Unraveling the Neuroprotective Mechanisms of Cobalamin in Ischemic Stroke: A Network Pharmacology and Molecular Docking Approach

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Methods We screened databases to identify the targets of cobalamin and performed intersection analysis with ischemic stroke-related targets to construct a "drug-target-disease" interaction network. Gene Ontology (GO) and KEGG pathway enrichment analyses were conducted to identify key biological processes and signaling pathways. Additionally, molecular docking was employed to assess the binding affinity between cobalamin and core targets. Results A total of 95 therapeutic targets of cobalamin for ischemic stroke were identified. Based on Cytoscape and molecular docking, we selected ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1, which exhibited strong binding affinity. GO analysis revealed that cobalamin primarily regulates inflammatory responses, post-translational protein modifications, complement binding, and lipoprotein particle binding. KEGG pathway analysis indicated that complement and coagulation cascades, PI3K/AKT, and other inflammation-related pathways are the major signaling pathways involved in the treatment of ischemic stroke by cobalamin. Conclusion This study is the first to elucidate the molecular mechanisms through which cobalamin exerts anti-inflammatory and neuroprotective effects via multi-target and multi-pathway actions from a computational biology perspective. These findings provide new theoretical insights for the treatment of ischemic stroke with cobalamin, though further experimental validation is required. Health sciences/Neurology Health sciences/Neurology/Neurological disorders/Stroke Ischemic stroke Cobalamin Network pharmacology Molecular Docking Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Ischemic stroke accounts for approximately 70% of all stroke cases, resulting in over 10 million deaths annually worldwide ( https://www.who.int/data/gho ). The pathological mechanisms of ischemic stroke involve multiple processes, including oxidative stress, inflammation, neuronal apoptosis, and disruption of the blood-brain barrier [ 1 , 2 ]. Although thrombolytic therapies, such as recombinant tissue plasminogen activator (rt-PA), and endovascular thrombectomy have shown some success in early reperfusion, many patients still suffer from irreversible neurological deficits due to the narrow therapeutic time window and the risk of reperfusion injury [ 3 ]. Therefore, exploring neuroprotective agents with multi-target and multi-pathway regulatory effects has become a prominent area of research. Cobalamin (vitamin B12) is a water-soluble vitamin essential for one-carbon metabolism and myelin synthesis. Recent studies suggest that cobalamin may possess neuroprotective effects, including antioxidant, anti-inflammatory, anti-apoptotic, and mitochondrial function-regulating properties [ 4 , 5 ]. Given these diverse biological activities, cobalamin is hypothesized to mitigate several pathological processes associated with ischemic stroke [ 6 ]. However, direct evidence supporting this hypothesis remains limited. Interestingly, cobalamin deficiency has been linked to various neurological disorders, such as cognitive impairment, autism, epilepsy, schizophrenia, depression, and migraines. Several studies have demonstrated that cobalamin supplementation can alleviate symptoms of these conditions [ 7 – 9 ]. Moreover, low serum cobalamin levels have been identified as an independent risk factor for ischemic stroke, with early supplementation showing potential to improve neurological outcomes in stroke patients [ 10 – 12 ]. Traditional experimental approaches are limited in fully elucidating the complex regulatory networks involved in ischemic stroke. In contrast, network pharmacology, which integrates target prediction, pathway analysis, and molecular docking, offers a systematic approach to explore the interactions between drugs, targets, and diseases, providing a novel perspective on the therapeutic potential of cobalamin [ 13 ]. This study aims to: (1) identify the core targets of cobalamin in ischemic stroke through network pharmacology, (2) validate the binding affinity of cobalamin to key targets using molecular docking, and (3) propose a multi-target regulatory framework for future experimental validation. The findings are expected to provide a theoretical basis for nutritional interventions and drug development in the treatment of ischemic stroke. A flowchart of the study is shown in Fig. 1 . 2. Methods and materials 2.1 Identification of targets of cobalamin Potential cobalamin targets were systematically retrieved from three databases in November 2024: DrugBank, GeneCards (retaining only targets with relevance scores ≥ 10) [ 14 ], and SwissTargetPrediction (using a probability cutoff ≥ 0.5) [ 15 ]. All gene names were converted to official HUGO Gene Nomenclature Committee symbols via UniProt, and duplicates were removed after cross-database integration. 2.2 Identification of ischemic stroke disease targets Disease targets for ischemic stroke were identified by searching GeneCards, DisGeNET, and OMIM databases. Targets with a relevance score ≥ 10 in GeneCards were included in the analysis [ 14 ]. A Venn diagram was used to merge the data from these databases, and duplicates were removed to identify common ischemic stroke targets. The potential therapeutic targets of cobalamin against ischemic stroke were then identified by cross-referencing these common ischemic stroke targets with known cobalamin targets using the Draw Venn Diagram online tool. Functional classification of these therapeutic targets was performed through the Panther database (accessed November 2024) [ 16 ]. 2.3 PPI network construction and analysis The common cobalamin targets for ischemic stroke were analyzed using the DAVID database (accessed December 2024) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis with Benjamini-Hochberg FDR correction. Terms with P < 0.05 and FDR < 0.05, containing at least 5 targets, were considered significant. Protein-protein interaction (PPI) networks were constructed using the STRING database (Homo sapiens; minimum interaction score: 0.7) and visualized in Cytoscape using a force-directed layout. Hub genes were identified as the top 10% based on degree centrality. The integrated functional network was then constructed and visualized [ 17 ]. 2.4 Molecular docking validation First, the crystal structure of the target protein was obtained from the PDB. PyMOL was used to remove water molecules, inorganic ions, and other non-essential components, and the processed structure was saved as the receptor file [ 18 ]. The ligand molecule was retrieved from the PubChem database, converted to PDB format using PyMOL, and subsequently prepared by adding hydrogen atoms and charges. The coordinates of the receptor’s active site were identified using AutoDockTools, and a grid box was defined by specifying the center and dimensions of the docking region. Molecular docking was then performed using AutoDock Vina [ 19 ]. After docking, the binding conformation with the lowest binding energy was selected and analyzed. The receptor-ligand interactions were visualized using PyMOL [ 20 ]. The URLs employed in this section are summarized in Table 1 . Table 1 The websites software used in the study. NO Database, database and analysis platform Website Version References 1 AutoDock Vina_v1.2.2 https://vina.scripps.edu/ V1.2.2 [ 19 ] 2 AutoDockTools https://autodock.scripps.edu/resources/adt/ V1.5.7 [ 21 ] 3 Cytoscape https://cytoscape.org/ V3.10.1 [ 22 ] 4 DAVID Bioinformatics https://david.ncifcrf.gov/tools.jsp - [ 23 ] 5 Draw Venn Diagram http://bioinformatics.psb.ugent.be/webtools/Venn/ - - 6 DisGeNet database https://www.disgenet.org/ - [ 24 ] 7 Drugbank database https://go.drugbank.com/ V6.0 [ 25 ] 8 GeneCards database https://www.genecards.org/ - [ 14 ] 9 OMIM https://omim.org/ - [ 26 ] 10 PubChem database https://pubchem.ncbi.nlm.nih.gov/ - - 11 Pymol https://www.pymol.org/ V3.0.4 [ 27 ] 12 String tool https://string-db.org/ V12.0 [ 28 ] 13 Swiss Target Prediction http://www.swisstargetprediction.ch/ - [ 29 ] 14 Uniprot database https://www.uniprot.org/ - [ 30 ] 3. Results 3.1 Target identification for GO and KEGG enrichment analysis of cobalamin intervention in ischemic stroke A total of 2,216 cobalamin-related targets were initially retrieved from the GeneCards, DrugBank, and SwissTargetPrediction databases. Simultaneously, 2,262 ischemic stroke-associated targets were identified by searching the GeneCards and OMIM databases. By intersecting the cobalamin-related targets with those associated with ischemic stroke, 828 common targets were obtained (Fig. 2 A). Subsequently, a Venn diagram analysis between these 828 shared targets and our previously identified proteomic targets yielded 95 overlapping genes (Fig. 2 B). The functional categories of these 95 targets are shown in Fig. 2 C, including metabolite interconversion enzymes, protein-modifying enzymes, intercellular signaling molecules, transmembrane signal receptors, gene-specific transcriptional regulators, transporters, protein-binding activity modulators, cell adhesion molecules, defense/immunity proteins, and DNA metabolism proteins. 3.2 PPI network construction The overlapping targets were first submitted to the STRING database for PPI network analysis (Fig. 3 A). The resulting network was then visualized using Cytoscape v3.10.1 (Fig. 3 B). To further identify the core targets of cobalamin in the regulation of ischemic stroke, degree centrality (DC) was calculated using the CytoNCA plugin in Cytoscape. ALB, FN1, and CRP exhibited the highest DC values (Table 2 ) and were therefore selected as potential hub targets. To explore the modular organization of these targets, the MCODE plugin was applied for cluster analysis of the PPI network. As shown in Figs. 3 C, 3 E, and 3 G, Cluster 1 consisted of 40 nodes and 437 edges with a score of 22.410, Cluster 2 included 27 nodes and 149 edges with a score of 11.462, and Cluster 3 comprised 4 nodes and 6 edges with a score of 4. Functional enrichment analysis based on GO biological processes (GO-BP) was then performed for each cluster. As illustrated in Fig. 3 D, proteins in Cluster 1 were primarily involved in the negative regulation of blood coagulation, acute-phase response, and blood coagulation. Proteins in Cluster 2 (Fig. 3 F) were mainly associated with blood coagulation, inflammatory response, negative regulation of fibrinolysis, and complement activation via the alternative pathway. Cluster 3 proteins (Fig. 3 H) were predominantly related to lipid transport, lipoprotein metabolic process, and triglyceride catabolic process. Collectively, these results suggest that the core functional modules within the PPI network are mainly involved in coagulation cascades, inflammatory responses, and lipid metabolism. These biological processes are known to play critical roles in the pathogenesis and progression of ischemic stroke. Table 2 The evaluation of drug-likeness properties on key metabolites NO. Target DC value NO. Target DC value 1 ALB 37 20 F2 27 2 APOE 36 21 LEP 27 3 CRP 35 22 MPO 26 4 FN1 35 23 SPP1 26 5 PLG 35 24 CLU 25 6 VWF 32 25 TTR 25 7 VTN 32 26 PF4 25 8 APOB 32 27 PXDN 25 9 C3 31 28 ADIPOQ 24 10 AGT 31 29 APOH 24 11 SERPINE1 30 30 THBS1 23 12 KNG1 30 31 SERPINC1 23 13 APP 29 32 CCL5 22 14 TIMP1 29 33 CP 22 15 HP 29 34 PON1 21 16 TGFB1 28 35 C4B 21 17 SERPINA1 28 36 SERPINF2 20 18 VCAM1 28 37 MMP2 20 19 IGF1 27 To further investigate the functional core genes involved in the effects of cobalamin on ischemic stroke, we performed topological analysis and functional annotation of the PPI network using the CytoHubba plugin in the Cytoscape platform. This analysis identified 10 hub genes: AGT, CRP, PLG, VWF, ALB, FN1, TIMP1, APOE, SPP1, and SERPINE1 (Fig. 4 A). Subsequently, GO enrichment analysis was conducted for these hub genes. In the BP category, the top five enriched terms were: symbiont-related biological processes, fibrinolysis, low-density lipoprotein particle remodeling, negative regulation of blood coagulation, and negative regulation of fibrinolytic processes (Fig. 4 B). In the Cellular Component (CC) category, the most significantly enriched terms included: platelet alpha granule lumen, extracellular space, extracellular region, extracellular exosome, and collagen-containing extracellular matrix (Fig. 4 C). For Molecular Function (MF) (Fig. 4 D), the top enriched terms were: protease binding, protein folding chaperone binding, receptor–ligand activity, signaling receptor binding, and integrin binding. Notably, network centrality analysis using CytoNCA showed a high degree of consistency with the results obtained from CytoHubba, further validating the critical role of these hub genes. These genes are primarily involved in the regulation of key biological processes such as the coagulation cascade, inflammatory response, and lipid metabolism, suggesting that they may play essential roles in the pathogenesis and progression of ischemic brain injury. 3.3 GO enrichment analysis Figure 5 A illustrates the core hub genes potentially modulated by cobalamin in the context of ischemic stroke. GO enrichment analysis further revealed the involvement of these genes in key BP, CC, and MF. In the BP category, the top five enriched terms were: acute-phase response, interaction with symbiont, acute inflammatory response, platelet degranulation, and maintenance of location (Fig. 5 B). For the CC category, the most significantly enriched components included: platelet alpha granule lumen, platelet alpha granule, blood microparticle, endoplasmic reticulum lumen, and secretory granule lumen. In the MF category, the top five enriched functions were: chaperone binding, macrolide binding, toxic substance binding, opsonin binding, and low-density lipoprotein particle binding. In addition, the c-net network diagram (Fig. 5 C) provides a visual overview of the functional associations among these hub genes. These findings suggest that cobalamin may exert protective effects in ischemic stroke by modulating key biological processes such as the inflammatory response, post-translational protein modification, complement activation, and lipoprotein particle binding. 3.4 KEGG enrichment analysis KEGG pathway analysis provides key insights into the regulatory mechanisms underlying biological processes, thereby facilitating a more comprehensive understanding of the protective effects of cobalamin in ischemic stroke. As shown in Fig. 6 A, cobalamin appears to exert its effects primarily through several critical signaling pathways, including the complement and coagulation cascades, cholesterol metabolism, and ECM–receptor interaction pathways. Further KEGG enrichment analysis categorized these pathways into the following major functional groups (Figs. 6 B and 6 C): Human disease-related pathways, such as the AGE-RAGE signaling pathway in diabetic complications, Staphylococcus aureus infection, proteoglycans in cancer, various infectious diseases, and endocrine and metabolic disorders; Organismal systems, encompassing pathways involved in the immune system, digestive system, aging, complement and coagulation cascades, and cholesterol metabolism; Cellular processes, including phagosome formation, focal adhesion, ferroptosis, the p53 signaling pathway, cell growth and death, transport and catabolism, and cell–cell communication in eukaryotes; Environmental information processing, including ECM–receptor interaction, cytokine–cytokine receptor interaction, PI3K-Akt signaling pathway, signaling molecules and interaction, and signal transduction. Figure 6 D illustrates a bubble plot of the top 20 significantly enriched pathways and their associated target genes, while Fig. 6 E displays a pathway–target network, with green nodes representing signaling pathways and yellow nodes indicating target genes. Taken together, these findings suggest that cobalamin may exert neuroprotective effects against ischemic stroke by modulating multiple pathways, particularly those involved in the complement and coagulation cascades, PI3K/Akt signaling, and other inflammation-related mechanisms. This highlights the potential of cobalamin as a multitarget therapeutic agent in the prevention and treatment of ischemic stroke. 3.5 Validation of interactions between cobalamin and potential targets through molecular docking To evaluate the binding affinity of cobalamin with the proteins encoded by the 10 hub genes, molecular docking analysis was performed. The docking model with the lowest binding energy (ΔG) was recorded for each ligand–target protein pair. Due to the lack of available docking sites for CRP and vWF in the AutoDock database, these two targets were excluded from the docking analysis. The docking results for the remaining eight target proteins are summarized in Table 3 and illustrated in Fig. 7 . Among them, cobalamin exhibited the strongest binding affinity with ALB and TIMP1, with ALB showing the most stable binding conformation. This was followed by PLG, FN1, AGT, SERPINE1, APOE, and SPP1. The specific binding sites between cobalamin and each target protein are depicted in Fig. 7 . These results suggest that cobalamin may exert its protective effects in ischemic stroke, at least in part, by stably interacting with key hub proteins involved in the pathophysiology of the disease. Cobalamin is shown in red. Target proteins are displayed as cyan. The places where cobalamin and the target proteins are connected represent specific docking sites between cobalamin and target proteins. Table 3 Molecular docking results of RES with target proteins Drug Targets PDB ID Energy (kcal/mol) Full Fitness (kcal/mol) ΔGvdw (kcal/mol) Cobalamin AGT 5M3X -6.5 -4.5 -5.5 Cobalamin ALB 6JE7 -8.7 -6.5 -7.4 Cobalamin APOE 6V7M -6.3 -4.2 -5.4 Cobalamin FN1 4GH7 -6.8 -4.8 -5.8 Cobalamin PLG 8UQ6 -7.9 -6 -6.7 Cobalamin SERPINE1 9PAI -6.5 -4.7 -5.5 Cobalamin SPP1 3DSF -6.2 -4.5 -5.3 Cobalamin TIMP1 3V96 -8.2 -6.1 -7 4. Discussion With the rapid development of the economy and society, the prevalence of ischemic stroke has gradually increased worldwide, leading to a heavy economic and social burden. Our previous clinical studies have identified cobalamin deficiency as a significant predictor of the occurrence and development of ischemic stroke, and early supplementation of cobalamin can improve patient outcomes [ 10 – 12 ]. Additionally, cobalamin is a bioactive compound with multiple beneficial effects, including neuroprotective roles in ischemic stroke, such as epigenetic regulation, mitochondrial function modulation, and the preservation of the neurovascular unit integrity. In this study, we used network pharmacology, bioinformatics analysis, and molecular docking simulations to explore potential therapeutic targets and mechanisms of cobalamin in ischemic stroke from multiple perspectives. The aim of this study is to investigate the potential therapeutic targets of cobalamin in the treatment of ischemic stroke. First, we identified and validated a set of target genes closely associated with ischemic stroke, including ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1. These genes are critically involved in the pathophysiological processes of stroke, encompassing blood circulation, neuroprotection, inflammation, apoptosis, and vascular remodeling. Notably, our study demonstrated that cobalamin significantly modulated the aberrant expression of these genes, suggesting its potential therapeutic value in promoting neurological recovery following ischemic stroke. ALB is the most abundant circulating protein in the bloodstream and plays a multifaceted biological role. Its functions include binding and transporting a wide array of plasma drugs and endogenous molecules, maintaining colloid osmotic pressure, and exerting antioxidant, anticoagulant, and antiplatelet effects [ 31 – 33 ]. Previous studies have identified serum ALB levels as predictive biomarkers for both the occurrence of stroke and unfavorable outcomes following stroke. The PIVOTAL trial, which enrolled 2,141 participants, reported that lower ALB levels were independently associated with an increased risk of stroke over a median follow-up of 2.1 years, suggesting that ALB may be an important predictor of stroke risk in this population [ 34 ]. Similarly, findings from the CNSR-III, which analyzed data from 13,618 patients with acute ischemic stroke or transient ischemic attack, demonstrated that reduced serum ALB was an independent predictor of poor prognosis. Patients with ALB levels < 35 g/L had a 37% higher risk of unfavorable functional outcomes at 3 months (adjusted OR = 1.37) and a 113% higher risk of mortality (adjusted HR = 2.13). Additionally, for every 10 g/L reduction in ALB, the risk of adverse outcomes further increased (OR = 1.17, HR = 1.86). These associations remained significant throughout the 1-year follow-up period, reinforcing the prognostic value of serum ALB in stroke patients [ 35 ]. TIMP1 is an endogenous inhibitor of matrix metalloproteinases (MMPs) and plays a crucial role in maintaining the integrity of the blood–brain barrier [ 36 ]. A cohort study by Zhong et al. reported that elevated serum TIMP1 levels at admission were associated with poor outcomes in stroke patients [ 37 ]. Existing evidence suggests that during acute brain injury, the endogenous expression of TIMP1 is insufficient to provide adequate neuroprotection, indicating the need for exogenous supplementation to achieve its full therapeutic potential. The neuroprotective mechanisms of TIMP1 may include: (1) inhibition of MMP-9-mediated blood-brain barrier disruption; (2) attenuation of inflammatory responses; and (3) promotion of tissue repair [ 37 , 38 ]. These findings support the rationale for developing TIMP1-targeted therapeutic strategies in stroke management. PLG, a core component of the fibrinolytic system, not only facilitates thrombolysis but also modulates stroke progression through its roles in resolving inflammation, regulating immune cell migration, and providing neuroprotection. Dysregulation of PLG function has been closely associated with the onset and development of stroke [ 39 ]. Similarly, genetic polymorphisms in SERPINE1, which also acts as a chemotactic factor, have been associated with an increased risk of ischemic stroke and may exacerbate neuronal injury after ischemia-reperfusion by enhancing neutrophil infiltration [ 40 ]. Dysregulation of the coagulation-fibrinolysis axis may also contribute to cerebral hemorrhage by compromising vascular stability. For instance, polymorphisms in the FN1 gene-such as rs10202709-are significantly associated with the risk of intraventricular hemorrhage (IVH) in preterm infants, with carriers of the TT genotype being more prone to developing high-grade IVH [ 41 ]. Moreover, elevated plasma levels of cellular fibronectin, a splice variant of FN1, have been identified as a biomarker for hemorrhagic transformation and poor clinical outcomes in patients with acute ischemic stroke [ 42 ]. The M235T polymorphism in the AGT gene has been significantly associated with an increased risk of ischemic stroke—particularly lacunar infarction in men-among Asian populations [ 43 ]. The underlying mechanisms may involve impaired regulation of blood pressure and accelerated atherosclerotic progression. APOE also contributes to stroke susceptibility through epigenetic regulation: its DNA methylation status may modulate key pathways involved in atherogenesis [ 44 ], while APOE genotype variations may further elevate cardiovascular risk by disrupting fatty acid metabolism [ 45 ]. SPP1 plays a critical role in orchestrating the inflammatory response during the acute phase of stroke. After cerebral ischemia–reperfusion injury, SPP1 expression is significantly upregulated and is negatively regulated by miR-340-5p, highlighting its potential as a therapeutic target for anti-inflammatory strategies [ 46 ]. SPP1⁺ macrophages have been shown to promote stroke-associated inflammation following aneurysmal rupture by driving phenotypic switching of vascular smooth muscle cells and facilitating collagen remodeling [ 47 ]. Furthermore, in the MCAO model, activation of SPP1⁺ microglia exacerbates pontine infarction, whereas inhibiting their activity confers neuroprotective effects [ 48 ]. KEGG enrichment analysis revealed that the complement and coagulation cascades, along with the PI3K/Akt signaling pathway, are closely associated with the pathogenesis of stroke. Cobalamin deficiency contributes to increased stroke risk through multiple mechanisms. On one hand, it leads to abnormal accumulation of blood cells in the bone marrow. The resulting fragility of erythrocyte membranes predisposes them to intramedullary hemolysis, causing erythrocyte fragmentation and thrombocytopenia. The accumulation of hemolytic byproducts further damages the vascular endothelium [ 49 ]. On the other hand, cobalamin deficiency promotes the buildup of toxic metabolites such as homocysteine and methylmalonic acid, which impair endothelial function through oxidative stress. This triggers platelet activation and upregulation of tissue factor expression, ultimately initiating the coagulation cascade and exacerbating vascular pathology [ 50 ]. The complement system exerts a dual role in ischemic stroke: while its activation aggravates cerebral ischemia/reperfusion injury and inflammatory responses, it also participates in neural repair processes. Clinical studies have shown that elevated levels of complement components, such as C3, are positively correlated with the degree of neurological impairment in patients with ischemic stroke [ 51 , 52 ], suggesting that the complement cascade may serve as a dynamic target for modulating both injury and repair mechanisms after stroke. The PI3K/Akt pathway plays a central neuroprotective role in stroke by regulating cell proliferation, survival, and metabolism. In cerebral ischemia/reperfusion injury, activation of this pathway alleviates oxidative and endoplasmic reticulum stress, suppresses inflammation, neuronal apoptosis, autophagy, and pyroptosis, and preserves the integrity of the blood–brain barrier. These effects collectively contribute to a reduction in infarct volume and improvement in neurological function [ 53 – 55 ]. Notably, cobalamin supplementation has been shown to activate the PI3K/Akt pathway, leading to increased expression of brain-derived neurotrophic factor, inhibition of neuronal apoptosis, and attenuation of neurological damage in cerebral palsy models [ 56 ], further underscoring the therapeutic potential of this signaling axis in stroke. This study, through computational modeling, revealed that cobalamin may exert neuroprotective effects by modulating multiple key genes and signaling pathways, offering novel insights into the treatment of ischemic stroke. However, several limitations should be acknowledged. First, the findings have not yet been validated by in vitro, in vivo, or clinical studies. Second, no comparisons were made with existing stroke therapies, nor were combination interventions explored. Additionally, the optimal therapeutic dosage of cobalamin remains undefined. Future research should aim to experimentally validate the identified targets and pathways, investigate their underlying mechanisms, and assess both the clinical efficacy and safety of cobalamin-based interventions. These efforts will be crucial for advancing the translational potential of cobalamin in stroke therapy. Despite these limitations, the present study provides a valuable framework for further investigation into the mechanisms by which cobalamin may act in the treatment of stroke, representing an important contribution to the field. 5. Conclusion In this study, we employed a combination of network pharmacology, bioinformatics analysis, and molecular docking simulations to investigate the potential mechanisms of cobalamin in the treatment of ischemic stroke. Our findings indicate that cobalamin targets a broad range of molecules implicated in ischemic stroke, and its therapeutic effects may be mediated through the reversal of aberrant expression of key genes, including ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1. Moreover, the complement and coagulation cascades, as well as the PI3K/Akt signaling pathway, emerged as potential therapeutic pathways. These findings provide a comprehensive understanding of the molecular targets through which cobalamin may exert neuroprotective effects, offering a theoretical foundation for its clinical application in ischemic stroke treatment. Abbreviations AGT Angiotensinogen ALB Albumin APOE Apolipoprotein E CC Cellular Component CRP C-Reactive Protein DC Degree Centrality FN1 Fibronectin 1 GO Gene Ontology IVH Intraventricular Hemorrhage KEGG Kyoto Encyclopedia of Genes and Genomes MCAO Middle Cerebral Artery Occlusion MF Molecular Function MMPs Matrix Metalloproteinases PDB Protein Data Bank PLG Plasminogen rt-PA Recombinant Tissue Plasminogen Activator SERPINE1 Serpin Family E Member 1 SPP1 Secreted Phosphoprotein 1 TIMP1 Tissue Inhibitor of Metalloproteinases 1 VWF Von Willebrand Factor Declarations Acknowledgments We thank all investigators contributed to this article. We also give thanks to all patients enrolled in this study. Data Availability All data analysed during this study are included in the websites mentioned above. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository [57] with the dataset identifier PXD062264. The data not published within this article are available from the corresponding author on reasonable request. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 82171456) awarded to Qin Yang and the 2023 Research Planning Project of the Sichuan Provincial Psychological Society (No. SCSXLXH2023034) awarded to Pingping Liu. Author contributions Q.Y. contributed to the study conception and design and provided critical revisions and editorial input for the manuscript. L. Z. and Y.C. jointly drafted the initial version of the manuscript and developed the primary tables and figures. H.W. and J.W. performed the data analysis. 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Low serum albumin levels predict poor outcome in patients with acute ischemic stroke or transient ischemic attack. Stroke Vasc Neurol. 2021;6(3):458-66. doi:10.1136/svn-2020-000676 . Liu M-B, Wang W, Gao J-M, et al. Icariside II attenuates cerebral ischemia/reperfusion-induced blood-brain barrier dysfunction in rats via regulating the balance of MMP9/TIMP1. Acta Pharmacol Sin. 2020;41(12):1547-56. doi:10.1038/s41401-020-0409-3 . Zhong C, Wang G, Xu T, et al. Tissue inhibitor metalloproteinase-1 and clinical outcomes after acute ischemic stroke. Neurology. 2019;93(18):e1675-e85. doi:10.1212/WNL.0000000000008389 . Ries C. Cytokine functions of TIMP-1. Cell Mol Life Sci. 2014;71(4):659-72. doi:10.1007/s00018-013-1457-3 . Perucci L O, Vago J P, Miles L A, Sousa L P. Crosstalk between the plasminogen/plasmin system and inflammation resolution. J Thromb Haemost. 2023;21(10):2666-78. doi:10.1016/j.jtha.2023.07.013 . Pu Z, Bao X, Xia S, Shao P, Xu Y. Serpine1 Regulates Peripheral Neutrophil Recruitment and Acts as Potential Target in Ischemic Stroke. J Inflamm Res. 2022;15:2649-63. doi:10.2147/JIR.S361072 . Szpecht D, Al-Saad S R, Karbowski L M, et al. Role of Fibronectin-1 polymorphism genes with the pathogenesis of intraventricular hemorrhage in preterm infants. Childs Nerv Syst. 2020;36(8):1729-36. doi:10.1007/s00381-020-04598-3 . Wang L, Deng L, Yuan R, et al. Association of Matrix Metalloproteinase 9 and Cellular Fibronectin and Outcome in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis. Front Neurol. 2020;11:523506. doi:10.3389/fneur.2020.523506 . Wang S, Zeng R, Lei L, Huang J. Angiotensinogen gene polymorphism and ischemic stroke in East Asians: A meta-analysis. Neural Regen Res. 2013;8(13):1228-35. doi:10.3969/j.issn.1673-5374.2013.13.004 Qin X, Li J, Wu T, et al. Overall and sex-specific associations between methylation of the ABCG1 and APOE genes and ischemic stroke or other atherosclerosis-related traits in a sibling study of Chinese population. Clin Epigenetics. 2019;11(1):189. doi: 10.1186/s13148-019-0784-0 . Satizabal CL, Samieri C, Davis-Plourde KL, et al. APOE and the association of fatty acids with the risk of stroke, coronary heart disease, and mortality. Stroke. 2018;49(12):2822-9. doi: 10.1161/STROKEAHA.118.022132 . Nie QQ, Zheng ZQ, Liao J, et al. SPP1/AnxA1/TIMP1 as essential genes regulate the inflammatory response in the acute phase of cerebral ischemia-reperfusion in rats. J Inflamm Res. 2022;15:4873-90. doi: 10.2147/JIR.S369690 . Lan Y, Zhang X, Liu S, et al. Fate mapping of Spp1 expression reveals age-dependent plasticity of disease-associated microglia-like cells after brain injury. Immunity. 2024;57(2). doi: 10.1016/j.immuni.2024.01.008 . Luo M, Qiu Z, Tang X, et al. Inhibiting Cyclin B1-treated Pontine Infarction by suppressing proliferation of SPP1+ microglia. Mol Neurobiol. 2023;60(4):1782-96. doi: 10.1007/s12035-022-03183-w . Morrissey D, Sun Y, Koilpillai S, Kropf J, Carlan S. Pseudo-thrombotic microangiopathy secondary to vitamin B12 deficiency. Case Rep Med. 2022;2022:7306070. doi: 10.1155/2022/7306070 . Lentz S. Mechanisms of thrombosis in hyperhomocysteinemia. Curr Opin Hematol. 1998;5(5):343-9. doi: 10.1097/00062752-199809000-00007 . Ma Y, Liu Y, Zhang Z, Yang GY. Significance of complement system in ischemic stroke: a comprehensive review. Aging Dis. 2019;10(2):429-62. doi: 10.14336/AD.2019.0119 . Yang P, Zhu Z, Zang Y, et al. Increased serum complement C3 levels are associated with adverse clinical outcomes after ischemic stroke. Stroke. 2021;52(3):868-77. doi: 10.1161/STROKEAHA.120.031715 . Zhu B, Zhou X. The study of PI3K/AKT pathway in lung cancer metastasis and drug resistance. Zhongguo Fei Ai Za Zhi = Chinese J Lung Cancer. 2011;14(8):689-94. doi: 10.3779/j.issn.1009-3419.2011.08.10 . Han Y, Sun Y, Peng S, et al. PI3K/AKT pathway: A potential therapeutic target in cerebral ischemia-reperfusion injury. Eur J Pharmacol. 2025;998:177505. doi: 10.1016/j.ejphar.2025.177505 . Khan H, Singh A, Singh Y, et al. Pharmacological modulation of PI3K/PTEN/Akt/mTOR/ERK signaling pathways in ischemic injury: a mechanistic perspective. Metab Brain Dis. 2025;40(3):131. doi: 10.1007/s11011-025-01543-8 . Li EY, Zhao PJ, Jian J, et al. Vitamin B1 and B12 mitigates neuron apoptosis in cerebral palsy by augmenting BDNF expression through MALAT1/miR-1 axis. Cell Cycle (Georgetown, Tex). 2019;18(21):2849-59. doi: 10.1080/15384101.2019.1638190 . Perez-Riverol Y, Bandla CJ, Kundu DJ, et al. The PRIDE database at 20 years: 2025 update. Nucleic Acids Res. 2025;53(D1):D543-D53. doi: 10.1093/nar/gkae1011 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Jul, 2025 Reviews received at journal 29 Jun, 2025 Reviews received at journal 10 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers invited by journal 04 Jun, 2025 Editor assigned by journal 02 Jun, 2025 Editor invited by journal 02 Jun, 2025 Submission checks completed at journal 31 May, 2025 First submitted to journal 19 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6698703","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":466713387,"identity":"86c5a8ad-f461-4b23-9dfa-28b16086f5ac","order_by":0,"name":"Li Zhou","email":"","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Zhou","suffix":""},{"id":466713389,"identity":"97fe5861-cda7-47dd-934b-debc4ff88885","order_by":1,"name":"Yanli Cai","email":"","orcid":"","institution":"Ziyang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanli","middleName":"","lastName":"Cai","suffix":""},{"id":466713391,"identity":"8f9e86ce-9e9f-4c93-b66e-fbdc8c3f93e3","order_by":2,"name":"Haiyun Wu","email":"","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haiyun","middleName":"","lastName":"Wu","suffix":""},{"id":466713393,"identity":"07549823-5225-4aaa-b3fb-78cb5f1a366e","order_by":3,"name":"Jiani Wang","email":"","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiani","middleName":"","lastName":"Wang","suffix":""},{"id":466713395,"identity":"6c9ba291-3748-48af-a20a-a56abf231a6a","order_by":4,"name":"Fangmei Xiao","email":"","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fangmei","middleName":"","lastName":"Xiao","suffix":""},{"id":466713397,"identity":"d56a42bd-1c4d-4bd1-b2d8-455d739a7914","order_by":5,"name":"Pingping Liu","email":"","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Pingping","middleName":"","lastName":"Liu","suffix":""},{"id":466713399,"identity":"35b6123d-a55f-4b00-99bc-55e661b2d75e","order_by":6,"name":"Qin Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYHACNoYPBhJybOzNB4jXwjijwsaYj+dYAvFamHnOpCXOk8hRIE69wY3kbQ942w6ntzHkMDD8qNhGWIvkjLRyA8m2w7ltDGcPMPacuU1YC79EjpmEIUgLY18CM2MbEVrYQFoSgQ4D+siAOC1gWw6cSUtgYyNWi2TPszLJhgobwzYetoSDRPnF4HjyNuk/BhLy8vMfH3zwo4IILQwCCQZw9gEi1AMB/wEDwopGwSgYBaNgZAMAqrk6AeDMCsIAAAAASUVORK5CYII=","orcid":"","institution":"the First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Qin","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-05-19 11:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6698703/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6698703/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-41564-6","type":"published","date":"2026-03-02T15:58:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84163856,"identity":"92befaf8-ee91-4efd-9daa-db91aaa7a24c","added_by":"auto","created_at":"2025-06-08 15:12:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":411689,"visible":true,"origin":"","legend":"\u003cp\u003eA flowchart of the network pharmacology analysis used in the study\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/7c87692bfaa8ccf9980470e0.png"},{"id":84164013,"identity":"e6b52da3-6725-422e-b247-623c3a17667d","added_by":"auto","created_at":"2025-06-08 15:20:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":304324,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of genes regulating ischemic stroke by cobalamin. (A) The common targets of cobalamin and ischemic stroke. (B) The common targets between proteomic targets-cobalamin and ischemic stroke targets. (C) Classification of the identified targets.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/0d40218b243d1e144737922f.png"},{"id":84163857,"identity":"002a77eb-3a52-4a2a-a017-aaa79aea2a66","added_by":"auto","created_at":"2025-06-08 15:12:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":700304,"visible":true,"origin":"","legend":"\u003cp\u003eThe enrichment analysis of PPI network. (\u003cstrong\u003eA\u003c/strong\u003e) The PPI network from STRING. (\u003cstrong\u003eB\u003c/strong\u003e) The visualization of PPI network. (\u003cstrong\u003eC\u003c/strong\u003e) The Cluster1 of PPI. (\u003cstrong\u003eD\u003c/strong\u003e) The GO-BP analysis of Cluster1. (\u003cstrong\u003eE\u003c/strong\u003e) The Cluster2 of PPI. (\u003cstrong\u003eF\u003c/strong\u003e) The GO-BP analysis of Cluster2. (\u003cstrong\u003eG\u003c/strong\u003e) The Cluster3 of PPI. (\u003cstrong\u003eH\u003c/strong\u003e) The GO-BP analysis of Cluster3.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/5817c53e3e81c9b3242dc777.png"},{"id":84164014,"identity":"91136d95-5e7b-4f0b-8ba5-b5b7bf9b8a8c","added_by":"auto","created_at":"2025-06-08 15:20:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":367624,"visible":true,"origin":"","legend":"\u003cp\u003eThe GO function enrichment analysis of core targets of cobalamin regulating ischemic stroke. (\u003cstrong\u003eA\u003c/strong\u003e) The hub genes of PPI network. (\u003cstrong\u003eB\u003c/strong\u003e) The BP analysis of hub genes. (\u003cstrong\u003eC\u003c/strong\u003e) The CC analysis of hub genes. (\u003cstrong\u003eD\u003c/strong\u003e) The MF analysis of hub genes\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/d7e36fc5d332f05955eea6f1.png"},{"id":84163863,"identity":"ac81f15e-26a7-491e-8f05-dc9dd4827780","added_by":"auto","created_at":"2025-06-08 15:12:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":389203,"visible":true,"origin":"","legend":"\u003cp\u003eThe GO function enrichment analysis of core targets of cobalamin regulating ischemic stroke. (\u003cstrong\u003eA\u003c/strong\u003e) The hub genes of PPI network. (\u003cstrong\u003eB\u003c/strong\u003e) The BP, CC and MF analysis of hub genes. (\u003cstrong\u003eC\u003c/strong\u003e) The c-net analysis of hub genes.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/33c1855a2670fb9e7ba87137.png"},{"id":84163866,"identity":"2fdcd775-37f3-4e11-a220-9600317af877","added_by":"auto","created_at":"2025-06-08 15:12:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":482732,"visible":true,"origin":"","legend":"\u003cp\u003eThe KEGG enrichment analysis identified the core pathways of cobalamin regulating ischemic stroke. (\u003cstrong\u003eA\u003c/strong\u003e) KEGG pathway analysis. (\u003cstrong\u003eB\u003c/strong\u003e) KEGG classification analysis. (\u003cstrong\u003eC\u003c/strong\u003e) KEGG pathway annotation analysis. (\u003cstrong\u003eD\u003c/strong\u003e) The network of targets-pathways (Note: the V shape represents-pathway, the yellow rectangle represents target). (\u003cstrong\u003eE\u003c/strong\u003e) A pathway–target network, with green nodes representing signaling pathways and yellow nodes indicating target genes.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/db6785cf0b9805f8a9d461c8.png"},{"id":84164018,"identity":"c929d75f-f82a-46ff-a510-f39d8f264ad6","added_by":"auto","created_at":"2025-06-08 15:20:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":844602,"visible":true,"origin":"","legend":"\u003cp\u003eThe 3-dimensional map of the binding sites between cobalamin and target proteins.\u003c/p\u003e\n\u003cp\u003eCobalamin is shown in red. Target proteins are displayed as cyan. The places where cobalamin and the target proteins are connected represent specific docking sites between cobalamin and target proteins.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/60c77f8a42c0c136725796ac.png"},{"id":104251134,"identity":"dfcfc5b5-a16a-44eb-8e22-2b4f495d5fc4","added_by":"auto","created_at":"2026-03-09 16:12:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4457002,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6698703/v1/b2b6f379-b1fa-4317-827a-59c3da328565.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling the Neuroprotective Mechanisms of Cobalamin in Ischemic Stroke: A Network Pharmacology and Molecular Docking Approach","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIschemic stroke accounts for approximately 70% of all stroke cases, resulting in over 10\u0026nbsp;million deaths annually worldwide (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/data/gho\u003c/span\u003e\u003cspan address=\"https://www.who.int/data/gho\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The pathological mechanisms of ischemic stroke involve multiple processes, including oxidative stress, inflammation, neuronal apoptosis, and disruption of the blood-brain barrier [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although thrombolytic therapies, such as recombinant tissue plasminogen activator (rt-PA), and endovascular thrombectomy have shown some success in early reperfusion, many patients still suffer from irreversible neurological deficits due to the narrow therapeutic time window and the risk of reperfusion injury [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, exploring neuroprotective agents with multi-target and multi-pathway regulatory effects has become a prominent area of research.\u003c/p\u003e \u003cp\u003eCobalamin (vitamin B12) is a water-soluble vitamin essential for one-carbon metabolism and myelin synthesis. Recent studies suggest that cobalamin may possess neuroprotective effects, including antioxidant, anti-inflammatory, anti-apoptotic, and mitochondrial function-regulating properties [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Given these diverse biological activities, cobalamin is hypothesized to mitigate several pathological processes associated with ischemic stroke [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, direct evidence supporting this hypothesis remains limited. Interestingly, cobalamin deficiency has been linked to various neurological disorders, such as cognitive impairment, autism, epilepsy, schizophrenia, depression, and migraines. Several studies have demonstrated that cobalamin supplementation can alleviate symptoms of these conditions [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Moreover, low serum cobalamin levels have been identified as an independent risk factor for ischemic stroke, with early supplementation showing potential to improve neurological outcomes in stroke patients [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTraditional experimental approaches are limited in fully elucidating the complex regulatory networks involved in ischemic stroke. In contrast, network pharmacology, which integrates target prediction, pathway analysis, and molecular docking, offers a systematic approach to explore the interactions between drugs, targets, and diseases, providing a novel perspective on the therapeutic potential of cobalamin [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study aims to: (1) identify the core targets of cobalamin in ischemic stroke through network pharmacology, (2) validate the binding affinity of cobalamin to key targets using molecular docking, and (3) propose a multi-target regulatory framework for future experimental validation. The findings are expected to provide a theoretical basis for nutritional interventions and drug development in the treatment of ischemic stroke. A flowchart of the study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e"},{"header":"2. Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Identification of targets of cobalamin\u003c/h2\u003e \u003cp\u003ePotential cobalamin targets were systematically retrieved from three databases in November 2024: DrugBank, GeneCards (retaining only targets with relevance scores\u0026thinsp;\u0026ge;\u0026thinsp;10) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and SwissTargetPrediction (using a probability cutoff\u0026thinsp;\u0026ge;\u0026thinsp;0.5) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. All gene names were converted to official HUGO Gene Nomenclature Committee symbols via UniProt, and duplicates were removed after cross-database integration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Identification of ischemic stroke disease targets\u003c/h2\u003e \u003cp\u003eDisease targets for ischemic stroke were identified by searching GeneCards, DisGeNET, and OMIM databases. Targets with a relevance score\u0026thinsp;\u0026ge;\u0026thinsp;10 in GeneCards were included in the analysis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A Venn diagram was used to merge the data from these databases, and duplicates were removed to identify common ischemic stroke targets. The potential therapeutic targets of cobalamin against ischemic stroke were then identified by cross-referencing these common ischemic stroke targets with known cobalamin targets using the Draw Venn Diagram online tool. Functional classification of these therapeutic targets was performed through the Panther database (accessed November 2024) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 PPI network construction and analysis\u003c/h2\u003e \u003cp\u003eThe common cobalamin targets for ischemic stroke were analyzed using the DAVID database (accessed December 2024) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis with Benjamini-Hochberg FDR correction. Terms with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, containing at least 5 targets, were considered significant. Protein-protein interaction (PPI) networks were constructed using the STRING database (Homo sapiens; minimum interaction score: 0.7) and visualized in Cytoscape using a force-directed layout. Hub genes were identified as the top 10% based on degree centrality. The integrated functional network was then constructed and visualized [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Molecular docking validation\u003c/h2\u003e \u003cp\u003eFirst, the crystal structure of the target protein was obtained from the PDB. PyMOL was used to remove water molecules, inorganic ions, and other non-essential components, and the processed structure was saved as the receptor file [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The ligand molecule was retrieved from the PubChem database, converted to PDB format using PyMOL, and subsequently prepared by adding hydrogen atoms and charges. The coordinates of the receptor\u0026rsquo;s active site were identified using AutoDockTools, and a grid box was defined by specifying the center and dimensions of the docking region. Molecular docking was then performed using AutoDock Vina [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. After docking, the binding conformation with the lowest binding energy was selected and analyzed. The receptor-ligand interactions were visualized using PyMOL [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The URLs employed in this section are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe websites software used in the study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDatabase, database and analysis platform\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWebsite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVersion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutoDock Vina_v1.2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vina.scripps.edu/\u003c/span\u003e\u003cspan address=\"https://vina.scripps.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV1.2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutoDockTools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://autodock.scripps.edu/resources/adt/\u003c/span\u003e\u003cspan address=\"https://autodock.scripps.edu/resources/adt/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV1.5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCytoscape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cytoscape.org/\u003c/span\u003e\u003cspan address=\"https://cytoscape.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV3.10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDAVID Bioinformatics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/tools.jsp\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/tools.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDraw Venn Diagram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.psb.ugent.be/webtools/Venn/\u003c/span\u003e\u003cspan address=\"http://bioinformatics.psb.ugent.be/webtools/Venn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisGeNet database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.disgenet.org/\u003c/span\u003e\u003cspan address=\"https://www.disgenet.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrugbank database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://go.drugbank.com/\u003c/span\u003e\u003cspan address=\"https://go.drugbank.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneCards database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMIM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omim.org/\u003c/span\u003e\u003cspan address=\"https://omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePubChem database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePymol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pymol.org/\u003c/span\u003e\u003cspan address=\"https://www.pymol.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV3.0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eString tool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwiss Target Prediction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swisstargetprediction.ch/\u003c/span\u003e\u003cspan address=\"http://www.swisstargetprediction.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniprot database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Target identification for GO and KEGG enrichment analysis of cobalamin intervention in ischemic stroke\u003c/h2\u003e \u003cp\u003eA total of 2,216 cobalamin-related targets were initially retrieved from the GeneCards, DrugBank, and SwissTargetPrediction databases. Simultaneously, 2,262 ischemic stroke-associated targets were identified by searching the GeneCards and OMIM databases. By intersecting the cobalamin-related targets with those associated with ischemic stroke, 828 common targets were obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Subsequently, a Venn diagram analysis between these 828 shared targets and our previously identified proteomic targets yielded 95 overlapping genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The functional categories of these 95 targets are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, including metabolite interconversion enzymes, protein-modifying enzymes, intercellular signaling molecules, transmembrane signal receptors, gene-specific transcriptional regulators, transporters, protein-binding activity modulators, cell adhesion molecules, defense/immunity proteins, and DNA metabolism proteins.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 PPI network construction\u003c/h2\u003e \u003cp\u003eThe overlapping targets were first submitted to the STRING database for PPI network analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The resulting network was then visualized using Cytoscape v3.10.1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). To further identify the core targets of cobalamin in the regulation of ischemic stroke, degree centrality (DC) was calculated using the CytoNCA plugin in Cytoscape. ALB, FN1, and CRP exhibited the highest DC values (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and were therefore selected as potential hub targets.\u003c/p\u003e \u003cp\u003eTo explore the modular organization of these targets, the MCODE plugin was applied for cluster analysis of the PPI network. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, Cluster 1 consisted of 40 nodes and 437 edges with a score of 22.410, Cluster 2 included 27 nodes and 149 edges with a score of 11.462, and Cluster 3 comprised 4 nodes and 6 edges with a score of 4. Functional enrichment analysis based on GO biological processes (GO-BP) was then performed for each cluster.\u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, proteins in Cluster 1 were primarily involved in the negative regulation of blood coagulation, acute-phase response, and blood coagulation. Proteins in Cluster 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF) were mainly associated with blood coagulation, inflammatory response, negative regulation of fibrinolysis, and complement activation via the alternative pathway. Cluster 3 proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH) were predominantly related to lipid transport, lipoprotein metabolic process, and triglyceride catabolic process.\u003c/p\u003e \u003cp\u003eCollectively, these results suggest that the core functional modules within the PPI network are mainly involved in coagulation cascades, inflammatory responses, and lipid metabolism. These biological processes are known to play critical roles in the pathogenesis and progression of ischemic stroke.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe evaluation of drug-likeness properties on key metabolites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDC value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTarget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDC value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPOE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLEP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMPO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePLG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e 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\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPOB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePXDN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eADIPOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPOH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSERPINE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTHBS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKNG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSERPINC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCCL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTIMP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePON1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTGFB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC4B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSERPINA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSERPINF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVCAM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMMP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo further investigate the functional core genes involved in the effects of cobalamin on ischemic stroke, we performed topological analysis and functional annotation of the PPI network using the CytoHubba plugin in the Cytoscape platform. This analysis identified 10 hub genes: AGT, CRP, PLG, VWF, ALB, FN1, TIMP1, APOE, SPP1, and SERPINE1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eSubsequently, GO enrichment analysis was conducted for these hub genes. In the BP category, the top five enriched terms were: symbiont-related biological processes, fibrinolysis, low-density lipoprotein particle remodeling, negative regulation of blood coagulation, and negative regulation of fibrinolytic processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In the Cellular Component (CC) category, the most significantly enriched terms included: platelet alpha granule lumen, extracellular space, extracellular region, extracellular exosome, and collagen-containing extracellular matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). For Molecular Function (MF) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), the top enriched terms were: protease binding, protein folding chaperone binding, receptor\u0026ndash;ligand activity, signaling receptor binding, and integrin binding.\u003c/p\u003e \u003cp\u003eNotably, network centrality analysis using CytoNCA showed a high degree of consistency with the results obtained from CytoHubba, further validating the critical role of these hub genes. These genes are primarily involved in the regulation of key biological processes such as the coagulation cascade, inflammatory response, and lipid metabolism, suggesting that they may play essential roles in the pathogenesis and progression of ischemic brain injury.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 GO enrichment analysis\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA illustrates the core hub genes potentially modulated by cobalamin in the context of ischemic stroke. GO enrichment analysis further revealed the involvement of these genes in key BP, CC, and MF. In the BP category, the top five enriched terms were: acute-phase response, interaction with symbiont, acute inflammatory response, platelet degranulation, and maintenance of location (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). For the CC category, the most significantly enriched components included: platelet alpha granule lumen, platelet alpha granule, blood microparticle, endoplasmic reticulum lumen, and secretory granule lumen. In the MF category, the top five enriched functions were: chaperone binding, macrolide binding, toxic substance binding, opsonin binding, and low-density lipoprotein particle binding. In addition, the c-net network diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) provides a visual overview of the functional associations among these hub genes. These findings suggest that cobalamin may exert protective effects in ischemic stroke by modulating key biological processes such as the inflammatory response, post-translational protein modification, complement activation, and lipoprotein particle binding.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 KEGG enrichment analysis\u003c/h2\u003e \u003cp\u003eKEGG pathway analysis provides key insights into the regulatory mechanisms underlying biological processes, thereby facilitating a more comprehensive understanding of the protective effects of cobalamin in ischemic stroke. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, cobalamin appears to exert its effects primarily through several critical signaling pathways, including the complement and coagulation cascades, cholesterol metabolism, and ECM\u0026ndash;receptor interaction pathways. Further KEGG enrichment analysis categorized these pathways into the following major functional groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC): Human disease-related pathways, such as the AGE-RAGE signaling pathway in diabetic complications, Staphylococcus aureus infection, proteoglycans in cancer, various infectious diseases, and endocrine and metabolic disorders; Organismal systems, encompassing pathways involved in the immune system, digestive system, aging, complement and coagulation cascades, and cholesterol metabolism; Cellular processes, including phagosome formation, focal adhesion, ferroptosis, the p53 signaling pathway, cell growth and death, transport and catabolism, and cell\u0026ndash;cell communication in eukaryotes; Environmental information processing, including ECM\u0026ndash;receptor interaction, cytokine\u0026ndash;cytokine receptor interaction, PI3K-Akt signaling pathway, signaling molecules and interaction, and signal transduction. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD illustrates a bubble plot of the top 20 significantly enriched pathways and their associated target genes, while Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE displays a pathway\u0026ndash;target network, with green nodes representing signaling pathways and yellow nodes indicating target genes. Taken together, these findings suggest that cobalamin may exert neuroprotective effects against ischemic stroke by modulating multiple pathways, particularly those involved in the complement and coagulation cascades, PI3K/Akt signaling, and other inflammation-related mechanisms. This highlights the potential of cobalamin as a multitarget therapeutic agent in the prevention and treatment of ischemic stroke.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Validation of interactions between cobalamin and potential targets through molecular docking\u003c/h2\u003e \u003cp\u003eTo evaluate the binding affinity of cobalamin with the proteins encoded by the 10 hub genes, molecular docking analysis was performed. The docking model with the lowest binding energy (ΔG) was recorded for each ligand\u0026ndash;target protein pair. Due to the lack of available docking sites for CRP and vWF in the AutoDock database, these two targets were excluded from the docking analysis. The docking results for the remaining eight target proteins are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Among them, cobalamin exhibited the strongest binding affinity with ALB and TIMP1, with ALB showing the most stable binding conformation. This was followed by PLG, FN1, AGT, SERPINE1, APOE, and SPP1. The specific binding sites between cobalamin and each target protein are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. These results suggest that cobalamin may exert its protective effects in ischemic stroke, at least in part, by stably interacting with key hub proteins involved in the pathophysiology of the disease.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCobalamin is shown in red. Target proteins are displayed as cyan. The places where cobalamin and the target proteins are connected represent specific docking sites between cobalamin and target proteins.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMolecular docking results of RES with target proteins\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTargets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDB ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnergy (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFull Fitness (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eΔGvdw (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5M3X\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6JE7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPOE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6V7M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4GH7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePLG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8UQ6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSERPINE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9PAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSPP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3DSF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalamin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTIMP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3V96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eWith the rapid development of the economy and society, the prevalence of ischemic stroke has gradually increased worldwide, leading to a heavy economic and social burden. Our previous clinical studies have identified cobalamin deficiency as a significant predictor of the occurrence and development of ischemic stroke, and early supplementation of cobalamin can improve patient outcomes [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, cobalamin is a bioactive compound with multiple beneficial effects, including neuroprotective roles in ischemic stroke, such as epigenetic regulation, mitochondrial function modulation, and the preservation of the neurovascular unit integrity. In this study, we used network pharmacology, bioinformatics analysis, and molecular docking simulations to explore potential therapeutic targets and mechanisms of cobalamin in ischemic stroke from multiple perspectives. The aim of this study is to investigate the potential therapeutic targets of cobalamin in the treatment of ischemic stroke.\u003c/p\u003e \u003cp\u003eFirst, we identified and validated a set of target genes closely associated with ischemic stroke, including ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1. These genes are critically involved in the pathophysiological processes of stroke, encompassing blood circulation, neuroprotection, inflammation, apoptosis, and vascular remodeling. Notably, our study demonstrated that cobalamin significantly modulated the aberrant expression of these genes, suggesting its potential therapeutic value in promoting neurological recovery following ischemic stroke.\u003c/p\u003e \u003cp\u003eALB is the most abundant circulating protein in the bloodstream and plays a multifaceted biological role. Its functions include binding and transporting a wide array of plasma drugs and endogenous molecules, maintaining colloid osmotic pressure, and exerting antioxidant, anticoagulant, and antiplatelet effects [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Previous studies have identified serum ALB levels as predictive biomarkers for both the occurrence of stroke and unfavorable outcomes following stroke. The PIVOTAL trial, which enrolled 2,141 participants, reported that lower ALB levels were independently associated with an increased risk of stroke over a median follow-up of 2.1 years, suggesting that ALB may be an important predictor of stroke risk in this population [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Similarly, findings from the CNSR-III, which analyzed data from 13,618 patients with acute ischemic stroke or transient ischemic attack, demonstrated that reduced serum ALB was an independent predictor of poor prognosis. Patients with ALB levels\u0026thinsp;\u0026lt;\u0026thinsp;35 g/L had a 37% higher risk of unfavorable functional outcomes at 3 months (adjusted OR\u0026thinsp;=\u0026thinsp;1.37) and a 113% higher risk of mortality (adjusted HR\u0026thinsp;=\u0026thinsp;2.13). Additionally, for every 10 g/L reduction in ALB, the risk of adverse outcomes further increased (OR\u0026thinsp;=\u0026thinsp;1.17, HR\u0026thinsp;=\u0026thinsp;1.86). These associations remained significant throughout the 1-year follow-up period, reinforcing the prognostic value of serum ALB in stroke patients [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTIMP1 is an endogenous inhibitor of matrix metalloproteinases (MMPs) and plays a crucial role in maintaining the integrity of the blood\u0026ndash;brain barrier [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. A cohort study by Zhong et al. reported that elevated serum TIMP1 levels at admission were associated with poor outcomes in stroke patients [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Existing evidence suggests that during acute brain injury, the endogenous expression of TIMP1 is insufficient to provide adequate neuroprotection, indicating the need for exogenous supplementation to achieve its full therapeutic potential. The neuroprotective mechanisms of TIMP1 may include: (1) inhibition of MMP-9-mediated blood-brain barrier disruption; (2) attenuation of inflammatory responses; and (3) promotion of tissue repair [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These findings support the rationale for developing TIMP1-targeted therapeutic strategies in stroke management.\u003c/p\u003e \u003cp\u003ePLG, a core component of the fibrinolytic system, not only facilitates thrombolysis but also modulates stroke progression through its roles in resolving inflammation, regulating immune cell migration, and providing neuroprotection. Dysregulation of PLG function has been closely associated with the onset and development of stroke [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Similarly, genetic polymorphisms in SERPINE1, which also acts as a chemotactic factor, have been associated with an increased risk of ischemic stroke and may exacerbate neuronal injury after ischemia-reperfusion by enhancing neutrophil infiltration [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Dysregulation of the coagulation-fibrinolysis axis may also contribute to cerebral hemorrhage by compromising vascular stability. For instance, polymorphisms in the FN1 gene-such as rs10202709-are significantly associated with the risk of intraventricular hemorrhage (IVH) in preterm infants, with carriers of the TT genotype being more prone to developing high-grade IVH [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Moreover, elevated plasma levels of cellular fibronectin, a splice variant of FN1, have been identified as a biomarker for hemorrhagic transformation and poor clinical outcomes in patients with acute ischemic stroke [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe M235T polymorphism in the AGT gene has been significantly associated with an increased risk of ischemic stroke\u0026mdash;particularly lacunar infarction in men-among Asian populations [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The underlying mechanisms may involve impaired regulation of blood pressure and accelerated atherosclerotic progression. APOE also contributes to stroke susceptibility through epigenetic regulation: its DNA methylation status may modulate key pathways involved in atherogenesis [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], while APOE genotype variations may further elevate cardiovascular risk by disrupting fatty acid metabolism [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSPP1 plays a critical role in orchestrating the inflammatory response during the acute phase of stroke. After cerebral ischemia\u0026ndash;reperfusion injury, SPP1 expression is significantly upregulated and is negatively regulated by miR-340-5p, highlighting its potential as a therapeutic target for anti-inflammatory strategies [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. SPP1⁺ macrophages have been shown to promote stroke-associated inflammation following aneurysmal rupture by driving phenotypic switching of vascular smooth muscle cells and facilitating collagen remodeling [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Furthermore, in the MCAO model, activation of SPP1⁺ microglia exacerbates pontine infarction, whereas inhibiting their activity confers neuroprotective effects [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eKEGG enrichment analysis revealed that the complement and coagulation cascades, along with the PI3K/Akt signaling pathway, are closely associated with the pathogenesis of stroke. Cobalamin deficiency contributes to increased stroke risk through multiple mechanisms. On one hand, it leads to abnormal accumulation of blood cells in the bone marrow. The resulting fragility of erythrocyte membranes predisposes them to intramedullary hemolysis, causing erythrocyte fragmentation and thrombocytopenia. The accumulation of hemolytic byproducts further damages the vascular endothelium [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. On the other hand, cobalamin deficiency promotes the buildup of toxic metabolites such as homocysteine and methylmalonic acid, which impair endothelial function through oxidative stress. This triggers platelet activation and upregulation of tissue factor expression, ultimately initiating the coagulation cascade and exacerbating vascular pathology [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The complement system exerts a dual role in ischemic stroke: while its activation aggravates cerebral ischemia/reperfusion injury and inflammatory responses, it also participates in neural repair processes. Clinical studies have shown that elevated levels of complement components, such as C3, are positively correlated with the degree of neurological impairment in patients with ischemic stroke [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], suggesting that the complement cascade may serve as a dynamic target for modulating both injury and repair mechanisms after stroke.\u003c/p\u003e \u003cp\u003eThe PI3K/Akt pathway plays a central neuroprotective role in stroke by regulating cell proliferation, survival, and metabolism. In cerebral ischemia/reperfusion injury, activation of this pathway alleviates oxidative and endoplasmic reticulum stress, suppresses inflammation, neuronal apoptosis, autophagy, and pyroptosis, and preserves the integrity of the blood\u0026ndash;brain barrier. These effects collectively contribute to a reduction in infarct volume and improvement in neurological function [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Notably, cobalamin supplementation has been shown to activate the PI3K/Akt pathway, leading to increased expression of brain-derived neurotrophic factor, inhibition of neuronal apoptosis, and attenuation of neurological damage in cerebral palsy models [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], further underscoring the therapeutic potential of this signaling axis in stroke.\u003c/p\u003e \u003cp\u003eThis study, through computational modeling, revealed that cobalamin may exert neuroprotective effects by modulating multiple key genes and signaling pathways, offering novel insights into the treatment of ischemic stroke. However, several limitations should be acknowledged. First, the findings have not yet been validated by in vitro, in vivo, or clinical studies. Second, no comparisons were made with existing stroke therapies, nor were combination interventions explored. Additionally, the optimal therapeutic dosage of cobalamin remains undefined. Future research should aim to experimentally validate the identified targets and pathways, investigate their underlying mechanisms, and assess both the clinical efficacy and safety of cobalamin-based interventions. These efforts will be crucial for advancing the translational potential of cobalamin in stroke therapy. Despite these limitations, the present study provides a valuable framework for further investigation into the mechanisms by which cobalamin may act in the treatment of stroke, representing an important contribution to the field.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this study, we employed a combination of network pharmacology, bioinformatics analysis, and molecular docking simulations to investigate the potential mechanisms of cobalamin in the treatment of ischemic stroke. Our findings indicate that cobalamin targets a broad range of molecules implicated in ischemic stroke, and its therapeutic effects may be mediated through the reversal of aberrant expression of key genes, including ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1. Moreover, the complement and coagulation cascades, as well as the PI3K/Akt signaling pathway, emerged as potential therapeutic pathways. These findings provide a comprehensive understanding of the molecular targets through which cobalamin may exert neuroprotective effects, offering a theoretical foundation for its clinical application in ischemic stroke treatment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAGT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensinogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPOE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eApolipoprotein E\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCellular Component\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-Reactive Protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDegree Centrality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFN1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibronectin 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntraventricular Hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCAO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMiddle Cerebral Artery Occlusion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMolecular Function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMPs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMatrix Metalloproteinases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePDB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein Data Bank\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlasminogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ert-PA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRecombinant Tissue Plasminogen Activator\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSERPINE1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSerpin Family E Member 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPP1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSecreted Phosphoprotein 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTIMP1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTissue Inhibitor of Metalloproteinases 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVWF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVon Willebrand Factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all investigators contributed to this article. We also give thanks to all patients enrolled in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analysed during this study are included in the websites mentioned above. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository [57] with the dataset identifier PXD062264. The data not published within this article are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 82171456) awarded to Qin Yang and the 2023 Research Planning Project of the Sichuan Provincial Psychological Society (No. SCSXLXH2023034) awarded to Pingping Liu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQ.Y. contributed to the study conception and design and provided critical revisions and editorial input for the manuscript. L. Z. and Y.C. jointly drafted the initial version of the manuscript and developed the primary tables and figures. H.W. and J.W. performed the data analysis. F.X. and P.L. were responsible for data acquisition from the relevant datasets. All authors were involved in the study design, contributed to manuscript revisions, and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eQin C, Dong M-H, Tang Y, et al. The foam cell-derived exosomal miRNA novel-3 drives neuroinflammation and ferroptosis during ischemic stroke. Nat Aging. 2024;4(12):1845\u0026ndash;61. doi:10.1038/s43587-024-00727-8 .\u003c/li\u003e\n\u003cli\u003eQin C, Yang S, Chu Y-H, et al. 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Nucleic Acids Res. 2025;53(D1):D543-D53. doi: 10.1093/nar/gkae1011\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ischemic stroke, Cobalamin, Network pharmacology, Molecular Docking","lastPublishedDoi":"10.21203/rs.3.rs-6698703/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6698703/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aims to systematically elucidate the multi-target mechanisms of cobalamin in the treatment of ischemic stroke using network pharmacology and molecular docking techniques.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe screened databases to identify the targets of cobalamin and performed intersection analysis with ischemic stroke-related targets to construct a \"drug-target-disease\" interaction network. Gene Ontology (GO) and KEGG pathway enrichment analyses were conducted to identify key biological processes and signaling pathways. Additionally, molecular docking was employed to assess the binding affinity between cobalamin and core targets.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 95 therapeutic targets of cobalamin for ischemic stroke were identified. Based on Cytoscape and molecular docking, we selected ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1, which exhibited strong binding affinity. GO analysis revealed that cobalamin primarily regulates inflammatory responses, post-translational protein modifications, complement binding, and lipoprotein particle binding. KEGG pathway analysis indicated that complement and coagulation cascades, PI3K/AKT, and other inflammation-related pathways are the major signaling pathways involved in the treatment of ischemic stroke by cobalamin.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study is the first to elucidate the molecular mechanisms through which cobalamin exerts anti-inflammatory and neuroprotective effects via multi-target and multi-pathway actions from a computational biology perspective. These findings provide new theoretical insights for the treatment of ischemic stroke with cobalamin, though further experimental validation is required.\u003c/p\u003e","manuscriptTitle":"Unraveling the Neuroprotective Mechanisms of Cobalamin in Ischemic Stroke: A Network Pharmacology and Molecular Docking Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-08 15:12:46","doi":"10.21203/rs.3.rs-6698703/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-03T06:02:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-29T16:45:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-10T19:49:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196930914891426765541103040659411393372","date":"2025-06-05T02:03:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333562193542425131436744276258097866045","date":"2025-06-05T01:07:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-05T01:04:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-03T01:20:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-02T08:34:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-31T17:03:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-05-19T11:49:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"473187de-ed1c-4251-b082-130a484de525","owner":[],"postedDate":"June 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49551980,"name":"Health sciences/Neurology"},{"id":49551982,"name":"Health sciences/Neurology/Neurological disorders/Stroke"}],"tags":[],"updatedAt":"2026-03-09T16:08:15+00:00","versionOfRecord":{"articleIdentity":"rs-6698703","link":"https://doi.org/10.1038/s41598-026-41564-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-02 15:58:04","publishedOnDateReadable":"March 2nd, 2026"},"versionCreatedAt":"2025-06-08 15:12:46","video":"","vorDoi":"10.1038/s41598-026-41564-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-41564-6","workflowStages":[]},"version":"v1","identity":"rs-6698703","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6698703","identity":"rs-6698703","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}