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PubMed2026

The Mechanism of Celosiae Semen in the Treatment of Diabetic Cataract: Based on Network Pharmacology.

INTRODUCTION: Diabetes mellitus can be complicated by a variety of ocular diseases, among which the postoperative complications of diabetic cataract (DC) are significantly higher than those of non-DC patients. Therefore, finding drugs with natural active ingredients is an urgent challenge in the prevention and treatment of DC. Discovering the potential molecular mechanism of celosiae semen (CS) for the treatment of DC and providing new ideas and programs for the treatment and prevention of DC. METHODS: In this study, network pharmacology, molecular docking, and molecular dynamics simulations were utilized to predict the binding and functional enrichment of the main active ingredients of CS with DC-related targets, and to explore the potential pathways and mechanisms of CS for the treatment of DC. RESULTS: Through database searching and screening, a total of 45 potential targets of CS for the treatment of DC were identified, functionally enriched, and a protein-protein interaction network was constructed, and the key target, SRC, was finally found. The results of molecular docking and molecular dynamics simulation showed that the main active ingredient of CS, stigmasterol, could bind stably to the key target SRC protein. DISCUSSION: This study not only elucidates the phyto-pharmacological basis of CS in DC management but also provides a framework for developing natural product-derived targeted therapies against diabetic ocular complications. The integration of modern genomics and computational chemistry to deconstruct the therapeutic effects of traditional Chinese herbal medicines has great clinical significance in expanding the scope of traditional Chinese medicines for the treatment of DC and promoting precision targeting. However, this requires verification through basic experiments. CONCLUSION: These computational findings suggest that CS may exert its anti-cataract effects through the multi-target modulation of diabetic metabolic pathways and SRC-mediated signaling cascades.

Humans↗

PubMed2026

In silico screening of anti-atherosclerotic compounds from Morus alba leaves by machine learning and network pharmacology.

OBJECTIVE: This study integrates machine learning with network pharmacology, molecular docking, and molecular dynamics simulations to screen bioactive compounds from Mulberry leaves and elucidate their potential mechanisms against atherosclerosis (AS). METHODS: A training dataset of anti-AS active compounds was compiled and encoded as Morgan fingerprints. Three machine learning classifiers, specifically Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XG-Boost), were constructed and evaluated using multiple performance metrics. Potential active components from Mulberry leaves and AS-related targets were retrieved, followed by protein-protein interaction network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was then performed to evaluate binding affinities between core targets and candidate compounds, and the most stable complex was subjected to molecular dynamics simulations using GROMACS (2025). RESULTS: The RF model achieved superior performance (accuracy= 0.8354, F1 = 0.8408, AUC = 0.9119) with 100% external validation accuracy. Thirteen anti-AS candidates were prioritized from mulberry leaves, four of which have been previously documented. Network pharmacology revealed AKT1 and IL6 as core targets, enriched in pathways such as endocrine resistance. Molecular docking and dynamics simulations confirmed strong binding between oxysanguinarine and AKT1, with the complex exhibiting high stability. CONCLUSION: The RF model provides a reliable computational tool for prioritizing anti-AS compounds from Mulberry leaves. The integrated analysis reveals that Mulberry leaves exert anti-atherosclerotic effects through multi-target (e.g., AKT1, IL6) and multi-pathway (e.g., PI3K-Akt) mechanisms, offering a framework for further experimental validation.

Morus↗

PubMed2026

Mechanism of Action of Hedyotis diffusa Extract in a Rat Model of Acute Lung Injury Based on Transcriptomic Analysis.

OBJECTIVE: This study established a rat model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) to evaluate pathological damage, collagen deposition, inflammatory cytokine levels, and key gene/protein expression following Hedyotis diffusa water extract (HDWE) intervention. Combined with ultra-high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS), transcriptomic analysis, and molecular simulation, this study identified the bioactive components of HDWE, evaluated their potential interactions with ALI-related targets, and explored the multi-omics-based protective mechanisms of HDWE. METHODS: Thirty-six Sprague-Dawley (SD) rats were randomly divided into six groups: Control group, ALI group, DXMS group, HDWE-L group (100 mg/kg), HDWE-M group (200 mg/kg), and HDWE-H group (300 mg/kg). Hematoxylin and eosin (H&E) and Masson's trichrome staining were used to evaluate lung pathological changes and collagen deposition. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum tumor necrosis factor-α TNF-α interleukin-1β IL-1β, erleukin-6 (IL-6), and interleukin-10 (IL-10) levels. Transcriptomic analysis identified differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), receiver operating characteristic (ROC), and immune infiltration analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) detected the mRNA expression levels of SPHK1, RELA, and NFKBIA. Immunohistochemistry evaluated the expression of eight hub targets, including endothelin-1 (EDN1), sphingosine kinase 1 (SPHK1), intercellular adhesion molecule 1 (ICAM1), interleukin-17 (IL-17), prostaglandin-endoperoxide synthase 2 (PTGS2/COX-2), NF-κB p65 (encoded by RELA), WT1-associated protein (WTAP), and myeloperoxidase (MPO). UHPLC-Q-Orbitrap HRMS characterized HDWE constituents. Molecular docking analysis was performed between 22 compounds and eight hub targets, followed by 100 ns molecular dynamics simulations and molecular mechanics-Poisson-Boltzmann surface area (MM/PBSA) binding free energy calculations for five core targets. Compared with the control group, the ALI group showed increased levels of TNF-α (86%), IL-1β (107%), and IL-6 (66%), accompanied by a 43% reduction in IL-10 and a 300% increase in lung collagen deposition. All HDWE doses alleviated inflammatory responses, with medium-dose HDWE showing the most pronounced effects. Specifically, medium-dose HDWE increased IL-10 levels by 52% and reduced IL-6, TNF-α, and IL-1β levels by 18%, 22%, and 11%, respectively. Transcriptomic analysis identified 2512 DEGs between the control group and ALI groups, 832 exclusive DEGs between the ALI group and HDWE-M groups, and 876 overlapping DEGs enriched in TNF, IL-17, and NF-κB signaling pathways. The eight-hub-gene diagnostic model achieved an area under the curve (AUC) of 0.969. RELA, SPHK1, and four other hub genes showed positive correlations with Th1, Th17, and neutrophil infiltration. In the ALI group, SPHK1, RELA, and NFKBIA mRNA expression levels were 1.30-, 0.96-, and 0.71-fold of those in the control group, respectively. Compared with the ALI group, high-dose HDWE treatment and low-dose HDWE treatment reduced SPHK1 expression to 0.62- and 0.57-fold, respectively, and increased NFKBIA expression to 1.68- and 1.58-fold, respectively. High-dose HDWE treatment reduced RELA expression to 0.43-fold. The expression levels of inflammation-related proteins were increased in the ALI group and were reduced after HDWE treatment. Twenty-two HDWE components were identified, 16 of which met the docking criteria. Asperulosidic acid exhibited favorable predicted binding affinities with all eight targets, with calculated binding free energies of -14.74, -14.92, -17.58, -23.04, and -16.10 kcal/mol for MPO, IL-17, NF-κB p65, PTGS2/COX-2, and SPHK1, respectively. CONCLUSIONS: This study provides systematic in vivo pharmacodynamic and in silico component-target evidence regarding the protective effects of HDWE against LPS-induced ALI. HDWE treatment increased NFKBIA expression and reduced SPHK1, RELA, and multiple inflammatory protein levels, suggesting that HDWE may regulate the IL-17/NF-κB-associated inflammatory network, although direct causal relationships require further validation. Asperulosidic acid may represent a key bioactive component with broad target-binding potential. This study was limited by the use of an LPS-induced rat ALI model without gene knockout or target inhibitor validation; therefore, further functional experiments are required to confirm the proposed regulatory mechanisms.

Hedyotis diffusa↗

PubMedDate not supplied

Modelling the dynamics of an antigenic peptide using NMR relaxation data.

The internal dynamics of a cyclic peptide which was designed to mimic an antigenic loop of the haemagglutinin, is studied through heteronuclear relaxation along the 13C alpha-1H alpha vectors and through homonuclear relaxation along the 1H alpha-1HN and 1H beta-1H beta' vectors. Order parameters are extracted from the longitudinal and cross-relaxation data. Molecular dynamics simulations are performed and the order parameters are calculated in different ways from the trajectories. The simulation, which is performed in vacuo, gives smaller order parameters (vector motions of larger amplitude) than the experimental results. However, the general features of the experimental order parameters are reproduced by the molecular dynamics simulation. The flexibility of the molecule can then be investigated from the results of the molecular dynamics. It shows that the mobility observed through the order parameters is due to motions in flanking regions, remote from the observed vectors.

Amino Acid Sequence↗

PubMed2026

Zhiling Jiangya decoction treats hypertension in rats: An integrative study of network pharmacology, immune infiltration, molecular simulation, and 16S rDNA sequencing.

OBJECTIVE: This study integrated network pharmacology, immune infiltration analysis, molecular docking, molecular dynamics simulation, ADMET prediction, 16S rDNA sequencing, and rat experiments to elucidate the potential mechanisms underlying the antihypertensive effects of Zhiling Jiangya Decoction (ZLJYD). METHODS: Active compounds and their potential targets were screened from the PubChem, TCMSP, NovoPro, and SwissTargetPrediction databases. Hypertension-related targets were retrieved from the OMIM and GeneCards databases, and overlapping targets were identified. The STRING database and Cytoscape 3.10.1 software were used to construct a protein-protein interaction network and a herb-component-target-disease network. Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the key biological processes and signaling pathways involved. Using the CIBERSORT algorithm combined with correlation analysis, we investigated the association between key targets and immune cell infiltration. Molecular docking, molecular dynamics simulations, and ADMET predictions were performed to assess the binding stability and pharmacokinetic properties of the main compounds with their corresponding targets. Finally, the antihypertensive efficacy of ZLJYD was validated using a spontaneously hypertensive rat model, and alterations in gut microbiota were analyzed using 16S rDNA sequencing. RESULTS: A total of 123 active compounds and 267 hypertension-related targets of ZLJYD were identified. Enrichment analysis revealed that these targets were primarily associated with the PI3K-Akt signaling pathway and lipid and atherosclerosis pathways. Immune infiltration analysis suggested that the therapeutic effects of ZLJYD may involve the regulation of follicular helper T cells, naïve B cells, and naïve CD4⁺ T cells. Molecular docking and dynamics simulations supported the stable binding of key compounds to their target proteins, while ADMET predictions indicated favorable pharmacokinetic properties and safety profiles. Rat experiments demonstrated that ZLJYD significantly reduced blood pressure in spontaneously hypertensive rats, partially alleviated gut microbiota dysbiosis, and altered microbial community structure and phylogenetic diversity. CONCLUSION: This study systematically elucidates the potential mechanisms underlying the antihypertensive effects of ZLJYD through multiple components, targets, and pathways, particularly immune regulation and gut microbiota remodeling. These findings provide mechanistic insights into its potential therapeutic application.

16S rDNA sequencing↗

PubMed2026

Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.

PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, this study aimed to clarify their association, identify the toxic targets of DEHP, and elucidate the underlying molecular mechanisms. METHODS: Multiple integrated approaches were employed, including Gene Expression Omnibus (GEO) data analysis, network toxicology, molecular docking, and machine learning. STRING and Cytoscape tools were utilized to identify key targets, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functional enrichment of intersecting targets. Machine learning and SHAP analysis were applied to screen core targets in GC. Molecular docking was performed to evaluate the binding affinity of DEHP toward core targets, and 200 ns molecular dynamics simulations were further conducted for representative complexes to validate their dynamic stability. RESULTS: A total of 18 key targets were identified using STRING and Cytoscape. GO and KEGG enrichment analyses demonstrated that these intersecting targets were primarily enriched in the extracellular region, as well as the Calcium signaling pathway and cAMP signaling pathway. Through machine learning analyses, 7 key genes (ADRB2, ESRRG, GRIA4, IL13RA2, NR3C2, PLA2G1B, and SULT2A1) were identified as core targets in GC through machine learning analyses. Molecular docking simulations revealed strong binding specificity between DEHP and the target proteins. Among them, NR3C2 and ADRB2 exhibited relatively high predictive importance in the machine learning models. DEHP showed favorable binding affinity toward these core targets, and molecular dynamics simulations further confirmed that ADRB2-DEHP and NR3C2-DEHP complexes maintained stable conformations throughout the simulation. CONCLUSIONS: Our findings identified GC associated genes that were computationally predicted as potential targets of DEHP. These results indicated structural compatibility between DEHP and its target proteins but did not prove that DEHP exposure accounts for the gene expression changes in GC.

Molecular Docking Simulation↗

PubMed1992

Homology modeling of a heme protein, lignin peroxidase, from the crystal structure of cytochrome c peroxidase.

A 3-dimensional model of lignin peroxidase (LiP) was constructed based on its sequence homology with other peroxidases, particularly cytochrome c peroxidase, the only protein with a known crystal structure in the peroxidase family. The construction of initial conformations of insertions and deletions was assisted by secondary structure predictions, amphipathic helix predictions, and consideration of the specific protein environment. A succession of molecular dynamics simulations of these regions with surrounding residues as constraints were carried out to relax the bond lengths and angles. Full protein molecular dynamics simulations with explicit consideration of bound waters were performed to relax the geometry and to identify dynamically flexible regions of the successive models for further refinement. Among the important functionally relevant structural features predicted are: (i) four disulfide bonds are predicted to be formed between Cys3 and Cys15, Cys14 and Cys285, Cys34 and Cys120 and Cys249 and Cys317; (ii) a glycosylation site, Asn257, was located on the surface; (iii) Glu40 was predicted to form a salt bridge with Arg43 on the distal side of the heme and was considered as a possible origin for the pH dependence of compound I formation; and (iv) two candidate substrate binding sites with a cluster of surface aromatic residues and flexible backbones were found in the refined model, consistent with the nature of known substrates of LiP. Based on these predicted structural features of the model, further theoretical and experimental studies are proposed to continue to elucidate the structure and function of LiP.

Amino Acid Sequence↗

PubMed2025

Unveiling novel antimicrobial peptides from the ruminant gastrointestinal microbiomes: A deep learning-driven approach yields an anti-MRSA candidate.

INTRODUCTION: Antimicrobial peptides (AMPs) present a promising avenue to combat the growing threat of antibiotic resistance. The ruminant gastrointestinal microbiome serves as a unique ecosystem that offers untapped potential for AMP discovery. OBJECTIVES: The aims of this study are to develop an effective methodology for the identification of novel AMPs from ruminant gastrointestinal microbiomes, followed by evaluating their antimicrobial efficacy and elucidating the mechanisms underlying their activity. METHODS: We developed a deep learning-based model to identify AMP candidates from a dataset comprising 120 metagenomes and 10,373 metagenome-assembled genomes derived from the ruminant gastrointestinal tract. Both in vivo and in vitro experiments were performed to examine and validate the antimicrobial activities of the AMP candidates that were selected through bioinformatic analysis and subsequently synthesized chemically. Additionally, molecular dynamics simulations were conducted to explore the action mechanism of the most potent AMP candidate. RESULTS: The deep learning model identified 27,192 potential secretory AMP candidates. Following bioinformatic analysis, 39 candidates were synthesized and tested. Remarkably, all synthesized peptides demonstrated antimicrobial activity against Staphylococcus aureus, with 79.5% showing effectiveness against multiple pathogens. Notably, Peptide 4, which exhibited the highest antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA), confirmed this effect in a mouse model with wound infection, exhibiting a low propensity for resistance development and minimal cytotoxicity and hemolysis towards mammalian cells. Molecular dynamics simulations provided insights into the mechanism of Peptide 4, primarily its ability to disrupt bacterial cell membranes, leading to cell death. CONCLUSION: This study highlights the power of combining deep learning with microbiome research to uncover novel therapeutic candidates, paving the way for the development of next-generation antimicrobials like Peptide 4 to combat the growing threat of MRSA would infections. It also underscores the value of utilizing ruminant microbial resources.

Animals↗

PubMed2026

Activity of natural single nucleotide variants of human alkyladenine DNA glycosylase AAG R145H, G163S and R197C involved in DNA binding.

Alkyladenine DNA glycosylase (AAG) is a critical enzyme in the base excision repair (BER) pathway that safeguards genome integrity by removing structurally diverse alkylated and deaminated purine lesions from DNA. It serves as a primary defense against alkylation-induced mutations, which are linked to cancer development, chronic inflammation, and neurodegenerative diseases. Single nucleotide variants (SNVs) in the gene coding region have the potential to alter the enzyme's functionality, potentially modulating the repair capacity and affecting response and prognosis following chemoradiotherapy. In our study, we investigated three SNVs that lead to amino acid class changes in regions involved in DNA substrate coordination: R145H, G163S, and R197C using an in vitro approach. Using biochemical assays and molecular dynamics simulations, we evaluated the thermal stability, DNA binding affinity, and glycosylase activity of AAG variants toward hypoxanthine (Hx) and 1,N6-ethenoadenosine (εA) containing substrates. The G163S variant showed reduced thermal stability due to the conformational strain in the β-hairpin loop that intercalates in DNA, but retained εA excision activity comparable to that of wild-type AAG, while losing activity against Hx-containing DNA. The R197C variant had a four-fold reduction in DNA binding affinity for both substrates, and was catalytically inactive, unable to excise either damaged bases. This loss of function correlated with the rearrangement of the 201-210 loop and the reorientation of Arg-201 and Arg-207, which disrupts critical DNA contacts. However, the R145H variant retained near-wild-type thermal stability and activity on both substrates, despite bioinformatic predictions of deleterious effect. Molecular dynamics simulations revealed variant-specific structural disruptions. The data obtained underscore the importance of experimental validation in assessing the functional impact SNVs.

DNA Glycosylases↗

PubMed1992

Binding of an antiviral agent to a sensitive and a resistant human rhinovirus. Computer simulation studies with sampling of amino acid side-chain conformations. II. Calculation of free-energy differences by thermodynamic integration.

Thermodynamic-cycle perturbation theory and molecular dynamics simulations were used to calculate the difference in the free energy of binding of the antiviral compound WIN53338 to the wild-type human rhinovirus 14 and to a drug-resistant mutant of the virus in which valine 188 of the viral protein 1 is mutated to leucine. Because of the difficulty of achieving adequate sampling of all of the rotational isomers of amino acid side-chains in molecular dynamics simulations, an explicit treatment of the effects of the existence of multiple rotational isomers of residue 188 on the calculated free energies was used. The rotamers of residue 188 were first mapped by steric and energetic techniques as described in the accompanying article. Thermodynamic integration was then carried out during simulations of the virus, both with and without the antiviral compound bound, by mutating residue 188 while restraining its side-chain to one conformation. The contributions of the other rotamers of residue 188 to the free-energy changes for this mutation were then added to those calculated by thermodynamic integration as correction factors. Binding of WIN53338 to the wild-type virus was calculated to be favored over binding to the mutant virus by 1.7(+/- 3.0) kcal/mol. This is consistent with experimental data which, if differences in activity are assumed to be due to differences in binding, indicate that the binding affinity of WIN53338 for the wild-type virus is at least 0.15 to 1.7 kcal/mol greater than for the mutant virus. Thermodynamic integration was also performed in the conventional manner without restraints and was found to give less accurate results.

Antiviral Agents↗

PubMed1992

Binding of an antiviral agent to a sensitive and a resistant human rhinovirus. Computer simulation studies with sampling of amino acid side-chain conformation. I. Mapping the rotamers of residue 188 of viral protein 1.

The mutation of valine 188 to leucine in the viral protein 1 of human rhinovirus 14 renders the virus resistant to certain antiviral compounds. Thermodynamic-cycle perturbation theory provides a means of calculating the difference in the binding free energies of an antiviral compound to the wild-type virus and to the mutant virus. In calculating the relevant free-energy differences in molecular dynamics simulations, it is important to sample the multiple rotational isomers of residue 188 correctly. In general, these rotamers will not be fully sampled during a single molecular dynamics simulation. However, the contributions of all the rotamers to the free-energy differences associated with mutation of residue 188 may be considered explicitly once they have been identified and their relative free energies determined. Therefore, we describe here the mapping of the rotamers of residue 188 by steric-bump search and energy minimization techniques, and by the computation of potentials of mean force (p.m.f.s.) using umbrella sampling. The usefulness, validity and efficiency of these methods of examining rotameric states is discussed. Adiabatic mapping by energy minimization was found to be unreliable for this residue due to the small magnitude of its interactions with the surrounding protein atoms. Ambiguities in the adiabatic maps were resolved by computing p.m.f.s. The p.m.f. for valine 188 in the unliganded wild-type virus shows a minimum corresponding to the crystallographically observed conformation of valine 188. The p.m.f.s. for valine 188 in the liganded virus and for leucine 188 in the unliganded mutant virus suggest that the experimentally observed conformations may be interpreted as averages of a number of conformations corresponding to those at the minima in the p.m.f.s. The calculations suggest also that the conformation of leucine 188 may change when the ligand binds. The use of the calculated p.m.f.s. to compute the difference in the free energy of binding of an antiviral compound to the wild-type and mutant rhinoviruses is described in the accompanying article.

Antiviral Agents↗

PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗

PubMed1992

Molecular dynamics study of a complex between the human histocompatibility antigen HLA-A2 and the IMP58-66 nonapeptide from influenza virus matrix protein.

The structure of the influenza-virus-matrix-protein (IMP) 58-66 nonapeptide, bound to the major-histocompatibility-complex-encoded human leukocyte antigen (HLA) A2 protein was studied by molecular dynamics simulation. Starting from the extra electron density map of peptides co-crystallized with HLA-A2, the nonapeptide IMP58-66 was docked residue by residue in the protein binding cleft. The complex was simulated for 100 ps in a shell of 1372 water molecules. The averaged simulated HLA-A2 conformation was found to be similar to the crystal structure (0.182 nm RMS deviation, for the backbone atoms of the alpha 1-alpha 2 domain). Nine out of the 14 hydrogen bonds observed in the antigen-binding site were reproduced in the simulation. The IMP58-66 peptide exhibits an extended conformation with kinks at positions 3 and 5. The side chains of residues 2, 3 and 9 develop van der Waals' interactions with hydrophobic pockets of HLA-A2, corresponding to polymorphic residues of the major-histocompatibility-complex-encoded proteins. Both the N-terminus and C-terminus of the nonapeptide were anchored in the antigen-binding groove by hydrogen bonds with conserved amino acids. The N-terminus was more flexible and contacts four HLA-A2 conserved tyrosines (Tyr7, Tyr59, Tyr159 and Tyr171) and Glu63 by direct or water-relayed hydrogen bonds. Water intercalation occurred only around the N-terminus of the peptide, the C-terminal carboxylate forming strong hydrogen bonds with polar residues (Tyr84 and Thr143) and a salt bridge with Lys146 all over the molecular dynamics simulation. This model is fully compatible with the recently published crystal structure of the HLA-B27 protein, complexed by a mixture of self nonapeptides.

Amino Acid Sequence↗

PubMed2026

Matrine Alleviates Sepsis-Induced Acute Lung Injury by Reinforcing NQO1/SLC7A11/GPX4-Associated Anti-Ferroptotic Defenses and Attenuating NF-κB-Driven Inflammation.

BACKGROUND: Sepsis triggers dysregulated systemic inflammation and multiple-organ dysfunction, with the lungs being particularly susceptible to injury. Sepsis-induced acute respiratory distress syndrome (ARDS) is mainly driven by TLR4/NF-κB-mediated hyperinflammation and alveolar macrophage activation. Matrine, a bioactive alkaloid derived from Sophora flavescens, has been reported to modulate redox homeostasis and ferroptosis-associated lipid peroxidation. However, the target-specific mechanisms underlying its effects on ferroptosis and inflammatory signaling in sepsis-induced acute lung injury (SALI) remain incompletely understood. PURPOSE: This study aimed to evaluate the therapeutic effects of matrine in a cecal ligation and puncture (CLP)-induced SALI model and to determine whether its protective effects involve reinforcement of NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses and suppression of NF-κB-driven inflammation. METHODS: We analyzed the single-cell RNA-sequencing (scRNA-seq) dataset GSE273924 to characterize CD45-enriched pulmonary immune-cell subsets in sham mice and mice with intratracheal Escherichia coli-induced pneumonia. Network pharmacology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict Kushen (KS)-related targets and pathways associated with SALI. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) of GSE245013 were used to identify candidate targets. Matrine-NQO1 binding and intracellular target engagement were evaluated using molecular docking, molecular dynamics simulations, surface plasmon resonance (SPR), and the cellular thermal shift assay (CETSA). The therapeutic effects of matrine were assessed in mice with CLP-induced SALI and in lipopolysaccharide (LPS)-stimulated MH-S cells. Lung histopathology, inflammatory cytokine production, target protein expression, ferroptosis-associated indicators, and NF-κB activation were evaluated using molecular, biochemical, and histological assays. The functional contribution of NQO1 was further examined using the NQO1 inhibitor ES936. RESULTS: scRNA-seq analysis of GSE273924 revealed substantial remodeling of the CD45-enriched pulmonary immune-cell landscape in mice with intratracheal E. coli-induced pneumonia, including macrophage transcriptional programs associated with ferroptosis and inflammatory signaling. Integrated network pharmacology and bioinformatics analyses prioritized NQO1 as a candidate target of matrine and identified NF-κB signaling as a potentially relevant pathway. Molecular docking, molecular dynamics simulations, SPR, and CETSA supported matrine-NQO1 binding and intracellular target engagement. Functionally, matrine improved survival, attenuated lung injury, reinforced NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses, and suppressed NF-κB activation in CLP mice. Similar protective effects were observed in LPS-stimulated MH-S cells. ES936 partially attenuated the matrine-mediated improvements in cell viability, redox homeostasis, ferroptosis-associated indicators, and NF-κB p65 phosphorylation, supporting a functional contribution of NQO1 to the protective effects of matrine. CONCLUSION: Matrine alleviates SALI by reinforcing NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses and attenuating NF-κB-driven inflammation.

Animals↗

PubMed2026

Integrative computational analysis combining network pharmacology, regulatory network modeling, and molecular dynamics reveals the mechanisms of Quanshen compound in ITP.

UNLABELLED: Immune thrombocytopenia (ITP) is a hemorrhagic disorder caused by immune dysfunction. Quanshen Compound (QSC) is an in-house preparation developed by the Uyghur Hospital in Hotan Prefecture. This study primarily investigates and validates the potential pharmacological basis and mechanism of action of QSC in modulating immune thrombopoiesis. Based on the multi-database screening of the QSC and the related targets of ITP, the intersection was obtained to construct a protein-protein interaction (PPI) network and screen the core targets; the intersection targets were analyzed for gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using R packages; a component-target-pathway network was constructed to screen the key active components and their mechanisms of action. At the same time, the TF-mRNA-miRNA regulatory network of the core targets was constructed, and chromosome localization and subcellular localization analysis were performed; further, the binding stability of key components and core targets was verified through molecular docking and molecular dynamics simulation. A total of 227 potential target sites were screened out, among which TNF, IL6, AKT1, TP53 and IL1B were the core targets. The enrichment results indicated that these intersecting target sites mainly participated in inflammatory responses, immune regulation and hemostasis-related biological processes, and were significantly enriched in the PI3K-Akt signaling pathway, Toll-like receptor signaling pathway, Th17 cell differentiation and PD-1/PD-L1 signaling pathway. The core target TF-mRNA-miRNA regulatory network contained 184 nodes and 200 edges, suggesting that the core targets were subject to multi-level regulation. Molecular docking results showed that the main active components had good binding activity with the core targets, and molecular dynamics simulation further verified the stability of the complex. QSC may improve ITP through a multi-component, multi-target, and multi-pathway synergistic mechanism involving key targets such as TNF, IL6, AKT1, TP53, and IL1B, as well as the PI3K-Akt signaling pathway. These findings provide new insights into the potential therapeutic mechanisms of QSC against ITP and warrant further experimental validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s40203-026-00718-0.

Immune thrombocytopenia↗

PubMed2026

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-κB, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗

PubMed1992

Molecular dynamics of alkylated DNA.

The effect of methylation of the O4 atom of thymine in two oligonucleotide sequences is investigated by molecular dynamics simulations. Three types of environments are considered including: (i) in vacuo calculation, with a distance-dependent dielectric function and unhydrated counter-ions; (ii) in vacuo calculation, with a distance-dependent dielectric constant and hydrated counter-ions; and (iii) with a 9 A thick explicit water layer and counter-ions. In all environments, the oligonucleotide sequence containing the chemically modified thymine paired with guanine is more stable than the oligonucleotide sequence in which the modified thymine is paired with adenine. The methyl group attached to the O4 atom of thymine is found in a syn configuration with respect to the N3 atom. The best fit between the experimental NMR results and the molecular dynamics simulations is obtained using the environment with hydrated counter-ions.

Alkylation↗

PubMed2026

Integrated computational and experimental benchmarking of Bacillus phage endolysins reveals the relationship between peptidoglycan-fragment recognition descriptors and antibacterial performance.

Protein-based antibacterials such as bacteriophage endolysins offer a targeted therapeutic strategy against Gram-positive pathogens. However, prioritizing the most effective candidates from the large sequence diversity available remains a significant challenge. Here we present a standardized computational-experimental benchmarking framework that evaluates seven phage-derived endolysin variants (E1, E2, E3, E7, E10, E12, and E15) identified from Bacillus genomes. We combined molecular docking and residue-level interaction mapping against muramyl dipeptide (MDP), a minimal conserved peptidoglycan motif, with 1000-ns molecular dynamics simulations, MM/PBSA binding free-energy estimation, and matched functional inhibition assays against Staphylococcus aureus and Micrococcus luteus. Computational analyses revealed generally favorable MDP recognition across variants, albeit with notable differences in contact patterns and complex stability profiles. Experimental screening identified E2 as the most potent antibacterial agent against both species, while E7 and E1 performed strongly in selected computational metrics. Integrated analysis showed only modest correlations between computational descriptors of fragment recognition/stability and observed antibacterial performance. This study establishes a practical comparative benchmarking platform for endolysin candidate prioritization, nominates E2 and E7 as promising candidates for further development, and highlights E1 as a potential structural scaffold for rational engineering, while explicitly demonstrating both the utility and the current limitations of using minimal peptidoglycan fragments as proxies for full cell-wall recognition in lysin benchmarking.

Endopeptidases↗