, and resistance development. The glucose transport and sensing mechanisms are well developed in these organisms as an important strategy to sustain survival. Modulating these transport or sensor mechanisms may serve as an important strategy to inhibit fungal growth. Moreover, the structural difference between human and fungal glucose transporters makes them more appealing as drug targets. Limited literature is available for fungal glucose entry mechanisms. This review provides a comprehensive account of sugar transport mechanisms in common fungal pathogens.

Mechanistic and structural insights into vitamin B2 metabolizing enzyme riboflavin kinase from Leishmania donovani

Leishmania donovani relies on specific vitamins and cofactors crucial for its survival and pathogenesis. Tailoring therapies to disrupt these pathways offers a promising strategy for the treatment of Visceral Leishmaniasis. Current treatment regimens are limited due to drug resistance and high costs. The dependency of Leishmania parasites on Vitamin B2 and its metabolic products is not known. In this study, we have biochemically and biophysically characterized a Vitamin B2 metabolism enzyme, riboflavin kinase from L. donovani (LdRFK) which converts riboflavin (vitamin B2) into flavin mononucleotide (FMN). Sequence comparison with human counterpart reflects 31.58 % identity only, thus opening up the possibility of exploring it as drug target. The rfk gene was cloned, expressed and the recombinant protein was purified. Kinetic parameters of LdRFK were evaluated with riboflavin and ATP as substrates which showed differential binding affinity when compared with the human RFK enzyme. Thermal and denaturant stability of the enzyme was evaluated. The rfk gene was overexpressed in the parasites and its role in growth and cell cycle was evaluated. In the absence of crystal structure, homology modelling and molecular dynamic simulation studies were performed to predict LdRFK structure. The data shows differences in substrate binding between human and parasite enzyme. This raises the possibility of exploring LdRFK for specific designing of antileishmanial molecules. Gene disruption studies can further validate its candidature as antileishmanial target.

The Gene Network Correlation Analysis of Obesity to Type 1 Diabetes and Cardiovascular Disorders: An Interactome-Based Bioinformatics Approach.

The current study focuses on the importance of Protein-Protein Interactions (PPIs) in biological processes and the potential of targeting PPIs as a new treatment strategy for diseases. Specifically, the study explores the cross-links of PPIs network associated with obesity, type 1 diabetes mellitus (T1DM), and cardiac disease (CD), which is an unexplored area of research. The research aimed to understand the role of highly connected proteins in the network and their potential as drug targets. The methodology for this research involves retrieving genes from the NCBI online gene database, intersecting genes among three diseases (type 1 diabetes, obesity, and cardiovascular) using Interactivenn, determining suitable drug molecules using NetworkAnalyst, and performing various bioinformatics analyses such as Generic Protein-Protein Interactions, topological properties analysis, function enrichment analysis in terms of GO, and Kyoto Encyclopedia of Genes and Genomes (KEGG), gene co-expression network, and protein drug as well as protein chemical interaction network. The study focuses on human subjects. The results of this study identified 12 genes [VEGFA (Vascular Endothelial Growth Factor A), IL6 (Interleukin 6), MTHFR (Methylenetetrahydrofolate reductase), NPPB (Natriuretic Peptide B), RAC1 (Rac Family Small GTPase 1), LMNA (Lamin A/C), UGT1A1 (UDP-glucuronosyltransferase family 1 membrane A1), RETN (Resistin), GCG (Glucagon), NPPA (Natriuretic Peptide A), RYR2 (Ryanodine receptor 2), and PRKAG2 (Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 2)] that were shared across the three diseases and could be used as key proteins for protein-drug/chemical interaction. Additionally, the study provides an in-depth understanding of the complex molecular and biological relationships between the three diseases and the cellular mechanisms that lead to their development. Potentially significant implications for the therapy and management of various disorders are highlighted by the findings of this study by improving treatment efficacy, simplifying treatment regimens, cost-effectiveness, better understanding of the underlying mechanism of these diseases, early diagnosis, and introducing personalized medicine. In conclusion, the current study provides new insights into the cross-links of PPIs network associated with obesity, T1DM, and CD, and highlights the potential of targeting PPIs as a new treatment strategy for these prevalent diseases.

Identification of potential therapeutic targets for skin cutaneous melanoma on the basic of transcriptomics.

Advanced skin cutaneous melanoma (SKCM) is responsible for the majority of skin cancer-related deaths. Apart from the rare BRAF V600F mutation, which can be targeted with specific drugs, there are currently no other novel effective therapeutic targets. We used SMR analysis with cis-expressed quantitative trait locus (cis-eQTL) as the exposure variable and SKCM as the outcome variable to identify potential therapeutic targets for SKCM. Colocalization assays and HEIDI tests are used to test whether SKCM risk and gene expression are driven by common SNPs. Replication analysis further validated the findings, and we also constructed protein-protein interaction networks to explore the relationship between the identified genes and known SKCM targets. Drug prediction and molecular docking further validated the medicinal value of drug targets. Transcriptome differential analysis further validated that there were differences between normal tissues and SKCM for the selected targets. We identified 13 genes significantly associated with the risk of SKCM, including five protective genes and eight harmful genes. The HEIDI test and co-localization analysis further indicates a causal association between genes (SOX4, MAFF) and SKCM, categorized as Class 1 evidence targets. The remaining 11 genes, except for HELZ2 show a moderately causal association with SKCM, categorized as Class 2 evidence targets. Target druggability predictions from DGIdb suggest that SOX4, MAFF, ACSF3, CDK10, SPG7, and TCF25 are likely to be future drug targets. The study provides genetic evidence for targeting available drug genes for the treatment of SKCM.

The Identification of Potential Anti-Depression/Anxiety Drug Targets by Stress-Induced Rat Brain Regional Proteome and Network Analyses.

Depression and anxiety disorders are prevalent stress-related neuropsychiatric disorders and involve multiple molecular changes and dysfunctions across various brain regions. However, the specific and shared pathophysiological mechanisms occurring in these regions remain unclear. Previous research used a rat model of chronic mild stress (CMS) to segregate and identify depression-susceptible, anxiety-susceptible, and insusceptible groups; then the proteomes of six distinct brain regions (the hippocampus, prefrontal cortex, hypothalamus, pituitary, olfactory bulb, and striatum) were separately and quantitatively analyzed. To gain a comprehensive and systematic understanding of the molecular abnormalities, this study aimed to investigate and compare differential proteomics data from the six regions. Differentially expressed proteins (DEPs) were identified in between specific regions and across all regions and subjected to a series of bioinformatics analyses. Regional comparisons showed that stress-induced proteomic changes and corresponding gene ontology and pathway enrichments were largely distinct, attributable to differences in cell populations, protein compositions, and brain functions of these areas. Additionally, a notable degree of overlap in the significantly enriched terms was identified, potentially suggesting strong connections in the enrichment across different regions. Furthermore, intra-regional and inter-regional protein-protein interaction networks and drug-target-DEP networks were constructed. Integrated analysis of the three association networks in the six regions, along with the DisGeNET database, identified ten DEPs as potential targets for anti-depression/anxiety drugs. Collectively, these findings revealed commonalities and differences across different brain regions at the protein level induced by CMS, and identified several novel protein targets for the development of new therapeutics for depression and anxiety.

Mitochondria-Targeted Multifunctional Nanoprodrugs by Inhibiting Metabolic Reprogramming for Combating Cisplatin-Resistant Lung Cancer.

How to address the resistance of cisplatin (CDDP) has always been a clinical challenge. The resistance mechanism of platinum-based drugs is very complex, including nuclear DNA damage repair, apoptosis escape, and tumor metabolism reprogramming. Tumor cells can switch between mitochondrial oxidative phosphorylation (OXPHOS) and glycolysis and develop resistance to chemotherapy drugs through metabolic variability. In addition, due to the lack of histone protection and a relatively weak damage repair ability, mitochondrial DNA (mtDNA) is more susceptible to damage, which in turn affects mitochondrial OXPHOS and can become a potential target for platinum-based drugs. Therefore, mitochondria, as targets of anticancer drugs, have become a hot topic in tumor resistance research. This study constructed a self-assembled nanotargeted drug delivery system LND-SS-Pt-TPP/HA-CD. β-Cyclodextrin-grafted hydronic acid (HA-CD)-encapsulated prodrug nanoparticles can target CD44 on the tumor surface and further deliver the prodrug to intracellular mitochondria through a triphenylphosphine group (TPP+). Disulfide bonds can be selectively degraded by glutathione (GSH) in mitochondria, releasing lonidamine (LND) and the cisplatin prodrug (Pt(IV)). Under the action of GSH and ascorbic acid, Pt(IV) is further reduced to cisplatin (Pt(II)). Cisplatin can cause mtDNA damage, induce mitochondrial dysfunction and mitophagy, and then affect mitochondrial OXPHOS. Meanwhile, LND can reduce the hexokinase II (HK II) level, induce destruction of mitochondria, and block energy supply by glycolysis inhibition. Ultimately, this self-assembled nano targeted delivery system can synergistically kill cisplatin-resistant lung cancer cells, which supplies an overcome cisplatin resistance choice via the disrupt mitochondria therapy.

Investigating the potential mechanisms of Litsea cubeba essential oil for anti-melanoma through experimental validation, network pharmacology, and molecular docking analysis

Abstract Objectives Melanoma remains a challenge due to the lack of effective and low-toxicity treatments. Litsea cubeba essential oil (LEO), known for its tyrosinase inhibitory activity, has shown promise as an anti-melanoma compound, although robust scientific evidence is lacking. Methods We conducted GC-MS analysis to identify the major components of LEO and screened for effective components were further evaluated on A375 and HaCaT cells using the CCK-8 assay. Network pharmacology was employed to predict potential targets using PharmMapper and SwissTarget Prediction databases, with melanoma-related targets sourced from the GeneCards database. Protein–protein interaction (PPI) network was created using STRING and Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the DAVI database. Additionally, we constructed a natural product-main components-core targets-pathways-disease (NMCPD) network in Cytoscape and conducted molecular docking using PyMOL and Autodock Vina. Results GC-MS analysis revealed neral (cis-citral) and geranial (trans-citral) as the primary active components of LEO. Cell assays demonstrated that a citral mixture, in combination with LEO, effectively inhibited A375 cell growth with IC50 values of 35.94 ± 1.23 μM and 12.00 ± 0.96 μg/mL, while exhibiting minimal toxicity to HaCaT cells with IC50 values of 67.72 ± 2.96 μM and 22.32 ± 2.53 μg/mL. Screening identified10 hub targets among 190 common targets between drug and disease-related targets. KEGG pathway enrichment analysis suggested therapeutic effects of citral on melanoma by modulating signaling pathways. Molecular docking revealed strong binding affinity of neral and geranial with RXRA and ESR1, suggesting that citral, the principal LEO component, regulates multiple pathways for potential melanoma therapy. Conclusions These findings support the potential utility of LEO as a treatment for melanoma and highlight the importance of exploring tyrosinase inhibitors for the development of novel anti-melanoma drugs.

In vitro cancer cell line luminescence-based validation of anticancer phytocompounds obtained from Leucas biflora against HELA cervical and A549 lung cancer cells.

Current research aims to screen the anticancer prospective of Leucas biflora phytocompounds against apoptotic regulator target protein essential for cancer progression. In gas chromatography-mass spectrometry analysis major phytocompounds such as tetracosahexaene, squalene, phytol, 22-stigmasten-3-one, stigmasterol, fluorene, and 1,4-dihydro were identified in ethanolic leaf extract of Leucas biflora. In vitro, the free radical scavenging potential of ethanolic leaf extract of Leucas biflora was examined through its DPPH and ABTS radical scavenging potential IC50 value 15.35 and 13.20 μg/ml, respectively. Dose-dependent cytotoxicity was monitored against both A549 lung cancer and HELA cervical cancer cells. Leucas biflora ethanolic leaf extract highly reduces the cell viability of both HELA and A549 cells in in vitro cytotoxicity assays. Leucas biflora ethanolic extract produces 23.76% and 29.76% viability rates against A549 lung and HELA cervical cancer cell lines, and their IC50 values differ slightly at 95.80 and 90.40 μg/ml, respectively. In molecular docking analysis lung cancer target protein-ligand complex 5Y9T-16132746 showed a maximum score of -14 kcal/mol by exhibiting stable binding affinity and interactions among all screened complexes. Based on docking score nine phytocompounds from Leucas biflora and two reference standard drugs were chosen for further analysis. Further validation reveals that the fluorene, 1,4-dihydro possess good ADMET, Bioactivity and density functional theory indices.

Small Molecule Inhibitors against the Bacterial Pathogen Brucella.

Brucellosis remains one of the major zoonotic diseases worldwide. As a causative agent of brucellosis, it has many ways to evade recognition by the immune system, allowing it to replicate and multiply in the host, causing significant harm to both humans and animals. The pathogenic mechanism of Brucella has not been elucidated, making the identification of drug targets from the pathogenic mechanism a challenge. Metalloenzymatic targets and some protein targets unique to Brucella are exploitable in the development of inhibitors against this disease. The development of specific small molecule inhibitors is urgently needed for brucellosis treatment due to the antibiotic resistance of Brucella. This review summarizes the research on small molecule inhibitors of Brucella, which could be instructive for subsequent studies.

RELA-Mediated Upregulation of LINC03047 Promotes Ferroptosis in Silica-Induced Pulmonary Fibrosis via SLC39A14

Long non-coding RNAs play a key role in silicosis, a fatal fibrotic lung disease, and there is an urgent need to develop new treatment targets. Long intergenic non-protein-coding RNA 3047 (LINC03047) is associated with cancer, but its role and mechanism in the progression of silicosis require further elucidation. This study investigated the function of LINC03047 in the epithelial-mesenchymal transition (EMT) during silicosis progression. LINC03047 expression was upregulated in SiO2-treated BEAS-2B and A549 cells, promoting SiO2-induced ferroptosis and subsequent EMT. Moreover, knockdown of LINC03047 significantly decreased the expression of solute carrier family 39 member 14 (SLC39A14), a ferrous iron transporter, and inhibition of SLC39A14 alleviated the ferroptosis and EMT caused by LINC03047 overexpression. We further investigated that NF-κB p65 (RELA) was critical for LINC03047 transcription in SiO2-treated BEAS-2B and A549 cells. In vivo experiments showed that SLC39A14 deficiency improved SiO2-induced lipid peroxidation and EMT. Collectively, our study reveals the function of the RELA/LINC03047/SLC39A14 axis in SiO2-induced ferroptosis and EMT, thereby contributing to the identification of novel drug targets for silicosis therapy.

MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-modal features using deep learning algorithms. These features include 3D structural properties at the nucleotide base level of the RNA molecule, relational graphs based on overall RNA structure, and rich RNA semantic information. In our investigation, we gathered 851 interactions between RNA and small molecule ligand from the RNAglib dataset and RLBind training set. Unlike conventional training sets, this collection broadened its scope by including RNA complexes that have the same RNA sequence but change their respective binding sites due to structural differences or the presence of different ligands. This enhancement enables the MultiModRLBP model to more accurately capture subtle changes at the structural level, ultimately improving its ability to discern nuances among similar RNA conformations. Furthermore, we evaluated MultiModRLBP on two classic test sets, Test18 and Test3, highlighting its performance disparities on small molecules based on metal and non-metal ions. Additionally, we conducted a structural sensitivity analysis on specific complex categories, considering RNA instances with varying degrees of structural changes and whether they share the same ligands. The research results indicate that MultiModRLBP outperforms the current state-of-the-art methods on multiple classic test sets, particularly excelling in predicting binding sites for non-metal ions and instances where the binding sites are widely distributed along the sequence. MultiModRLBP also can be used as a potential tool when the RNA structure is perturbed or the RNA experimental tertiary structure is not available. Most importantly, MultiModRLBP exhibits the capability to distinguish binding characteristics of RNA that are structurally diverse yet exhibit sequence similarity. These advancements hold promise in reducing the costs associated with the development of RNA-targeted drugs.