Pediatric B-cell acute lymphoblastic leukemia achieves overall survival approaching 90
Girardinia diversifolia is a wild medicinal plant traditionally used to treat rheumatism. However, experimental validation of its anti-inflammatory potential remained unexplored. This study investigated the prospect of G. diversifolia leaf extracts to alleviate inflammation via in vitro and in silico approach with relevance to rheumatoid arthritis (RA). Phytochemical composition of methanolic extract of G. diversifolia leaves (GD) were investigated via spectrophotometric methods, gas chromatography – mass spectrometry (GC-MS) and High-Resolution Liquid Chromatography–Mass Spectrometry Quadrupole Time-of-Flight (HR-LCMS-QROF). In vitro anti-inflammatory activity was evaluated via HRBC membrane stabilization assay, heat induced protein denaturation assay and 15-lipoxygenase inhibitory assay. Additional anti-oxidant assays were conducted. Network pharmacology analysis was conducted to predict potential RA associated gene targets of detected GD compounds, hub genes and signalling pathways. Molecular docking of compounds to target hub genes and evaluation of interacting residues was done. Phytochemical analysis tentatively identified several phytosterols, fatty acids, tocopherols, alkaloids and terpenoids. At the concentrations tested, GD exhibited notable membrane stabilizing activity, prevention of protein denaturation and 15-LOX inhibitory activity. At higher concentrations membrane stabilization and prevention of protein denaturation was statistically comparable to standard drug. The predicted bioactive compounds - Squalene, Somniferine, Americine and Dipiperamide E showed favourable binding affinities for key inflammatory targets - TLR4, AKT1, MMP9 and EGFR respectively, interacting with key residues present at the canonical binding sites of the proteins. In conclusion, G. diversifolia has anti-inflammatory potential. The present findings provide preliminary scientific evidence for utilization of G. diversifolia as traditional medicine for treating rheumatism and establish a foundation for future pharmacological investigations of this underexplored medicinal species.
Streptococcus pneumoniae remains a leading bacterial pathogen causing pneumonia, meningitis, septicemia, and post-viral respiratory infections such as COVID-19. Despite licensed vaccines, efficacy is limited by serotype dependency, cost, and restricted coverage, highlighting the need for broad-spectrum alternatives. Protein-based vaccines with conserved antigens represent a promising strategy. This study aimed to design and evaluate an efficient peptide-based vaccine against pneumococcal virulence factors using immunoinformatics tools. Two major pneumococcal surface proteins were selected, and two immunodominant epitope-rich regions enriched in overlapping B-cell and MHC-II epitopes were identified and linked using a flexible linker. To enhance immunogenicity, human β-defensin-2 (hBD-2) was fused to the N-terminus with a rigid linker, and a His-tag was added at the C-terminus. The construct showed high predicted antigenicity (VaxiJen score: 0.917), was predicted to be non-allergenic, and exhibited favorable solubility and physicochemical properties. Structural modeling, refinement, discontinuous B-cell epitope mapping, docking with TLR4/MD2, molecular dynamics, and immune simulations were performed. The construct demonstrated favorable stability and safety, while B-cell epitope mapping indicated predicted immunogenic potential. Molecular docking predicted stable interactions with TLR4/MD2, with the top-ranked ClusPro complex showing an energy score of − 779.3. Normal mode analysis suggested structural flexibility and conformational stability of the complex. Immune simulations predicted potentially robust primary, secondary, and tertiary responses, including antibody production, memory cell generation, and IFN-γ induction. Integrating conserved immunodominant regions into a peptide-based construct with hBD-2 adjuvant through rational immunoinformatics resulted in a computationally predicted stable and immunogenic candidate that may potentially overcome serotype dependency and provide broader protection. In silico results suggest this peptide-based vaccine is a promising candidate, warranting further in vitro and in vivo validation.
Targeting tumor angiogenesis through vascular endothelial growth factor receptor-2 (VEGFR-2) remains a promising strategy for breast cancer therapy. In this present research study, a novel series of quinoline–triazole hybrids (SVI01–SVI10) was designed, synthesized, and evaluated as potential VEGFR-2 inhibitors. The compounds were characterized and subjected to molecular docking, MM/GBSA study and MD simulations to investigate their binding affinity and stability within the VEGFR-2 active site (PDB ID: 1Y6A). In vitro cytotoxicity against the MCF-7 breast cancer cell line revealed that compound SVI08 exhibited the moderate activity (IC50 = 13.5 µM), compared to the standard doxorubicin (IC50 = 2.98 µM). Upon docking study, all compounds showed favourable binding interactions with Cys917 in hinge region, along with stable protein–ligand complexes during 100 ns simulations. ADMET profiling indicated acceptable drug-like properties for all compounds. Furthermore, in vivo sub-acute toxicity studies in Wistar rats confirmed that SVI08 is well tolerated up to 50 mg/kg, with no significant histopathological abnormalities. Overall, these findings highlight quinoline–triazole hybrid SVI08 as a preliminary lead to the further optimization as a VEGFR-2-targeted anticancer agents.
Dengue virus (DENV) remains a pressing global health threat with no approved antiviral therapy to date. In this study, we explore the conserved hydrophobic pocket at the dimer interface of the dengue capsid protein as a novel target for antiviral intervention. Using a high-resolution capsid structure with modeled N-terminal disordered regions, we performed virtual screening of the entire DrugBank database employing AutoDock Vina to identify potential repurposable inhibitors. Six top-binding candidates were shortlisted based on docking scores and binding site specificity. These molecules were subjected to classical molecular dynamics (MD) simulations to evaluate complex stability, followed by thermal titration MD (TTMD) to assess interaction robustness under thermal stress. Three molecules—DB02152, DB08683, and DB13014—exhibited highly stable binding throughout both MD and TTMD analyses, with DB13014 (Hypericin) showing the highest thermal stability and favorable interaction energy. In silico ADMET profiling further validated the drug-like properties of these compounds, indicating acceptable oral bioavailability, low toxicity risk, and synthetic tractability. These findings highlight the dengue capsid hydrophobic pocket as a viable drug target and propose repurposing of small molecules as anti-dengue therapeutics.
Pancreatic cancer remains a therapeutic challenge due to its aggressive nature and resistance to conventional therapies. This study investigates the epigenetic effects of curcumin on the miR-29b/DNMT3B/MUC1 axis in pancreatic cancer cells (MIA PaCa-2) through an integrated bioinformatics and experimental approach. In silico analyses, including molecular docking and a preliminary 10 ns molecular dynamics simulation, indicated a plausible binding pose of curcumin within DNMT3B’s catalytic site (binding energy: − 4.72 kcal/mol), with key interactions at residues GLU585 and ASN718, suggesting short-term binding persistence. In vitro experiments demonstrated that curcumin (IC50 = 32.1 μM) significantly upregulated miR-29b (1.27-fold, p < 0.05), downregulated DNMT3B (63
Subtype selectivity is a paired drug-design property, and some structure-based studies infer it from score comparisons across receptors without directly validating the score difference against paired experimental selectivity. We evaluated Vina-family docking-score differences in an audited 5-HT2A/5-HT2B benchmark comprising 419 same-endpoint paired activity records, 413 unique compounds, and 411 docking-complete compounds across two structures per subtype. Experimental selectivity was ΔpX = pX(5-HT2A) - pX(5-HT2B), and docking selectivity was Δscore = mean score(5-HT2B) - mean score(5-HT2A), so positive values favored 5-HT2A. Vina Δscore gave Pearson r = 0.097 (95
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer occurring worldwide. The non-specificity and toxic side effects of conventional anti-cancer drugs have encouraged researchers to seek safer alternatives from natural sources. Atranorin, a depside group of secondary metabolites found in various lichens, possesses several pharmacological properties. Therefore, we aimed to investigate the anti-lung cancer activity of atranorin. For that, the anti-proliferative effect of atranorin was assessed and compared to that of doxorubicin against A549 lung cancer cells and BEAS-2B normal cells. Subsequently, a range of microscopic and flow cytometric evaluations were conducted to determine the apoptotic efficacy of atranorin. Furthermore, network pharmacology, combined with molecular docking, facilitated the identification of key targets. Finally, a molecular dynamics simulation was performed to verify the stability of the atranorin-target complex. Results reveal that IC50 of atranorin is 15.05 ± 1.18 µM against A549 cells and has a significantly higher selectivity index than the standard drug doxorubicin. Atranorin induced robust apoptosis in the A549 cells through upregulation of phospho-p53 expression. Apoptosis was associated with the generation of intercellular ROS. A significant disruption of mitochondrial membrane potential and upregulation of Caspase-9 expression indicated that apoptosis occurred via the intrinsic pathway. Network pharmacology identified a potential target, Matrix metalloproteinase-9 (MMP-9), and in silico docking analysis revealed that atranorin has a higher binding affinity for MMP-9 than doxorubicin. Additionally, molecular dynamics simulation demonstrated the stability of the atranorin-MMP-9 complex through several parameters. Therefore, in silico and in vitro experiments confirmed the significant anticancer activity of atranorin against A549 cells.
Oral squamous cell carcinoma (OSCC) is a major global health burden, with epidermal growth factor receptor (EGFR) serving as an important therapeutic target. However, resistance to currently available EGFR inhibitors limits the efficacy of long-term treatment. In this study, a structure-based virtual screening approach was employed using the Mcule database to identify novel small molecules with potential EGFR-inhibitory activity. The top-ranked compounds were subjected to consensus docking using multiple docking platforms and compared with established EGFR inhibitors. The most promising complexes were further evaluated using 500 ns molecular dynamics simulations to investigate their structural stability, conformational flexibility, and binding persistence. ADMET and pharmacokinetic analyses were performed to assess the drug-like and safety profiles. Five lead compounds (C1–C5) demonstrated significant binding affinities toward EGFR, ranging from − 9.9 to − 9.2 kcal/mol, while satisfying the major drug-likeness criteria. Molecular dynamics simulations suggested that C1 and C4 may form relatively stable EGFR–ligand complexes, as supported by stable RMSD convergence and persistent interactions with key active-site residues throughout the simulation period. Trajectory-based interaction analyses further indicated a sustained binding behavior. ADMET profiling predicted favorable oral bioavailability and low predicted toxicity for most compounds, particularly C3 and C5, although a potential risk of cytochrome P450-mediated drug–drug interactions was observed. Overall, the shortlisted compounds exhibited docking and dynamic stability profiles comparable to those of the reference inhibitor Lapatinib. These findings suggest the potential therapeutic relevance of structurally novel EGFR-targeting scaffolds in OSCC and provide a foundation for future experimental validation through in vitro and in vivo studies.
Infectious bronchitis virus (IBV) remains a major threat to the poultry industry owing to its high transmissibility and the continuous emergence of antigenically diverse variants that compromise vaccine efficacy. The viral spike protein, which mediates host cell attachment and membrane fusion, represents an attractive target for antiviral intervention. In this study, a structure-based computational approach was employed to identify phytochemical inhibitors targeting the IBV spike protein. A curated library (PCLibVer2) comprising 2,400 phytochemicals derived from poultry-safe botanicals was subjected to hierarchical virtual screening using Glide against two receptor-binding domain-associated binding pockets. The three top-ranked lead phytochemicals were evaluated by three independent 100 ns molecular dynamics simulations, followed by trajectory-based Prime MM-GBSA binding free energy calculations and principal component analysis. All three phytochemicals exhibited favourable docking scores and stable protein–ligand interactions throughout the simulations. Molecular dynamics analyses demonstrated stable structural behaviour, persistent hydrogen-bond interactions, and reduced conformational sampling relative to the apo protein. MM-GBSA analysis predicted favourable binding free energies for all complexes, with Rutin exhibiting the strongest binding affinity at both binding pockets (− 50.07 ± 13.14 and − 55.14 ± 20.22 kcal/mol). Principal component analysis further showed that Rutin consistently produced the most compact conformational ensemble, indicating reduced protein flexibility. In silico ADMET analysis identified comparable pharmacokinetic profiles for the three lead phytochemicals. Collectively, these findings highlight the potential of flavonoid-based phytochemicals as natural inhibitors of IBV spike-mediated viral entry. This study provides a computational framework for the development of phytochemical-based interventions that may complement existing vaccination strategies and support efforts to reduce antibiotic use in poultry, pending experimental validation.
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.
Kisspeptin-10 (KP-10), the bioactive core fragment of kisspeptin neuropeptides, has emerged as a modulator of reward-related behaviors beyond its canonical role in reproductive neuroendocrinology. While behavioral studies indicate that KP-10 promotes impulsive and compulsive-like phenotypes in rodent models, the molecular mechanisms underlying these effects remain unclear. This study employed an integrated computational approach to evaluate the binding selectivity of KP-10 across key receptors implicated in impulsivity and compulsion. Three-dimensional structures of KP-10 bound to kisspeptin receptor 1 (KISS1R), neuropeptide FF receptor 1 (NPFF1R), dopamine D1/D2 receptors (D1R/D2R), and serotonin 5-HT1A/2A receptors (5-HT1AR/5-HT2AR) were predicted via AlphaFold2 and embedded in lipid bilayers for 500-ns molecular dynamics simulations. Binding free energies calculated via the implicit solvation method revealed the lowest binding energies for KISS1R (ΔGGB =− 158.3 ± 6.9 kcal/mol), followed by NPFF1R (ΔGGB =− 155.5 ± 10.0 kcal/mol), with substantially weaker interactions for 5-HT1AR (− 136.5 ± 9.2 kcal/mol), D2R (− 115.9 ± 9.5 kcal/mol), and 5-HT2AR (− 111.1 ± 9.3 kcal/mol). Conformational stability metrics (RMSD, RMSF, Rg, and hydrogen bond occupancy) corroborated these energetic trends. These results demonstrate the high selectivity of KP-10 for KISS1R compared to the following monoaminergic receptors: dopamine types 1 and 2 and serotonin types 1A and 2A, suggesting that its effects on impulsive and compulsive behavior occur primarily through canonical kisspeptin signaling rather than through direct modulation of these receptors. However, experimental confirmation of these results is required to draw firm conclusions.
Helicobacter pylori colonize the gastric epithelial cells and poses a strong risk factor for gastric complications like chronic gastritis, ulcer diseases, and gastric cancer. Despite the complex treatment regimens, antibiotic resistance is the primary cause of eradication failure and calls for alternate treatment strategy. This study aims to design peptide ligands that specifically target protein–protein interactions in the transcription machinery of H. pylori. The dissociable σ-factor known as SigA, which binds with the RNA polymerase (RNAP) core beta-prime subunit (RpoC). This interacting region has been targeted to design specific peptide ligands using structure-based computational methods. The lack of experimental structures necessitated generating structural models for Hp RpoC, Hp SigA and Hp RpoC-SigA complex structure. The complex was built based on hybrid template-based modeling (TBM) techniques. The RpoC-SigA interface has been exploited to design five suitable peptides-three peptides from H. pylori SigA (P1, P2, and P3) and two peptides from the SigA-interacting regions of H. pylori RpoC (P4 and P5). Investigation of the binding affinity of all five peptides suggests that P1, P3, and P5 exhibit significant affinity, indicating a potential hindrance to RNAP interaction with transcription factors prior to holoenzyme formation. These peptides may serve as promising inhibitors against H. pylori infection.
The immune system is the body’s defense mechanism that uses cells and organs to protect against foreign substances called pathogens. The absence or dysfunction of elements within immune system lead to immune diseases such as severe combined immunodeficiency (SCID). SCIDs are hereditary disorders that are characterized and sub-classified by an impaired number and function of T and B cells as T-B + SCID and T-B-SCID. The association between varied SCID phenotypes, including Omenn Syndrome, in clinics has been revealed with the presence of missense mutatinos in RAG1 gene. Here, we aim to understand the structural impacts of varied SCID phenotypes associated variants in RAG1 by utilizing in silico tools, molecular dynamics simulations and docking studies. Along 100 ns, classical MD simulations are run with mutant RAG1 complexes, including Arg396Leu(rs104894291), Arg396His(rs104894291), Val433Met(rs199474679), Met435Val(rs141524540), Arg474His(rs199474686), Arg474Cys(rs199474678), Trp522Cys(rs193922461), Glu722Lys(rs28933392), Arg778Gln(rs121918569), and Arg975Trp(rs121918570). Any structural alterations experienced in RAG1 due to presence of these missense variants were studied together with the change in RAG1-RAG2 protein–protein binding dynamics and 12-RSS heptamer/23-RSS nanomer bindings to RAG1 to understand the functional impacts of these missense variants on RAG1. These calculations have suggested that Arg396Leu(rs104894291), Arg474His(rs199474686), Arg474Cys(rs199474678), and Glu722Lys(rs28933392) have resulted in more drastic alterations in RAG1’s structure and function compared to others. We ended up with the theoretical background constituted by molecular dynamics simulations and docking calculations for each SCID or atypic SCID (Omenn Syndrome). Our calculations would be further utilized to design a novel molecule or to run drug repurposing to ensure the proper functioning of mutant RAG1.
Dengue viruses (DENVs) usually cause a mild febrile illness which might flare up in some patients as dengue haemorrhagic fever (DHF) or dengue shock syndrome. Altered expression of autoimmune markers and development of autoimmune diseases was observed in patients exhibiting prolonged dengue symptoms, suggesting a possible correlation between DENVs and autoimmune diseases. Molecular mimicry of the blood coagulation pathway proteins by DENVs might be a potential factor underlying clinical manifestations of DHF. Inhibition of protein-protein interactions (PPIs) in DENV mimicry proteins and human proteins can potentially treat both DHF and, associated autoimmune diseases. In this study, we have performed a systematic in silico analysis of human proteins interacting with DENV mimicry proteins (HPIDMP) as novel drug targets. Potential inhibitors of the HPIDMP were discerned from the DrugBank database following stringent parameters. The protein–ligand interactions were predicted using molecular docking and evaluated with decoy-based validation, molecular dynamics simulations, and MM-PBSA binding free energy calculations. RAF1 targeting drugs Sorafenib and Regorafenib exhibited the most consistent interaction profile across all computational analyses, followed by the SIRT1-targeting compounds selisistat and resveratrol, which demonstrated moderate but consistent computational support. In contrast, the MYH9–artenimol and HSPE1–phenethyl isothiocyanate systems showed comparatively weaker support. On the basis of our results, we propose Sorafenib and Regorafenib as the most promising candidates for in vitro or clinical studies for treatment of DHF and/or DENV-associated autoimmune diseases, followed by Selisistat and Resveratrol. Thus these DrugBank molecules can be incorporated in clinical studies or in vitro testing for treatment of DHF and/or DENV-associated autoimmune diseases. Also, the methods adopted in this study can guide the repurposing of known drugs to treat other pathogen-associated autoimmune diseases.
Dopamine receptors (DRs) are key modulators of physiological and behavioral responses in the central nervous system (CNS), playing a major role in psychotic disorders. Among these, the D2-like members D2R, D3R and D4R are particularly attractive therapeutic targets for the development of novel compounds derived from both synthetic and natural sources. The marine bryozoan Amathia produces alkaloids known as amathamides (A-H), among which the tribrominated amathamide G (AM-G) stands out as a promising scaffold. Its benzene–aliphatic linker–pentacyclic structure is reminiscent of standard dopamine antagonists such as eticlopride (ETI). In this study, a debrominated (AM-0) and monobrominated derivatives (M4B, M5B and M6B) were successfully synthesized and purified. As an initial preclinical assessment, the drug likeness profiles of these compounds were predicted and analyzed based on physicochemical properties, medicinal chemistry, and pharmacokinetic parameters. The analysis revealed that debromination of AM-G improves both lipid and aqueous solubility, enhances overall drug desirability across four major medicinal chemistry rule sets, and predicts better CNS penetration, bioavailability, half-life, and clearance, while maintaining a relatively low risk of carcinogenicity. Molecular docking and molecular dynamics (MD) simulations suggested a differential affinity amongst amathamide G derivatives towards D2-like receptors. Specifically, AM-G behaved as a high-affinity putative ligand for D3R/D4R, whereas M5B and M6B showed selectivity for D2R. These findings support continued in vitro and in vivo evaluation of these compounds, particularly in models involving expression, structure-based variations, and pathologies associated with D2R-like receptors.
Cholera, caused by Vibrio cholerae, continues to pose a serious global public health challenge, with its impact worsened by rising antibiotic resistance associated with bacterial biofilm formation. This study explicitly describes the role of the uncharacterised protein (UP) TYC33605.1 in cyclic-di-GMP (c-di-GMP)-mediated biofilm regulation and identifies natural computationally predicted inhibitors to disrupt this mechanism. Functional annotation revealed TYC33605.1 as a membrane-associated diguanylate cyclase (DGC) with GGDEF and sensory domains, a potential driver for c-di-GMP synthesis and biofilm persistence. Homology modelling and molecular dynamics (MD) simulations supported a plausible, stable predicted 3D structure (C-score: −1.22, Ramachandran favoured regions: 91.1
The Mycobacterium avium complex (MAC) comprises non-tuberculous mycobacteria that cause respiratory infections in vulnerable humans and diseases in animals. Treating these infections is problematic owing to the persistence of MAC inside hosts, antibiotic resistance, and adverse side effects. SAM-dependent methyltransferase is a key enzyme altering lipids and metabolites, as well as regulates cell wall permeability and virulence. Specifically, the ability of SAM-dependent methyltransferase to modify mycolic acid has made it a drug target for fighting persistent infections. To prevent the increasing MAC infections, targeting virulent genes and the discovery of novel drugs are necessary. Moreover, because of the limitations of existing therapies, alternative strategies are essential. This in silico analysis emphasised screening natural products, assessing their pharmacokinetic and toxicity properties, molecular docking with the SAM-dependent methyltransferase of MAC, followed by molecular simulations. The intention was to detect lead compounds acting against SAM-dependent methyltransferase. In this regard, eight natural products with suitable ADMET properties were finalised. Artificial intelligence-based modelling of SAM-dependent methyltransferase generated high-quality three-dimensional structures. Their molecular docking with the eight natural products identified docked complexes with binding energies ranging from − 4.7 to −10.3 kcal/mol. Molecular simulations with iMODS confirmed the stability and robustness of the docking complexes. Notably, demethoxycurcumin (–10.3 kcal/mol) and bisdemethoxycurcumin (–10.2 kcal/mol) exhibited superior binding affinities with the SAM-dependent methyltransferase of M. avium 104. These were the top compounds targeting SAM-dependent methyltransferase. This research provided evidence for drug target identification, although further experimental validation is required to translate this in silico outcome into clinical use.
Hand, Foot, and Mouth Disease (HFMD) presents a serious public health concern, especially in children below five years of age and is predominantly caused by Coxsackievirus A16 (CV-A16) and Enterovirus 71 (EV-A71). Despite the availability of supportive treatments and strain-specific protection offered by existing monovalent vaccines, there is an urgent need for a broadly effective, widely accessible multivalent vaccine. This study implements reverse vaccinology to design a multiepitope vaccine targeting key immunogenic regions of CV-A6, CV-A16 and EV-A71. From 18,278 VP1 capsid protein sequences, redundancy was eliminated using CD-HIT (90
Medicinal plants offer promising multi-target therapeutic agents due to their diverse bioactive compounds. This study explored LC–MS profiling, network pharmacology, molecular docking, and molecular dynamics simulation to investigate the potential antidepressant-related mechanisms of Leonotis leonurus and Mentha longifolia. A total of 20 and 15 compounds were identified in L. leonurus and M. longifolia, respectively. Target prediction and overlap analysis revealed 16 and 22 depression-associated targets for each plant. These targets were used to construct protein–protein interaction networks and perform Gene Ontology and KEGG pathway enrichment analyses. For L. leonurus, the key targets included SLC6A4, PTGS2, MAOA, and MAOB were enriched in serotonergic and dopaminergic synapse pathways, neuroactive ligand–receptor interaction, and PI3K/Akt signalling, suggesting, suggesting potential involvement in neurotransmission and neuroinflammatory regulation. Molecular docking showed strong interactions of procyanidin B5 and chrysoeriol with SLC6A4 and MAOA, respectively, while baicalin demonstrated the most favourable binding affinity (− 39.45 kcal/mol), exceeding that of fluoxetine (− 14.69 kcal/mol), both surpassing fluoxetine’s affinity (− 14.69 kcal/mol) to SLC6A4. For M. longifolia, targets such as DRD4, DRD3, GSK3β, COMT, and AKT1 were linked to dopaminergic synapse and neuroactive ligand–receptor pathways. Key compounds, including baicalin, salvianolic acid A, and rosmarinic acid, showed strong binding to DRD4, DRD3, and GSK3β. Notably, quercetin 3-galactoside exhibited the highest affinity toward DRD4 (− 46.74 kcal/mol), outperforming fluoxetine (− 24.91 kcal/mol). Collectively, these findings suggest that both plants may possess antidepressant-related potential through predicted multi-component, multi-target modulation of neurotransmitter systems and neuroinflammatory pathways. However, these findings remain computational and require experimental validation to confirm biological efficacy and therapeutic relevance. This study provides a mechanistic framework to support future pharmacological investigations into the traditional use of these medicinal plants for mental health applications.
