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Results for “molecular docking”

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PubMed2025

Mechanism of action of curculigoside ameliorating osteoporosis: an analysis based on network pharmacology and experimental validation.

OBJECTIVE: This study aimed to predict and verify the mechanism of curculigoside in treating osteoporosis using network pharmacology, molecular docking technology, and micro-CT technology. METHODS: Herb databases were searched to identify and screen potential targets of curculigoside. The GeneCards platform was utilized to mine osteoporosis-related targets. Cytoscape 3.6.0 software was employed to construct a compound-target-disease network. A protein-protein interaction (PPI) network for curculigoside in osteoporosis treatment was established, and core targets were screened. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and GO biological process analyses were performed using the Metascape database. Finally, molecular docking and micro-CT were used to validate core targets relevant to osteoporosis. RESULTS: A total of 166 potential curculigoside targets and 4,313 osteoporosis-related targets were identified, with 91 common targets. Ten key targets, including matrix metalloproteinase (MMP)3, MMP9, interleukin (IL)-6, and caspase-3, were screened. KEGG pathway enrichment analysis indicated involvement in 10 pathways, such as the Rap1 signaling pathway and tumor necrosis factor (TNF) signaling pathway. Molecular docking results demonstrated strong binding affinity between curculigoside and the core targets. Micro-CT analysis revealed that curculigoside not only improved BMD, BV/TV, BS/BV, and Tb.Th but also reduced Tb.Sp in osteoporotic bone. CONCLUSIONS: Curculigoside is likely to treat osteoporosis through targets such as MMP3, MMP9, IL-6, and caspase-3, acting on signaling pathways including Rap1 and TNF. These results indicate that curculigoside exhibits multitarget and multipathway characteristics in osteoporosis treatment, providing a theoretical basis for further clinical investigation.

Osteoporosis↗

PubMed2006

Exploring the molecular basis of the enantioselective binding of penicillin G acylase towards a series of 2-aryloxyalkanoic acids: a docking and molecular dynamics study.

In the present paper, molecular modeling studies were undertaken in order to shed light on the molecular basis of the observed enantioselectivity of penicillin G acylase (PGA), a well known enzyme for its industrial applications, towards 16 racemic 2-aryloxyalkanoic acids, which have been reported to affect several biological systems. With this intention docking calculations and MD simulations were performed. Docking results indicated that the (S)-enantiomers establish several electrostatic interactions with SerB1, SerB386 and ArgB263 of PGA. Conversely, the absence of specific polar interactions between the (R)-enantiomers and ArgB263 seems to be the main reason for the different binding affinities observed between the two enantiomers. Results of molecular dynamics simulations demonstrated that polar interactions are responsible for both the ligand affinity and PGA enantiospecificity. Modeling calculations provided possible explanations for the observed enantioselectivity of the enzyme that rationalize available experimental data and could be the basis for future protein engineering efforts.

Alkanes↗

PubMed2003

An all-atom solution-equilibrated model for human extrinsic blood coagulation complex (sTF-VIIa-Xa): a protein-protein docking and molecular dynamics refinement study.

Tissue factor (TF)-bound factor (F)VIIa plays a critical role in activating FX, an event that rapidly results in blood coagulation. Despite recent advances in the structural information about soluble TF (sTF)-bound VIIa and Xa individually, the atomic details of the ternary complex are not known. As part of our long-term goal to provide a structural understanding of the extrinsic blood coagulation pathway, we built an all atom solution-equilibrated model of the human sTF-VIIa-Xa ternary complex using protein-protein docking and molecular dynamics (MD) simulations. The starting structural coordinates of sTF-VIIa and Xa were derived from dynamically equilibrated solution structures. Due to the flexible nature of the light-chain of the Xa molecule, a three-stage docking approach was employed in which SP (Arg195-Lys448)/EGF2 (Arg86-Arg139), EGF1 (Asp46-Thr85) and GLA (Ala1-Lys45) domains were docked in a sequential manner. The rigid-body docking approach of the FTDOCK method in conjunction with filtering based on biochemical knowledge from experimental site-specific mutagenesis studies provided the strategy. The best complex obtained from the docking experiments was further refined using MD simulations for 3 ns in explicit water. In addition to explaining most of the known experimental site-specific mutagenesis data pertaining to sTF-VIIa, our model also characterizes likely enzyme-binding exosites on FVIIa and Xa that may be involved in the ternary complex formation. According to the equilibrated model, the 140s loop of VIIa serves as the key recognition motif for complex formation. Stable interactions occur between the FVIIa 140s loop and the FXa -strand B2 region near the sodium-binding domain, the 160 s loop and the N-terminal activation loop regions. The helical-hydrophobic stack region that connects the GLA and EGF1 domains of VIIa and Xa appears to play a potential role in the membrane binding region of the ternary complex. The proposed model may serve as a reasonable structural basis for understanding the exosite-mediated substrate recognition of sTF-VIIa and to advance understanding of the TFPI-mediated regulatory pathway of the extrinsic blood coagulation cascade.

Binding Sites↗

PubMed2004

Structure-based discovery of a novel angiotensin-converting enzyme 2 inhibitor.

Angiotensin-converting enzyme 2 (ACE2) is considered an important therapeutic target for controlling cardiovascular diseases and severe acute respiratory syndrome (SARS) outbreaks. Recently solved high-resolution crystal structures of the apo-bound and inhibitor-bound forms of ACE2 have provided the basis for a novel molecular docking approach in an attempt to identify ACE2 inhibitors and compounds that block SARS coronavirus spike protein-mediated cell fusion. In this study, approximately 140 000 small molecules were screened by in silico molecular docking. In this structure-activity relation study, the molecules with the highest predicted binding scores were identified and assayed for ACE2 enzymatic inhibitory activity and for their ability to inhibit SARS coronavirus spike protein-mediated cell fusion. This approach identified N-(2-aminoethyl)-1 aziridine-ethanamine as a novel ACE2 inhibitor that also is effective in blocking the SARS coronavirus spike protein-mediated cell fusion. Thus, the molecular docking approach resulting in the inhibitory capacity of N-(2-aminoethyl)-1 aziridine-ethanamine provides an attractive small molecule lead compound on which the development of more effective therapeutic agents could be developed to modulate hypertension and for controlling SARS infections.

Angiotensin-Converting Enzyme 2↗

PubMed2005

Exploring blocker binding to a homology model of the open hERG K+ channel using docking and molecular dynamics methods.

Binding of blockers to the human voltage-gated hERG potassium channel is studied using a combination of homology modelling, automated docking calculations and molecular dynamics simulations, where binding affinities are evaluated using the linear interaction energy method. A homology model was constructed based on the available crystal structure of the bacterial KvAP channel and the affinities of a series of sertindole analogues predicted using this model. The calculations reproduce the relative binding affinities of these compounds very well and indicate that both polar interactions near the intracellular opening of the selectivity filter as well as hydrophobic complementarity in the region around F656 are important for blocker binding. These results are consistent with recent alanine scanning mutation experiments on the blocking of the hERG channel by other compounds.

Amino Acid Sequence↗

PubMed2026

Leveraging bioinformatics approaches for drug repositioning in space radiation protection.

The health effects of space radiation, primarily Galactic Cosmic Rays (GCRs), on humans remain largely unknown, with potential cardiovascular consequences posing a significant threat to astronauts on long-duration spaceflight missions. Currently, there are no established pharmacological countermeasures for GCR exposure. Drug repositioning offers a promising strategy to accelerate pharmaceutical research in space medicine. This study leverages existing bioinformatics techniques to identify and prioritize potential drug candidates associated with proteomic perturbations following simulated GCR exposure using previously published murine cardiac proteomic data. A protein-protein interaction (PPI) network was constructed using the top differentially expressed proteins (DEPs) from murine heart tissue following exposure to 5-ion GCRs as seed nodes, focusing on experimentally supported interactions. Network topology, Markov clustering, and functional enrichment analyses were used to characterize biologically relevant proteins and pathways. Drug-protein interactions were predicted using Drugst.One and mapped to PPI clusters of interest to identify candidate drugs. Selected drug-macromolecule interactions were further explored using CB-Dock2 molecular docking and short-duration molecular dynamics simulations as hypothesis-generating structural assessments. Analysis of a key PPI network cluster consisting of several ATP synthase proteins identified 23 unique drug candidates. These analyses demonstrate a systematic approach for leveraging bioinformatics techniques to identify candidate molecular targets and generate pharmacological hypotheses in the context of space radiation countermeasures. Ultimately, this strategy introduces a hypothesis-generating framework for the prioritization of potential drug candidates for future computational characterization and experimental investigation against spaceflight stressors.

Animals↗

PubMed2002

Docking and molecular dynamics studies at trypanothione reductase and glutathione reductase active sites.

A theoretical docking study on the active sites of trypanothione reductase (TR) and glutathione reductase (GR) with the corresponding natural substrates, trypanothione disulfide (T[S]2) and glutathione disulfide (GSSG), is reported. Molecular dynamics simulations were carried out in order to check the robustness of the docking results. The energetic results are in agreement with previous experimental findings and show the crossed complexes have lower stabilization energies than the natural ones. To test DOCK3.5, four nitro furanic compounds, previously designed as potentially active anti-chagasic molecules, were docked at the GR and TR active sites with the DOCK3.5 procedure. A good correlation was found between differential inhibitory activity and relative interaction energy (affinity). The results provide a validation test for the use of DOCK3.5 in connection with the design of anti-chagasic drugs.

Binding Sites↗

PubMed2006

Combining docking and molecular dynamic simulations in drug design.

A rational approach is needed to maximize the chances of finding new drugs, and to exploit the opportunities of potential new drug targets emerging from genomic and proteomic initiatives, and from the large libraries of small compounds now readily available through combinatorial chemistry. Despite a shaky early history, computer-aided drug design techniques can now be effective in reducing costs and speeding up drug discovery. This happy outcome results from development of more accurate and reliable algorithms, use of more thoughtfully planned strategies to apply them, and greatly increased computer power to allow studies with the necessary reliability to be performed. Our review focuses on applications and protocols, with the main emphasis on critical analysis of recent studies where docking calculations and molecular dynamics (MD) simulations were combined to dock small molecules into protein receptors. We highlight successes to demonstrate what is possible now, but also point out drawbacks and future directions. The review is structured to lead the reader from the simpler to more compute-intensive methods. Thus, while inexpensive and fast docking algorithms can be used to scan large compound libraries and reduce their size, more accurate but expensive MD simulations can be applied when a few selected ligand candidates remain. MD simulations can be used: during the preparation of the protein receptor before docking, to optimize its structure and account for protein flexibility; for the refinement of docked complexes, to include solvent effects and account for induced fit; to calculate binding free energies, to provide an accurate ranking of the potential ligands; and in the latest developments, during the docking process itself to find the binding site and correctly dock the ligand a priori.

Computer Simulation↗

PubMed2026

Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.

BACKGROUND: Stenotrophomonas maltophilia is a multidrug-resistant opportunistic pathogen causing severe hospital-acquired infections, especially in immunocompromised patients. The absence of an effective vaccine and rising antibiotic resistance underscore the need for novel interventions. This study employed an integrated reverse vaccinology and computational analyses to identify new immunogenic targets, design a multi-epitope vaccine (MEV), and propose potential drug targets. METHODS: A comprehensive immunoinformatics pipeline was employed to assess antigenicity, allergenicity, human similarity, and physicochemical properties of S. maltophilia proteins. Both B- and T-cell epitopes were screened; however, only the top B-cell epitopes were selected for MEV construction, given the extracellular nature of S. maltophilia. MEV-TLR interactions were analyzed through molecular docking and dynamics simulations. In parallel, cytoplasmic proteins were screened via a subtractive genomics approach to identify essential, non-human homologous, and non-microbiome-similar proteins, which were further evaluated for druggability and interaction networks to propose novel therapeutic targets. RESULTS: From a total of 4111 proteins, seven potential immunogenic targets were identified: GspD (WP_108270537.1), FhuE (WP_049451370.1), fimbrial protein (WP_012479122.1), TonB-dependent receptor (WP_169448402.1), TolC family protein (WP_108270106.1), autotransporter beta-barrel OMP (WP_169448945.1), and a hypothetical protein (WP_005407892.1). Subsequently, an MEV was designed using five immunogenic epitopes derived from four of these targets: WP_005407892.1 (ADQDSSNM), WP_049451370.1 (SGKAEQ and GEESKTPS), WP_108270537.1 (GVTSTQSDSERT), and WP_169448945.1 (RELGGDRNE). Molecular docking and molecular dynamics simulations demonstrated strong, stable, and feasible interactions between the MEV and TLR-2 and TLR-4 receptors. Moreover, nine novel drug targets were predicted for S. maltophilia, providing new therapeutic insights. CONCLUSION: The designed MEV and identified immunogenic targets represent promising vaccine candidates against S. maltophilia. Further in vitro and in vivo studies are essential to confirm their safety, immunogenicity, and protective efficacy. Additionally, subtractive genomics analysis revealed nine novel, non-homologous drug targets, offering safer and more specific therapeutic avenues.

Drug targets↗

PubMed2025

Genetic targets related to aging for the treatment of coronary artery disease.

BACKGROUND: Coronary Artery Disease (CAD) is the most common cardiovascular disease worldwide, threatening human health, quality of life and longevity. Aging is a dominant risk factor for CAD. This study aims to investigate the potential mechanisms of aging-related genes and CAD, and to make molecular drug predictions that will contribute to the diagnosis and treatment. METHODS: We downloaded the gene expression profile of circulating leukocytes in CAD patients (GSE12288) from Gene Expression Omnibus database, obtained differentially expressed aging genes through "limma" package and GenaCards database, and tested their biological functions. Further screening of aging related characteristic genes (ARCGs) using least absolute shrinkage and selection operator and random forest, generating nomogram charts and ROC curves for evaluating diagnostic efficacy. Immune cells were estimated by ssGSEA, and then combine ARCGs with immune cells and clinical indicators based on Pearson correlation analysis. Unsupervised cluster analysis was used to construct molecular clusters based on ARCGs and to assess functional characteristics between clusters. The DSigDB database was employed to explore the potential targeted drugs of ARCGs, and the molecular docking was carried out through Autodock Vina. Finally, single-cell data (GSE159677) of arterial intima was used to further explore the expression of aging signature genes in different cell subpopulations. RESULTS: We identified 8 ARCGs associated with CAD, in which HIF1A and FGFR3 were up while NOX4, TCF7L2, HK3, CDK18, TFAP4, and ITPK1 were down in CAD patients. Based on this, CAD patients can be divided into two molecular clusters, among which cluster A mainly involves functional pathways such as ECM receptor interaction and focal adhesion; cluster B mainly involves functional pathways such as amimo sugar and nucleotide sugar metabolism and pyrimidine metabolism. In addition, the molecular docking results showed that retinoic acid and resveratrol had good binding affinity with targets genes. Further single-cell analysis results showed that NOX4, TCF7L2, ITPK1, and HIF1A were specifically expressed in different types of cells in atherosclerotic tissues. CONCLUSION: Our study identified several ARCGs that may be involved in the pathogenesis and progression of CAD. Further, retinoic acid and resveratrol were potential candidate molecule drugs for inhibiting these targets.

Humans↗

PubMed2001

Improving the selectivity of HAV-peptides in modulating E-cadherin-E-cadherin interactions in the intercellular junction of MDCK cell monolayers.

PURPOSE: The objective of this work is to understand the sequence specificity of HAV peptides and to improve their selectivity in regulating E-cadherin-E-cadherin interactions in the intercellular junctions. METHODS: Peptide 1 was modified using an alanine scanning method to give peptides 2-6. The ability of these peptides to modulate intercellular junctions was evaluated using Madin-Darby Canine Kidney (MDCK) cell monolayers on Transwell membranes from either the apical (AP) or the basolateral (BL) side. Modulation of the intercellular junctions was measured by the ability to lower the transepithelial electrical resistance (TEER) of MDCK monolayers and by the increase in mannitol flux. Molecular docking experiments were performed to model the binding properties of these peptides to the EC1 domain of E-cadherin. RESULTS: Peptides 5 (Ac-SHAVAS-NH2) and 6 (Ac-SHAVSA-NH2) were found to be more effective than the parent peptide 1 in decreasing the resistance of the cell monolayer. Furthermore, comparative studies with the control and the weak inhibitor peptide 2 indicate that peptide 5 displayed a significant increase in mannitol flux. Molecular docking of peptides 1, 2 and 5 to the EC1 domain suggests that peptide 5 has the lowest binding energy. CONCLUSIONS: HAV peptides have the ability to modulate E-cadherin-E-cadherin interactions in the intercellular junctions of the MDCK cell monolayer, thus indirectly increasing the permeability of the tight junctions. This observation indicates that residues flanking the HAV sequence are important in the binding selectivity of HAV peptides to E-cadherin. Molecular docking can further aid in the design of peptides with better selectivity to the EC1 domain of E-cadherin.

Alanine↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2006

Scoring functions for protein-ligand docking.

Virtual screening by molecular docking has become established as a method for drug lead discovery and optimization. All docking algorithms make use of a scoring function in combination with a method of search. Two theoretical aspects of scoring function performance dominate operational performance. The first is the degree to which a scoring function has a global extremum within the ligand pose landscape at the proper location. The second is the degree to which the magnitude of the function at the extremum is accurate. Presuming adequate search strategies, a scoring function's location performance will dominate behavior with respect to docking accuracy: the degree to which a predicted pose of a ligand matches experimental observation. A scoring function's magnitude performance will dominate behavior with respect to screening utility: enrichment of true ligands over non-ligands. Magnitude estimation also controls pure scoring accuracy: the degree to which bona fide ligands of a particular protein may be correctly ranked. Approaches to the development of scoring functions have varied widely, with a number of functions yielding similarly high levels of performance relating to the location issue. However, even among functions performing equally well on location, widely varying performance is observed on the question of magnitude. In many cases, performance is good enough to yield high enrichments of true ligands versus non-ligands in screening across a wide variety of protein types. Generally, performance is not good enough to correctly rank among true ligands. Strategies for improvement are discussed.

Animals↗

PubMed2025

Computational identification of potential antifungal targets against Claviceps purpurea via MD simulation and MM/GBSA.

Ergot alkaloids produced by the fungus Claviceps purpurea pose significant risks to agriculture and human health. This study systematically investigates the pathogenicity of C. purpurea, analyzing five strains for their proteomic profiles, which revealed genetic variability in size and GC content. We identified proteins localized in various cellular compartments, contributing to our understanding of essential cellular processes. A focus on potential drug targets led to the identification of Alpha-N-acetylglucosaminidase, a hydrolase with significant mass and functional relevance, despite not matching a UniProt entry. The 3D structure prediction confirmed its integrity, making it a suitable target for further analysis. Molecular docking identified ligands CID:51,535,944 and CID:145,242,255 with strong binding affinities to Alpha-N-acetylglucosaminidase, highlighting interactions with key residues like TRP138, ARG651. Molecular docking interactions were validated and showed consistency through MD simulation analyses with greater RMSD, RMSF and PL contacts. This research enhances our understanding of C. purpurea, offering insights into its genetic diversity and cellular mechanisms while identifying promising therapeutic targets. The findings contribute to strategies for mitigating the economic and health impacts of C. purpurea infections, paving the way for innovative interventions in sustainable agriculture.

Molecular Docking Simulation↗

PubMed2026

Proteomic regulation of anti-proliferative and anti-migratory activity by potent phytochemicals from Pistacia integerrima J.L. Steward Ex Brandis via PI3K, AKT1, and KRAS for Lung Cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of mortality worldwide and remains a major therapeutic challenge due to high metastasis, drug resistance and limited treatments. Pistacia integerrima J.L. Steward Ex Brandis (PI) consists of flavonoids, steroids, terpenoids and phenolic compounds reported for pharmacological activities. The efficacy of potent bioactives from P. integerrima may be ascertained employing cytotoxic, antiproliferative, anti-migratory, and anti-metastatic evaluations in A549 NSCLC cells with proteomic profiling, molecular docking, and dynamics simulation study. METHODS AND RESULTS: PI EtAc produced significant dose-dependent cytotoxicity in A549 cells (100 µg/mL, p < 0.0001 in the MTT assay. There was a pronounced decrease in colony formation after treatment with EtAc, with 18.41% (p < 0.002), and markedly. Furthermore. PI EtAC markedly inhibited cell migration emphasized by wound healing and Transwell migration (p < 0.01) assays, indicating reduced metastatic migratory potential. Proteomic analysis demonstrated significant downregulation of Endoglin (CD105), KLK5 and MMP-2, indicating suppression of angiogenic and metastatic signalling pathways in the Human XL Oncology protein array. The interaction of major PI phytochemicals with key NSCLC-associated targets was recorded in Molecular docking, revealing favourable binding affinities of kaempferol, β- sitosterol, luteolin, and quercetin towards several oncogenic targets, including AKT1(- 7.6 kcal/mol), PI3K(- 9.4 kcal/mol), KRAS (- 8.5 kcal/mol) and MMP9 (- 8.1 kcal/mol). Molecular dynamics simulation confirmed the structural stability of the kaempferol -AKT1 complex throughout the 100 ns simulation. CONCLUSION: Pistacia integerrima bioactives exhibited significant anti-proliferative, anti-migratory, and anti-metastatic activities in vitro, which may provide scientific rationale identifying newer promising candidates for NSCLC.

Humans↗

PubMed2025

Mechanisms of Baishao () and Gancao () on major depressive disorder: network pharmacology and o validation.

OBJECTIVE: To elucidate the potential molecular mechanisms of Baishao (Radix Paeoniae Alba) (APR) and Gancao (Radix Glycyrrhizae) (GR) in the treatment of major depressive disorder (MDD). METHODS: Based on the network pharmacology strategy, the therapeutic targets of APR-GR for MDD are predicted, differentially expressed genes from the Integrated Gene Expression database for MDD patients. Topological networks are constructed, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways are enriched, their pharmacological potential molecular mechanisms are discussed, and molecular docking analysis is performed to further motivate compositional and target interactions. Finally, the CUMS mouse model is used for validation. RESULTS: Based on the pharmacological network analysis, 17 candidate genes were identified, including muscarinic acetylcholine receptor M1(CHRM1), muscarinic acetylcholine receptor M2 (CHRM2), β2-adrenergic receptor (ADRB2), adrenergic α1A receptor (ADRA1A) and 5-hydroxytryptamine transfer protein (SLC6A4), etc. which are primarily involved in reactive oxygen species metabolism, neural response, oxidative stress response and other biological processes. Further analysis revealed that these targets are closely related to Ca2+, cyclic adenosine monophosphate, etc., and exhibit optimal binding sites after molecular docking. Finally, in vivo experiments were performed and it was found that APR-GR significantly improved depression-like behavior and hippocampal impairment in mouse models, increasing brain levels of 5-hydroxytryptamine, dopamine and norepinephrine and decreasing serum levels of corticotropin releasing hormone, corticosterone and adreno cortico tropic hormone, while upregulating the expression of CHRM1, CHRM2 and ADRA1A in the hippocampus and downregulating the expression of SLC6A4 and ADRB2. CNCLUSION: This research sheds light on the potential molecular mechanism of APR-GR to improve MDD.

Major Depressive Disorder↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

TCGA-based identification of prognostic biomarkers and candidate traditional Chinese medicine compounds in papillary thyroid carcinoma: An observational study.

This study aimed to identify prognostic genes associated with papillary thyroid carcinoma (PTC) and explore candidate traditional Chinese medicine (TCM) compounds using integrated bioinformatics and molecular docking. In this observational study, PTC gene expression profiles and clinical data were obtained from The Cancer Genome Atlas. Differentially expressed genes were screened using differential-expression sequencing (DESeq2), followed by protein-protein interaction network analysis to identify hub genes. Their expression, diagnostic value, immune relevance, prognostic significance, protein-level validation, and single-cell distribution were assessed using gene expression profiling interactive analysis, receiver operating characteristic analysis, immune infiltration analysis, Kaplan-Meier survival analysis, the human protein atlas, and single-cell RNA-sequencing data. Candidate TCM compounds were predicted using symptom mapping (SymMap) and the TCM Systems Pharmacology Database and Analysis Platform, and molecular docking was performed to evaluate potential ligand-target interactions. Five hub genes, colony-stimulating factor 2, apolipoprotein E, fibronectin 1 (FN1), collagen type I alpha 1 chain (COL1A1), and intercellular adhesion molecule 1, were identified and found to be significantly upregulated in PTC tissues, with diagnostic value in receiver operating characteristic analysis. Immune infiltration analysis showed associations with macrophages, dendritic cells, and T helper 1 cells, whereas single-cell analysis demonstrated heterogeneous expression across immune and stromal cell populations, including fibroblasts. Higher FN1 and COL1A1 expression was associated with poorer outcomes. Immunohistochemistry supported the expression patterns, while single-cell analysis provided exploratory cell-type-level context for the cellular distribution of selected genes. Ginseng and Smilax glabra were predicted as common candidate TCMs, and docking suggested favorable binding between their active compounds and selected hub targets. Colony-stimulating factor 2, apolipoprotein E, FN1, COL1A1, and intercellular adhesion molecule 1 may be biologically relevant hub genes in PTC, while FN1 and COL1A1 may have prognostic value. Predicted TCM compounds provide preliminary computational evidence for possible compound-target interactions, requiring experimental and clinical validation.

Female↗