A Drug Repositioning Approach: Antidiabetic Empagliflozin May Be a Potential Drug for the Treatment of ALS

Year 2025, Volume: 3 Issue: 3, 87 - 97, 15.01.2026

Selma Sezen , Feyza Burul

https://doi.org/10.62425/rtpharma.1828403

Abstract

Objective: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease in which multiple mechanisms play a role in its pathogenesis. However, no radical treatment is currently available for the disease. The potential for repositioning of the antidiabetic drug empagliflozin, which has been reported to have neuroprotective effects in recent studies, in ALS was investigated using computational models.
Methods: In this study, to identify ALS-related target proteins, protein–protein interaction networks and disease–gene enrichment analysis were constructed using the STRING database. For molecular docking analyses, the 3D structures of these ALS-associated receptors SOD1 (2C9V), hnRNP A1 (1HA1), TDP-43 (4BS2), SQSTM1/p62 (5YP7) were obtained from the RCSB Protein Data Bank. Empagliflozin and the receptors were prepared using UCSF Chimera v1.19 and AutoDockTools 1.5.7, and binding scores were recorded with AutoDock Vina. The ADMET properties of empagliflozin were determined using ADMETlab 2.0 and LogBB_Pred.
Results: In the protein networks generated by STRING, ALS-related proteins with high confidence scores and physical interactions were identified, and among them, four target proteins showing significant interactions and with available PDB codes were selected. Molecular docking analyses revealed that empagliflozin exhibited moderate-to-high binding interactions with SOD1 (-8.5 kcal/mol), TDP-43 (-7.7 kcal/mol), hnRNP A1 (-7.3 kcal/mol), and SQSTM1/p62 (-7.1 kcal/mol). According to ADMET analysis, empagliflozin can cross the blood–brain barrier, has a low risk of hepatotoxicity, and shows potential interactions with androgen receptor and aromatase.
Conclusion: In this study, conducted to repurpose empagliflozin via ALS-related mechanisms, which has been reported to have cardioprotective, hepatoprotective, and renoprotective effects in clinical studies, the findings obtained using computational models suggest that empagliflozin may have neuroprotective effects in ALS.

Keywords

ALS , empagliflozin , molecular docking , SOD1 , STRING , TDP-43

Ethical Statement

This study does not require ethics committee approval.

Supporting Institution

The authors declared that this study has received no financial support.

References

• Ahmed, S., El-Sayed, M. M., Kandeil, M. A., & Khalaf, M. M. (2022). Empagliflozin attenuates neurodegeneration through antioxidant, anti-inflammatory, and modulation of α-synuclein and Parkin levels in rotenone-induced Parkinson's disease in rats. Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society, 30(6), 863–873. https://doi.org/10.1016/j.jsps.2022.03.005
• Alami, M., Morvaridzadeh, M., El Khayari, A., Boumezough, K., El Fatimy, R., Khalil, A., Fulop, T., & Berrougui, H. (2025). Reducing Alzheimer's disease risk with SGLT2 inhibitors: From glycemic control to neuroprotection. Ageing research reviews, 108, 102751. https://doi.org/10.1016/j.arr.2025.102751
• Amin, E. F., Rifaai, R. A., & Abdel-Latif, R. G. (2020). Empagliflozin attenuates transient cerebral ischemia/reperfusion injury in hyperglycemic rats via repressing oxidative-inflammatory-apoptotic pathway. Fundamental & clinical pharmacology, 34(5), 548–558. https://doi.org/10.1111/fcp.12548
• Atiya, A., Muhsinah, A. B., Alrouji, M., Alhumaydhi, F. A., Al Abdulmonem, W., Aljasir, M. A., Sharaf, S. E., Furkan, M., Khan, R. H., Shahwan, M., & Shamsi, A. (2023). Unveiling promising inhibitors of superoxide dismutase 1 (SOD1) for therapeutic interventions. International journal of biological macromolecules, 253(Pt 2), 126684. https://doi.org/10.1016/j.ijbiomac.2023.126684
• Barbara, M., Reddy, A., Osuorji, C., & Gohel, T. (2021). Elevated liver enzymes caused by empagliflozin in a nonalcoholic fatty liver disease patient. The American Journal of Gastroenterology, 116(S1), S1119. https://doi.org/10.14309/01.ajg.0000784208.21511.00
• Benavides-Serrato, A., Saunders, J. T., Holmes, B., Nishimura, R. N., Lichtenstein, A., & Gera, J. (2020). Repurposing potential of riluzole as an ITAF inhibitör in mTOR therapy resistant glioblastoma. International journal of molecular sciences, 21(1), 344. https://doi.org/10.3390/ijms21010344
• Bergh, S., Casadei, N., Gabery, S., Simonsson, O., Duarte, J. M. N., Kirik, D., Nguyen, H. P., & Petersén, Å. (2025). TDP-43 overexpression in the hypothalamus drives neuropathology, dysregulates metabolism and impairs behavior in mice. Acta neuropathologica communications, 13(1), 119. https://doi.org/10.1186/s40478-025-02018-8
• Cohen, N. R., Zitzewitz, J. A., Bilsel, O., & Matthews, C. R. (2019). Nonnative structure in a peptide model of the unfolded state of superoxide dismutase 1 (SOD1): Implications for ALS-linked aggregation. The Journal of biological chemistry, 294(37), 13708–13717. https://doi.org/10.1074/jbc.RA119.008765
• Deng, Z., Lim, J., Wang, Q., Purtell, K., Wu, S., Palomo, G. M., Tan, H., Manfredi, G., Zhao, Y., Peng, J., Hu, B., Chen, S., & Yue, Z. (2020). ALS-FTLD-linked mutations of SQSTM1/p62 disrupt selective autophagy and NFE2L2/NRF2 anti-oxidative stress pathway. Autophagy, 16(5), 917–931. https://doi.org/10.1080/15548627.2019.1644076
• Erichsen, J. M., Register, T. C., Sutphen, C., Ma, D., Gaussoin, S. A., Rudolph, M., Rundle, M., Bateman, J. T., Lockhart, S. N., Sai, K. K. S., Whitlow, C., & Craft, S. (2025). A phase 2A/B randomized trial of metabolic modulators intranasal insulin and empagliflozin for MCI and early AD. Alzheimer's & Dementia, 21(10), e70704. https://doi.org/10.1002/alz.70704
• Famularo, G., Sajeva, M. R., Marino, G., & Granato, C. (2017). Acute hepatitis caused by empagliflozin in a nonalcoholic fatty liver disease patient. The Annals of Pharmacotherapy, 51(12), 1142–1143. https://doi.org/10.1177/1060028017728522
• Floare, M. L., & Allen, S. P. (2020). Why TDP-43? Why not? Mechanisms of metabolic dysfunction in amyotrophic lateral sclerosis. Neuroscience insights, 15, 2633105520957302. https://doi.org/10.1177/2633105520957302
• Foster, A. D., Flynn, L. L., Cluning, C., Cheng, F., Davidson, J. M., Lee, A., Polain, N., Mejzini, R., Farrawell, N., Yerbury, J. J., Layfield, R., Akkari, P. A., & Rea, S. L. (2021). p62 overexpression induces TDP-43 cytoplasmic mislocalisation, aggregation and cleavage and neuronal death. Scientific reports, 11(1), 11474. https://doi.org/10.1038/s41598-021-90822-2
• Gheidari, D., Mehrdad, M., & Karimelahi, Z. (2024). Virtual screening, ADMET prediction, molecular docking, and dynamic simulation studies of natural products as BACE1 inhibitors for the management of Alzheimer's disease. Scientific Reports, 14(1), 26431. https://doi.org/10.1038/s41598-024-75292-6
• Hardiman, O., Al-Chalabi, A., Chio, A., Corr, E. M., Logroscino, G., Robberecht, W., Shaw, P. J., Simmons, Z., & van den Berg, L. H. (2017). Amyotrophic lateral sclerosis. Nature reviews. Disease primers, 3, 17071. https://doi.org/10.1038/nrdp.2017.71
• Huang, B., Liu, X., Zhang, T., Wu, Q., Huang, C., Xia, X. G., & Zhou, H. (2023). Increase in hnRNPA1 Expression Suffices to Kill Motor Neurons in Transgenic Rats. International journal of molecular sciences, 24(22), 16214. https://doi.org/10.3390/ijms242216214
• Inoue-Shibui, A., Kato, M., Suzuki, N., Kobayashi, J., Takai, Y., Izumi, R., Kawauchi, Y., Kuroda, H., Warita, H., & Aoki, M. (2019). Interstitial pneumonia and other adverse events in riluzole-administered amyotrophic lateral sclerosis patients: a retrospective observational study. BMC Neurology, 19(1), 72. https://doi.org/10.1186/s12883-019-1299-1
• Jeon, G. S., Shim, Y. M., Lee, D. Y., Kim, J. S., Kang, M., Ahn, S. H., Shin, J. Y., Geum, D., Hong, Y. H., & Sung, J. J. (2019). Pathological modification of TDP-43 in Amyotrophic Lateral Sclerosis with SOD1 mutations. Molecular neurobiology, 56(3), 2007–2021. https://doi.org/10.1007/s12035-018-1218-2
• Jiao, Y., Yang, L., Wang, R., Song, G., Fu, J., Wang, J., Gao, N., & Wang, H. (2024). Drug delivery across the blood-brain barrier: a new strategy for the treatment of neurological diseases. Pharmaceutics, 16(12), 1611. https://doi.org/10.3390/pharmaceutics16121611
• Kapeli, K., Martinez, F. J., & Yeo, G. W. (2017). Genetic mutations in RNA-binding proteins and their roles in ALS. Human genetics, 136(9), 1193–1214. https://doi.org/10.1007/s00439-017-1830-7
• Kawano, C., Isozaki, Y., Nakagawa, A., Hirayama, T., Nishiyama, K., & Kuroyama, M. (2020). Liver injury risk factors in amyotrophic lateral sclerosis patients treated with riluzole. Yakugaku Zasshı, 140, 923-928. https://doi.org/10.1248/yakushi.20-00015
• Kosinski, C., Papadakis, G. E., Salamin, O., Kuuranne, T., Nicoli, R., Pitteloud, N., & Zanchi, A. (2024). Effects of empagliflozin on reproductive system in men without diabetes. Scientific Reports, 14(1), 13802. https://doi.org/10.1038/s41598-024-64684-3
• Kuchay, M. S., Krishan, S., Mishra, S. K., Farooqui, K. J., Singh, M. K., Wasir, J. S., Bansal, B., Kaur, P., Jevalikar, G., Gill, H. K., Choudhary, N. S., & Mithal, A. (2018). Effect of empagliflozin on liver fat in patients with type 2 diabetes and nonalcoholic fatty liver disease: A randomized controlled trial (E-LIFT Trial). Diabetes care, 41(8), 1801–1808. https://doi.org/10.2337/dc18-0165
• Kunwittaya, S., Nantasenamat, C., Treeratanapiboon, L., Srisarin, A., Isarankura-Na-Ayudhya, C., & Prachayasittikul, V. (2013). Influence of logBB cut-off on the prediction of blood-brain barrier permeability. Biomedical and Applied Technology Journal, 1, 16-34.
• Kwon, D. H., Park, O. H., Kim, L., Jung, Y. O., Park, Y., Jeong, H., Hyun, J., Kim, Y. K., & Song, H. K. (2018). Insights into degradation mechanism of N-end rule substrates by p62/SQSTM1 autophagy adapter. Nature communications, 9(1), 3291. https://doi.org/10.1038/s41467-018-05825-x
• Levison, L. S., Blicher, J. U., & Andersen, H. (2024). Incidence and mortality of ALS: a 42-year population-based nationwide study. Journal of neurology, 272(1), 44. https://doi.org/10.1007/s00415-024-12743-0
• Macha, S., Brand, T., Meinicke, T., Link, J., & Broedl, U. C. (2015). Pharmacokinetics and Pharmacodynamics of Twice Daily and Once Daily Regimens of Empagliflozin in Healthy Subjects. Clinical therapeutics, 37(8), 1789–1796. https://doi.org/10.1016/j.clinthera.2015.06.003
• Marangoz A.D., & Erdoğan, Ç. (2020) Pathogenesis of amyotrophic lateral sclerosis (ALS). Pamukkale medical journal, 13(2), 477-484. https://dx.doi.org/10.31362/patd.643460
• Masrori, P., & Van Damme, P. (2020). Amyotrophic lateral sclerosis: a clinical review. European Journal of Neurology, 27, 1918 - 1929. https://doi.org/10.1111/ene.14393.
• Mohammed, N. N., Tadros, M. G., & George, M. Y. (2024). Empagliflozin repurposing in Parkinson's disease; Modulation of oxidative stress, neuroinflammation, AMPK/SIRT-1/PGC-1α, and wnt/β-catenin pathways. Inflammopharmacology, 32(1), 777–794. https://doi.org/10.1007/s10787-023-01384-w
• Monteiro Neto, J. R., de Souza, G. F., Dos Santos, V. M., de Holanda Paranhos, L., Ribeiro, G. D., Magalhães, R. S. S., Queiroz, D. D., & Eleutherio, E. C. A. (2025). SOD1, a crucial protein for neural biochemistry: dysfunction and risk of Amyotrophic Lateral Sclerosis. Molecular neurobiology, 62(11), 14966–14986. https://doi.org/10.1007/s12035-025-05067-1
• Monteiro Neto, J. R., de Souza, G. F., Dos Santos, V. M., de Holanda Paranhos, L., Ribeiro, G. D., Magalhães, R. S. S., Queiroz, D. D., & Eleutherio, E. C. A. (2025). SOD1, A crucial protein for neural biochemistry: Dysfunction and risk of amyotrophic lateral sclerosis. Molecular neurobiology, 62(11), 14966–14986. https://doi.org/10.1007/s12035-025-05067-1
• Mugundan, U. M., Sekar, P., & Ganesan, R. M. (2025). Repurposing antiviral drugs targeting the PARP-1 and HER2 pathways with multifaceted impacts through integrated network analysis and molecular mechanics. Chemical Physics Impact, 10, 100812. https://doi.org/10.1016/j.chphi.2024.100812
• Murugan, N. A., Muvva, C., Jeyarajpandian, C., Jeyakanthan, J., & Subramanian, V. (2020). Performance of force-field- and machine learning-based scoring functions in ranking MAO-B protein-ınhibitor complexes in relevance to developing parkinson's therapeutics. International Journal of Molecular Sciences, 21(20), 7648. https://doi.org/10.3390/ijms21207648
• Prasad, A., Bharathi, V., Sivalingam, V., Girdhar, A., & Patel, B. K. (2019). Molecular mechanisms of TDP-43 misfolding and pathology in Amyotrophic Lateral Sclerosis. Frontiers in molecular neuroscience, 12, 25. https://doi.org/10.3389/fnmol.2019.00025
• Rizea, R. E., Corlatescu, A. D., Costin, H. P., Dumitru, A., & Ciurea, A. V. (2024). Understanding amyotrophic lateral sclerosis: Pathophysiology, diagnosis, and therapeutic advances. International journal of molecular sciences, 25(18), 9966. https://doi.org/10.3390/ijms25189966
• Saini, A., & Chawla, P. A. (2024). Breaking barriers with tofersen: Enhancing therapeutic opportunities in amyotrophic lateral sclerosis. European journal of neurology, 31(2), e16140. https://doi.org/10.1111/ene.16140 Scheen A. J. (2014). Pharmacokinetic and pharmacodynamic profile of empagliflozin, a sodium glucose co-transporter 2 inhibitor. Clinical pharmacokinetics, 53(3), 213–225. https://doi.org/10.1007/s40262-013-0126-x
• Sezen S. (2025). Beyond glycemic control: The pleiotropic potential of SGLT-2 inhibitors. Ağrı Medical Journal, 3(3), 99-101. https://doi.org/10.61845/agrimedical.1811202
• Sezen, S., Karadayi, M., Yesilyurt, F., Burul, F., Gulsahin, Y., Ozkaraca, M., Okkay, U., & Gulluce, M. (2025). Acyclovir provides protection against 6-OHDA-induced neurotoxicity in SH-SY5Y cells through the kynurenine pathway. Neurotoxicology, 106, 1–9. https://doi.org/10.1016/j.neuro.2024.11.005
• Sezen, S., Ozakar, R. S., Bayram, C., Burul, F., Ozkaraca, M., Karadayi, M., Ekimci Deniz, F., Hacımuftuoglu, M., & Gulluce, M. (2026). A Plantago lanceolata L. extract-based cream enhances wound healing by modulating inflammatory mediators and growth factors in a full-thickness wound model: In vivo and İn-silico evidence. Journal of Drug Delivery Science and Technology, 107635. https://doi.org/10.1016/j.jddst.2025.107635
• Shaker, B., Lee, J., Lee, Y., Yu, M. S., Lee, H. M., Lee, E., Kang, H. C., Oh, K. S., Kim, H. W., & Na, D. (2023). A machine learning-based quantitative model (LogBB_Pred) to predict the blood-brain barrier permeability (logBB value) of drug compounds. Bioinformatics (Oxford, England), 39(10), btad577. https://doi.org/10.1093/bioinformatics/btad577
• Strange, R. W., Antonyuk, S. V., Hough, M. A., Doucette, P. A., Valentine, J. S., & Hasnain, S. S. (2006). Variable metallation of human superoxide dismutase: atomic resolution crystal structures of Cu-Zn, Zn-Zn and as-isolated wild-type enzymes. Journal of molecular biology, 356(5), 1152–1162. https://doi.org/10.1016/j.jmb.2005.11.081
• Sun, H., Chen, W., Chen, L., & Zheng, W. (2021). Exploring the molecular basis of UG-rich RNA recognition by the human splicing factor TDP-43 using molecular dynamics simulation and free energy calculation. Journal of computational chemistry, 42(23), 1670–1680. https://doi.org/10.1002/jcc.26704
• Szklarczyk, D., Nastou, K., Koutrouli, M., Kirsch, R., Mehryary, F., Hachilif, R., Hu, D., Peluso, M. E., Huang, Q., Fang, T., Doncheva, N. T., Pyysalo, S., Bork, P., Jensen, L. J., & von Mering, C. (2025). The STRING database in 2025: protein networks with directionality of regulation. Nucleic acids research, 53(D1), D730–D737. https://doi.org/10.1093/nar/gkae1113
• Taha, B. O., Kobeisy, M. A., Abdelmohsen, E., Abdelrhman, T., Abokresha, M. M., Hassanein, Z. M., & AbdEllah-Alawi, M. H. M. (2025). Outcomes of empagliflozin in nondiabetic fatty liver patients: A randomized controlled trial. Journal of Taibah University Medical Sciences, 20(4), 525–532. https://doi.org/10.1016/j.jtumed.2025.07.008
• Tahara, A., Takasu, T., Yokono, M., Imamura, M., & Kurosaki, E. (2016). Characterization and comparison of sodium-glucose cotransporter 2 inhibitors in pharmacokinetics, pharmacodynamics, and pharmacologic effects. Journal of Pharmacological Sciences, 130(3), 159–169. https://doi.org/10.1016/j.jphs.2016.02.003
• Tan, R. H., Ke, Y. D., Ittner, L. M., & Halliday, G. M. (2017). ALS/FTLD: experimental models and reality. Acta neuropathologica, 133(2), 177–196. https://doi.org/10.1007/s00401-016-1666-6
• Tanji, K., Zhang, H. X., Mori, F., Kakita, A., Takahashi, H., & Wakabayashi, K. (2012). p62/sequestosome 1 binds to TDP-43 in brains with frontotemporal lobar degeneration with TDP-43 inclusions. Journal of neuroscience research, 90(10), 2034–2042. https://doi.org/10.1002/jnr.23081
• Tsekrekou, M., Giannakou, M., Papanikolopoulou, K., & Skretas, G. (2024). Protein aggregation and therapeutic strategies in SOD1- and TDP-43- linked ALS. Frontiers in molecular biosciences, 11, 1383453. https://doi.org/10.3389/fmolb.2024.1383453
• U.S. Food and Drug Administration. (2022). Full Prescribing Information: JARDIANCE® (empagliflozin) tablets. https://www.accessdata.fda.gov/drugsatfda_docs/label/2022/204629s033lbl.pdf
• Visibelli, A., Roncaglia, B., Spiga, O., & Santucci, A. (2023). The impact of artificial intelligence in the odyssey of rare diseases. Biomedicines, 11(3), 887. https://doi.org/10.3390/biomedicines11030887
• Wang, H., Guan, L., & Deng, M. (2023). Recent progress of the genetics of amyotrophic lateral sclerosis and challenges of gene therapy. Frontiers in neuroscience, 17, 1170996. https://doi.org/10.3389/fnins.2023.1170996
• Wijesekera, L. C., & Leigh, P. N. (2009). Amyotrophic lateral sclerosis. Orphanet journal of rare diseases, 4, 3. https://doi.org/10.1186/1750-1172-4-3
• Wu, Y., Lou, L., & Xie, Z. R. (2020). A pilot study of all-computational drug design protocol-from structure prediction to ınteraction analysis. Frontiers in chemistry, 8, 81. https://doi.org/10.3389/fchem.2020.00081