A network pharmacology approach validates resveratrol’s in vivo neuroprotective effects against neurotoxic metals-induced cognitive decline

Main Article Content

Abida Zulfiqar
Saima Bashir
Aymen Tahir
Saadia Zahid
Touqeer Ahmed

Abstract

Objective: To investigate the neuroprotective effects of resveratrol against combined neurotoxicity induced by aluminum (Al), lead (Pb), and arsenic (As) using integrated in-silico and in-vivo approaches.


Methods: Thirty adult male Sprague–Dawley rats (10–12 weeks; 180–250 g) were randomized into three groups (n=10 each): control, metal mixture (Al+As+Pb; 25 mg/kg/day, oral), and metal mixture plus resveratrol (20 mg/kg/day in feed) for 60 days. Cognitive performance was assessed using the Y-maze and Morris water maze (MWM). Gene expression of synaptophysin, PSD-95, and CaMKIV in cortex and hippocampus was evaluated by qPCR using the 2^-ΔΔCT method. In-silico target prediction and network pharmacology were performed using Swiss Target Prediction, CTD, and GeneCards; intersecting targets were analyzed via STRING and Cytoscape, followed by GO/KEGG enrichment (DAVID/ShinyGO). Molecular docking (AutoDock Vina) assessed binding of resveratrol with IL6, TNF, IL1-β, synaptophysin, CaMKIV, and PSD-95.


Results: Network pharmacology identified 269 intersecting targets; hub genes included IL6, TNF, and IL1-β. Enrichment analysis highlighted pathways related to inflammation, apoptosis regulation, PI3K-Akt, MAPK, and neurodegeneration. Docking showed strong affinity with CaMKIV (−8.1 kcal/mol) and moderate affinity with IL6 (−6.8), IL1-β (−6.9), and PSD-95 (−6.5). In-vivo, the metal mixture impaired memory in Y-maze and MWM, while resveratrol significantly improved performance. Metal exposure downregulated synaptophysin, PSD-95, and CaMKIV expression in cortex and hippocampus; resveratrol partially to markedly restored expression.


Conclusion: Resveratrol mitigated Al/As/Pb-induced neurotoxicity, improving cognitive performance and synaptic gene expression, potentially through multi-target modulation of inflammatory and neurodegenerative pathways.

Article Details

How to Cite
Zulfiqar, Abida, et al. “A Network Pharmacology Approach Validates resveratrol’s in Vivo Neuroprotective Effects Against Neurotoxic Metals-Induced Cognitive Decline”. KHYBER MEDICAL UNIVERSITY JOURNAL, vol. 17, no. 4, Dec. 2025, pp. 417-31, doi:10.35845/kmuj.2025.24075.
Section
Original Articles

Funding data

References

1. Kim JJ, Kim YS, Kumar V. Heavy metal toxicity: an update of chelating therapeutic strategies. J Trace Elem Med Biol 2019;54:226-31. https://doi.org/10.1016/j.jtemb.2019.05.003

2. Ortega DR, Esquivel DFG, Ayala TB, Pineda B, Manzo SG, Quino JM, et al. Cognitive impairment induced by lead exposure during lifespan: mechanisms of lead neurotoxicity. Toxics 2021;9(2):23. https://doi.org/10.3390/toxics9020023

3. Andrade V, Aschner M, Marreilha Dos Santos A. Neurotoxicity of metal mixtures. In: Aschner M, Costa LG, editors. Neurotoxicity of metals. Cham: Springer; 2017. pp. 227-65. https://doi.org/10.1007/978-3-319-60189-2_12

4. Lucchini RG, Aschner M, Bellinger DC, Caito SW. Neurotoxicology of metals. In: Nordberg GF, Costa M, editors. Handbook of toxicology of metals. 4th ed. Amsterdam: Elsevier; 2015. pp. 299-311. https://doi.org/10.1016/B978-0-444-59453-2.00015-9

5. Karri V, Schuhmacher M, Kumar V. Heavy metals (Pb, Cd, As and MeHg) as risk factors for cognitive dysfunction: a general review of metal mixture mechanism in brain. Environ Toxicol Pharmacol 2016;48:203-13. https://doi.org/10.1016/j.etap.2016.09.016

6. Yu H, Liao Y, Li T, Cui Y, Wang G, Zhao F, et al. Alterations of synaptic proteins in the hippocampus of mouse offspring induced by developmental lead exposure. Mol Neurobiol 2016;53(10):6786-98. https://doi.org/10.1007/s12035-015-9597-0

7. Wang Y, Li S, Piao F, Hong Y, Liu P, Zhao Y. Arsenic down-regulates the expression of Camk4, an important gene related to cerebellar LTD in mice. Neurotoxicol Teratol 2009;31(5):318-22. https://doi.org/10.1016/j.ntt.2009.04.064

8. Asghar H, Ahmed T. Comparative study of time-dependent aluminum exposure and post-exposure recovery shows better improvement in synaptic changes and neuronal pathology in rat brain after short-term exposure. Neurochem Res 2023;48(9):2731-53. https://doi.org/10.1007/s11064-023-03936-6

9. Wang W, Wang S, Liu T, Ma Y, Huang S, Lei L, et al. Resveratrol: multi-targets mechanism on neurodegenerative diseases based on network pharmacology. Front Pharmacol 2020;11:694. https://doi.org/10.3389/fphar.2020.00694

10. Wang W, Liu T, Yang L, Ma Y, Dou F, Shi L, et al. Study on the multi-targets mechanism of triphala on cardio-cerebral vascular diseases based on network pharmacology. Biomed Pharmacother 2019;116:108994. https://doi.org/10.1016/j.biopha.2019.108994

11. Richard T, Pawlus AD, Iglésias ML, Pedrot E, Waffo‐Teguo P, Mérillon JM, et al. Neuroprotective properties of resveratrol and derivatives. Ann N Y Acad Sci 2011;1215(1):103-8. https://doi.org/10.1111/j.1749-6632.2010.05865.x

12. Zhang YM, Wei RM, Zhang MY, Zhang KX, Zhang JY, Fang SK, et al. Resveratrol ameliorates maternal immune activation-associated cognitive impairment in adult male offspring by relieving inflammation and improving synaptic dysfunction. Front Behav Neurosci 2023;17:1271653. https://doi.org/10.3389/fnbeh.2023.1271653

13. Wang R, Wu Z, Liu M, Wu Y, Li Q, Ba Y, et al. Resveratrol reverses hippocampal synaptic markers injury and SIRT1 inhibition against developmental Pb exposure. Brain Res 2021;1767:147567. https://doi.org/10.1016/j.brainres.2021.147567

14. Bartlett J. Introduction to sample size calculation using G*Power. Eur J Soc Psychol 2019:1-35.

15. Mélard G. On the accuracy of statistical procedures in Microsoft Excel 2010. Comput Stat 2014;29(5):1095-128. https://doi.org/10.1007/s00180-014-0482-5

16. Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res 2016;44(D1):D1202-13. https://doi.org/10.1093/nar/gkv951

17. Ru J, Li P, Wang J, Zhou W, Li B, Huang C, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014;6:13. https://doi.org/10.1186/1758-2946-6-13

18. Daina A, Michielin O, Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res 2019;47(W1):W357-64. https://doi.org/10.1093/nar/gkz382

19. Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, et al. The Comparative Toxicogenomics Database: update 2019. Nucleic Acids Res 2019;47(D1):D948-54. https://doi.org/10.1093/nar/gky868

20. Safran M, Dalah I, Alexander J, Rosen N, Iny Stein T, Shmoish M, et al. GeneCards Version 3: the human gene integrator. Database (Oxford) 2010;2010:baq020. https://doi.org/10.1093/database/baq020

21. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res 2015;43(D1):D447-52. https://doi.org/10.1093/nar/gku1003

22. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003;13(11):2498-504. https://doi.org/10.1101/gr.1239303

23. Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol 2003;4:1-11.

24. Ge SX, Jung D, Yao R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics 2020;36(8):2628-9. https://doi.org/10.1093/bioinformatics/btz931

25. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 2009;30(16):2785-91. https://doi.org/10.1002/jcc.21256

26. Bromley-Brits K, Deng Y, Song W. Morris water maze test for learning and memory deficits in Alzheimer's disease model mice. J Vis Exp 2011;(53):2920. https://doi.org/10.3791/2920

27. Conrad CD, Galea LA, Kuroda Y, McEwen BS. Chronic stress impairs rat spatial memory on the Y maze, and this effect is blocked by tianeptine pretreatment. Behav Neurosci 1996;110(6):1321. https://doi.org/10.1037//0735-7044.110.6.1321

28. Ishaq S, Siyar S, Basri R, Liaqat A, Hameed A, Ahmed T. Neuroprotective effects of shogaol in metals (Al, As and Pb) and high-fat diet-induced neuroinflammation and behavior in mice. Curr Mol Pharmacol 2023;16(7):725-50. https://doi.org/10.2174/1874467215666220928110557

29. Mahboob A, Farhat SM, Iqbal G, Babar MM, Zaidi NUSS, Nabavi SM, et al. Alpha-lipoic acid-mediated activation of muscarinic receptors improves hippocampus-and amygdala-dependent memory. Brain Res Bull 2016;122:19-28. https://doi.org/10.1016/j.brainresbull.2016.02.014

30. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001;25(4):402-8. https://doi.org/10.1006/meth.2001.1262

31. Zhao R, Liu P, Song A, Liu J, Chu Q, Liu Y, et al. Network pharmacology study on the mechanism of Qiangzhifang in the treatment of panic disorder. Ann Transl Med 2021;9(16):1350. https://doi.org/10.21037/atm-21-4090

32. Bastianetto S, Ménard C, Quirion R. Neuroprotective action of resveratrol. Biochim Biophys Acta Mol Basis Dis 2015;1852(6):1195-201. https://doi.org/10.1016/j.bbadis.2014.09.011

33. Walle T. Bioavailability of resveratrol. Ann N Y Acad Sci 2011;1215(1):9-15. https://doi.org/10.1111/j.1749-6632.2010.05842.x

34. Neves AR, Lucio M, Lima JLC, Reis S. Resveratrol in medicinal chemistry: a critical review of its pharmacokinetics, drug-delivery, and membrane interactions. Curr Med Chem 2012;19(11):1663-81. https://doi.org/10.2174/092986712799945085

35. Hu C, Chen C, Chen J, Xiao K, Wang J, Shi Q, et al. The low levels of nerve growth factor and its upstream regulatory kinases in prion infection is reversed by resveratrol. Neurosci Res 2021;162:52-62. https://doi.org/10.1016/j.neures.2019.12.019

36. Tan W, Qi L, Hu X, Tan Z. Research progress in traditional Chinese medicine in the treatment of Alzheimer’s disease and related dementias. Front Pharmacol 2022;13:921794. https://doi.org/10.3389/fphar.2022.921794

37. Gong W, Sun P, Li X, Wang X, Zhang X, Cui H, et al. Investigating the molecular mechanisms of resveratrol in treating cardiometabolic multimorbidity: a network pharmacology and bioinformatics approach with molecular docking validation. Nutrients 2024;16(15):2488. https://doi.org/10.3390/nu16152488

38. Ghafouri-Fard S, Bahroudi Z, Shoorei H, Hussen BM, Talebi SF, Baig SG, et al. Disease-associated regulation of gene expression by resveratrol: special focus on the PI3K/AKT signaling pathway. Cancer Cell Int 2022;22(1):298. https://doi.org/10.1186/s12935-022-02719-3

39. Zahoor M, Farhat SM, Khan S, Ahmed T. Daidzin improves neurobehavioral outcome in rat model of traumatic brain injury. Behav Brain Res 2024;472:115158. https://doi.org/10.1016/j.bbr.2024.115158

40. Lin Y, Chen F, Zhang J, Wang T, Wei X, Wu J, et al. Neuroprotective effect of resveratrol on ischemia/reperfusion injury in rats through TRPC6/CREB pathways. J Mol Neurosci 2013;50:504-13. https://doi.org/10.1007/s12031-013-9977-8

41. Toyoda H, Zhao MG, Mercaldo V, Chen T, Descalzi G, Kida S, et al. Calcium/calmodulin-dependent kinase IV contributes to translation-dependent early synaptic potentiation in the anterior cingulate cortex of adult mice. Mol Brain 2010;3:27. https://doi.org/10.1186/1756-6606-3-27

Similar Articles

<< < 3 > >> 

You may also start an advanced similarity search for this article.