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Neuroprotective mechanisms of cobalamin in ischemic stroke insights from network pharmacology and molecular simulations
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  • Published: 02 March 2026

Neuroprotective mechanisms of cobalamin in ischemic stroke insights from network pharmacology and molecular simulations

  • Li Zhou1 na1,
  • Yanli Cai2 na1,
  • Haiyun Wu1,
  • Jiani Wang1,
  • Fangmei Xiao1,
  • Pingping Liu1 &
  • …
  • Qin Yang1 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Neurology
  • Stroke

Abstract

This study aims to systematically investigate the multi-target mechanisms of cobalamin in the treatment of ischemic stroke using network pharmacology and molecular docking approaches. We screened databases to identify the targets of cobalamin and performed intersected with with ischemic stroke-related targets to construct a “drug-target-disease” interaction network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to identify key biological processes and signaling pathways. Additionally, molecular docking simulations were performed to assess the binding affinity between cobalamin and hub proteins. Molecular dynamics (MD) simulations were used to assess the stability of the protein–ligand complexes over a 500 ns simulation period. Additionally, ADME (Absorption, Distribution, Metabolism, Excretion) and blood–brain barrier (BBB) permeability predictions were made using ADMETlab 3.0 and admetSAR 3.0. A total of 95 therapeutic targets of cobalamin for ischemic stroke were identified. Network analysis and molecular docking highlighted eight core targets—ALB, TIMP1, PLG, FN1, AGT, SERPINE1, APOE, and SPP1—with high binding affinities to cobalamin. GO analysis suggested that cobalamin regulates inflammatory responses, post-translational modifications, complement binding, and lipoprotein particle binding. KEGG analysis identified complement and coagulation cascades, the PI3K/AKT pathway, and inflammation-related signaling as central to its therapeutic effects. Molecular docking showed strong binding to ALB and TIMP1, which was further confirmed by MD simulations, with minimal conformational changes. The PLG-cobalamin complex exhibited more fluctuations. ADME analysis revealed low passive permeability, particularly across the blood–brain barrier, but moderate distribution and high plasma protein binding. This study provides evidence that cobalamin may offer neuroprotective effects in ischemic stroke by interacting with key target proteins involved in coagulation, inflammation, and lipid metabolism. The findings highlight the potential of cobalamin as a therapeutic agent, although its limited ability to cross the blood–brain barrier may restrict its oral use. Further experimental validation and development of suitable delivery methods are needed to fully realize cobalamin’s potential in stroke therapy.

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 repository71 with the dataset identifier PXD062264. The data not published within this article are available from the corresponding author on reasonable request.

Abbreviations

WHO:

World Health Organization

rt-PA:

Recombinant tissue plasminogen activator

ALB:

Albumin

TIMP1:

Tissue inhibitor of metalloproteinases 1

PLG:

Plasminogen

FN1:

Fibronectin 1

AGT:

Angiotensinogen

SERPINE1:

Serpin family E member 1

APOE:

Apolipoprotein E

SPP1:

Secreted Phosphoprotein 1

PPI:

Protein-protein interaction

GO:

Gene ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

FDR:

False discovery rate

DAVID:

Database for Annotation, Visualization, and Integrated Discovery

STRING:

Search Tool for the Retrieval of Interacting Genes

MCC:

Maximal clique centrality

BP:

Biological process

CC:

Cellular component

MF:

Molecular function

MCODE:

Molecular Complex Detection

CytoNCA:

Cytoscape Network Centrality Analysis

VWF:

Von Willebrand factor

CRP:

C-reactive protein

PME:

Particle Mesh Ewald

NVT:

Number of particles (N), Volume (V), and Temperature (T) ensemble

NPT:

Number of particles (N), Pressure (P), and Temperature (T) ensemble

ADMET:

Absorption, Distribution, Metabolism, Excretion, and Toxicity

BBB:

Blood–brain barrier

TPSA:

Topological polar surface area

HIA:

Human intestinal absorption

CGenFF:

CHARMM General Force Field

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

Rg:

Radius of gyration

SASA:

Solvent accessible surface area

MD:

Molecular dynamics

PDB:

Protein Data Bank

MCAO:

Middle Cerebral Artery Occlusion

tHcy:

Total homocysteine

hs-CRP:

High-sensitivity C-reactive protein

References

  1. Qin, C. et al. The foam cell-derived exosomal miRNA Novel-3 drives neuroinflammation and ferroptosis during ischemic stroke. Nat. Aging 4(12), 1845–1861 (2024).

    Google Scholar 

  2. Qin, C. et al. Signaling pathways involved in ischemic stroke: molecular mechanisms and therapeutic interventions. Signal Transduct Target Ther. 7(1), 215 (2022).

    Google Scholar 

  3. GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 20(10), 795–820 (2021).

  4. Roth, W. & Mohamadzadeh, M. Vitamin B12 and gut-brain homeostasis in the pathophysiology of ischemic stroke. EBioMedicine 73, 103676 (2021).

    Google Scholar 

  5. Sands, T., Jawed, A., Stevenson, E., Smith, M. & Jawaid, I. Vitamin B12 deficiency: NICE guideline summary. BMJ 385, q1019 (2024).

    Google Scholar 

  6. Zhou, L., Song, X., Wang, J., Tan, Y. & Yang, Q. Effects of vitamin B12 deficiency on risk and outcome of ischemic stroke. Clin. Biochem. 118, 110591 (2023).

    Google Scholar 

  7. Mitra, S., Natarajan, R., Ziedonis, D. & Fan, X. Antioxidant and anti-inflammatory nutrient status, supplementation, and mechanisms in patients with schizophrenia. Prog. Neuropsychopharmacol. Biol. Psychiatry 78, 1–11 (2017).

    Google Scholar 

  8. Li, Z., Xue, B., Jiagui, H., Yongjun, T. & Qin, Y. Vitamin B12 supplementation improves cognitive function in middle aged and elderly patients with cognitive impairment. Nutr. Hosp. 40(4), 762–769 (2023).

    Google Scholar 

  9. Reynolds, E. H. Vitamin B12, folic acid, and the nervous system. Lancet Neurol. 5(11), 949–960 (2006).

    Google Scholar 

  10. Zhou, L. et al. Low vitamin B12 levels may predict the risk of ischemic stroke: A cross-sectional study. J. Clin. Neurosci. 117, 125–135 (2023).

    Google Scholar 

  11. Chen, X. et al. Low concentration of serum vitamin B12 may be a strong predictor of large-artery atherosclerosis stroke: A case-control study. Clin. Biochem. 131–132, 110813 (2024).

    Google Scholar 

  12. Zhou, L. et al. Serum levels of vitamin B12 combined with folate and plasma total homocysteine predict ischemic stroke disease: A retrospective case-control study. Nutr. J. 23(1), 76 (2024).

    Google Scholar 

  13. Nogales, C. et al. Network pharmacology: Curing causal mechanisms instead of treating symptoms. Trends Pharmacol. Sci. 43(2), 136–150 (2022).

    Google Scholar 

  14. Safran, M. et al. GeneCards Version 3: the human gene integrator. Database (Oxford). 2010, baq020 (2010).

    Google Scholar 

  15. Knox, C. et al. DrugBank 6.0: the DrugBank Knowledgebase for 2024. Nucleic Acids Res. 52(D1), D1265–D1275 (2024).

    Google Scholar 

  16. Mi, H. et al. PANTHER version 16: a revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Res. 49(D1), D394–D403 (2021).

    Google Scholar 

  17. Kanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. & Ishiguro-Watanabe, M. KEGG: Biological systems database as a model of the real world. Nucleic Acids Res. 53(D1), D672–D677 (2025).

    Google Scholar 

  18. Kanehisa, M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 28(11), 1947–1951 (2019).

    Google Scholar 

  19. Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28(1), 27–30 (2000).

    Google Scholar 

  20. Dennis, G. et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 4(5), P3 (2003).

    Google Scholar 

  21. Jiménez-García, N., de la Torre Lima, J. & García Alegría, J. The role of aspirin as antiaggregant therapy in primary prevention. An update. Med Clin (Barc). 153(8), 326–331 (2019).

    Google Scholar 

  22. Trott, O. & Olson, A. J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 31(2), 455–461 (2010).

    Google Scholar 

  23. Mooers, B. H. M. & Brown, M. E. Templates for writing PyMOL scripts. Protein Sci. 30(1), 262–269 (2021).

    Google Scholar 

  24. Qin, X. 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 11(1), 189 (2019).

    Google Scholar 

  25. Satizabal, C. L. et al. APOE and the association of fatty acids with the risk of stroke, coronary heart disease, and mortality. Stroke 49(12), 2822–2829 (2018).

    Google Scholar 

  26. Nie, Q. 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. 15, 4873–4890 (2022).

    Google Scholar 

  27. Lan, Y. et al. Fate mapping of Spp1 expression reveals age-dependent plasticity of disease-associated microglia-like cells after brain injury. Immunity 57(2), 291–307 (2024).

    Google Scholar 

  28. Luo, M. et al. Inhibiting Cyclin B1-treated Pontine Infarction by Suppressing Proliferation of SPP1+ Microglia. Mol Neurobiol. 60(4), 1782–1796 (2023).

    Google Scholar 

  29. Morrissey, D., Sun, Y., Koilpillai, S., Kropf, J. & Carlan, S. Pseudo-thrombotic microangiopathy secondary to vitamin B12 deficiency. Case Rep Med. 2022, 7306070 (2022).

    Google Scholar 

  30. Lentz, S. R. Mechanisms of thrombosis in hyperhomocysteinemia. Curr. Opin. Hematol. 5(5), 343–349 (1998).

    Google Scholar 

  31. Ma, Y., Liu, Y., Zhang, Z. & Yang, G. Significance of complement system in ischemic stroke: A comprehensive review. Aging Dis. 10(2), 429–462 (2019).

    Google Scholar 

  32. Yang, P. et al. Increased serum complement C3 levels are associated with adverse clinical outcomes after ischemic stroke. Stroke 52(3), 868–877 (2021).

    Google Scholar 

  33. Zhu, B. & Zhou, X. [The study of PI3K/AKT pathway in lung cancer metastasis and drug resistance]. Zhongguo Fei Ai Za Zhi 14(8), 689–694 (2011).

    Google Scholar 

  34. Han, Y. et al. PI3K/AKT pathway: A potential therapeutic target in cerebral ischemia-reperfusion injury. Eur J Pharmacol. 998, 177505 (2025).

    Google Scholar 

  35. Khan, H. et al. Pharmacological modulation of PI3K/PTEN/Akt/mTOR/ERK signaling pathways in ischemic injury: A mechanistic perspective. Metab. Brain Dis. 40(3), 131–149 (2025).

    Google Scholar 

  36. Li, E. et al. Vitamin B1 and B12 mitigates neuron apoptosis in cerebral palsy by augmenting BDNF expression through MALAT1/miR-1 axis. Cell Cycle 18(21), 2849–2859 (2019).

    Google Scholar 

  37. Perez-Riverol, Y. et al. The PRIDE database at 20 years: 2025 Update. Nucleic Acids Res. 53(D1), D543–D553 (2025).

    Google Scholar 

  38. Sanner, M. F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 17(1), 57–61 (1999).

    Google Scholar 

  39. Shannon, P. et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13(11), 2498–2504 (2003).

    Google Scholar 

  40. Sherman, B. T. et al. DAVID: A web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 50(W1), W216–W221 (2022).

    Google Scholar 

  41. Piñero, J. et al. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res. 48(D1), D845–D855 (2020).

    Google Scholar 

  42. Kanehisa, M., Furumichi, M., Sato, Y., Ishiguro-Watanabe, M. & Tanabe, M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 49(D1), D545–D551 (2021).

    Google Scholar 

  43. Wishart, D. S. et al. DrugBank: A knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 36(Database issue), D901–D906 (2008).

    Google Scholar 

  44. Amberger, J. S., Bocchini, C. A., Schiettecatte, F., Scott, A. F. & Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res. 43(Database issue), D789–D798 (2015).

    Google Scholar 

  45. Seeliger, D. & de Groot, B. L. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J. Comput. Aided Mol. Des. 24(5), 417–422 (2010).

    Google Scholar 

  46. Tian, W., Chen, C., Lei, X., Zhao, J. & Liang, J. CASTp 3.0: Computed atlas of surface topography of proteins. Nucleic Acids Res. 46(W1), W363–W367 (2018).

    Google Scholar 

  47. Szklarczyk, D. et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51(D1), D638–D646 (2023).

    Google Scholar 

  48. Daina, A., Michielin, O. & Zoete, V. SwissTargetPrediction: Updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 47(W1), W357–W364 (2019).

    Google Scholar 

  49. UniProt Consortium. UniProt: the universal protein knowledgebase in 2023. Nucleic Acids Res. 51(D1), D523–D531 (2023).

  50. Dong, J. et al. ADMETlab: A platform for systematic ADMET evaluation based on a comprehensively collected ADMET database. J. Cheminform 10(1), 29 (2018).

    Google Scholar 

  51. Yang, H. et al. admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties. Bioinformatics 35(6), 1067–1069 (2019).

    Google Scholar 

  52. Cheng, F. et al. AdmetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. J. Chem. Inf. Model. 52(11), 3099–3105 (2012).

    Google Scholar 

  53. Vanommeslaeghe, K. et al. CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J Comput Chem. 31(4), 671–690 (2010).

    Google Scholar 

  54. Dolezal, R. et al. Towards understanding the mechanism of action of antibacterial N-alkyl-3-hydroxypyridinium salts: Biological activities, molecular modeling and QSAR studies. Eur J Med Chem. 121, 699–711 (2016).

    Google Scholar 

  55. Childers, M. C. & Daggett, V. Validating molecular dynamics simulations against experimental observables in light of underlying conformational ensembles. J. Phys. Chem. B 122(26), 6673–6689 (2018).

    Google Scholar 

  56. He, K. et al. Folate, vitamin B6, and B12 intakes in relation to risk of stroke among men. Stroke 35(1), 169–174 (2003).

    Google Scholar 

  57. Yuan, M., Wang, B. & Tan, S. Mecobalamin and early functional outcomes of ischemic stroke patients with H-type hypertension. Rev. Assoc. Med. Bras. (1992) 64(5), 428–432 (2018).

    Google Scholar 

  58. Zoanni, B. et al. Novel insights about albumin in cardiovascular diseases: Focus on heart failure. Mass Spectrom Rev. 42(4), 1113–1128 (2023).

    Google Scholar 

  59. Lam, F. W. et al. Histone induced platelet aggregation is inhibited by normal albumin. Thromb. Res. 132(1), 69–76 (2013).

    Google Scholar 

  60. Paar, M. et al. Anticoagulant action of low, physiologic, and high albumin levels in whole blood. PLoS ONE 12(8), e0182997 (2017).

    Google Scholar 

  61. Mark, P. B. et al. Stroke in hemodialysis patients randomized to different intravenous iron strategies: A prespecified analysis from the PIVOTAL Trial. Kidney360 2(11), 1761–1769 (2021).

    Google Scholar 

  62. Zhou, H. et al. Low serum albumin levels predict poor outcome in patients with acute ischaemic stroke or transient ischaemic attack. Stroke Vasc Neurol. 6(3), 458–466 (2021).

    Google Scholar 

  63. Abu-Zahab, Z. A. et al. Frequency of comorbid diseases with high serum Vitamin B12 levels in patients attending King Salman Medical City (KSAMC), at Madinah. Int J Health Sci (Qassim). 19(1), 15–21 (2025).

    Google Scholar 

  64. Liu, 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. 41(12), 1547–1556 (2020).

    Google Scholar 

  65. Zhong, C. et al. Tissue inhibitor metalloproteinase-1 and clinical outcomes after acute ischemic stroke. Neurology 93(18), e1675–e1685 (2019).

    Google Scholar 

  66. Ries, C. Cytokine functions of TIMP-1. Cell. Mol. Life Sci. 71(4), 659–672 (2014).

    Google Scholar 

  67. Perucci, L. O., Vago, J. P., Miles, L. A. & Sousa, L. P. Crosstalk between the plasminogen/plasmin system and inflammation resolution. J. Thromb. Haemost. 21(10), 2666–2678 (2023).

    Google Scholar 

  68. 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. 15, 2649–2663 (2022).

    Google Scholar 

  69. Szpecht, D. et al. Role of Fibronectin-1 polymorphism genes with the pathogenesis of intraventricular hemorrhage in preterm infants. Childs Nerv. Syst. 36(8), 1729–1736 (2020).

    Google Scholar 

  70. Wang, L. et al. Association of matrix metalloproteinase 9 and cellular fibronectin and outcome in acute ischemic stroke: A systematic review and meta-analysis. Front. Neurol. 11, 523506 (2020).

    Google Scholar 

  71. Wang, S., Zeng, R., Lei, L. & Huang, J. Angiotensinogen gene polymorphism and ischemic stroke in East Asians: A meta-analysis. Neural Regen. Res. 8(13), 1228–1235 (2013).

    Google Scholar 

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Acknowledgements

We thank all investigators contributed to this article. We also give thanks to all patients enrolled in this study.

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 information

Author notes

  1. Li Zhou and Yanli Cai contributed equally to this work and are co-first authors.

Authors and Affiliations

  1. Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, 1 Youyi Road, Yuzhong District, Chongqing, 400016, China

    Li Zhou, Haiyun Wu, Jiani Wang, Fangmei Xiao, Pingping Liu & Qin Yang

  2. Outpatient Department, West China Hospital of Sichuan University-Ziyang Hospital, (Ziyang Central Hospital), Ziyang, Sichuan, 641300, China

    Yanli Cai

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  1. Li Zhou
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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. 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.

Corresponding author

Correspondence to Qin Yang.

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Zhou, L., Cai, Y., Wu, H. et al. Neuroprotective mechanisms of cobalamin in ischemic stroke insights from network pharmacology and molecular simulations. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41564-6

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  • Received: 19 May 2025

  • Accepted: 20 February 2026

  • Published: 02 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-41564-6

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Keywords

  • Ischemic stroke
  • Cobalamin
  • Network pharmacology
  • Molecular docking
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