Computational drug repurposing in Parkinson’s disease: Omaveloxolone and cyproheptadine as promising therapeutic candidates DOI Creative Commons
Xin Guo, Jie Wang, Hongyang Fan

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 8, 2025

Background: Parkinson's disease (PD), a prevalent and progressive neurodegenerative disorder, currently lacks effective satisfactory pharmacological treatments. Computational drug repurposing represents promising efficient strategy for discovery, aiming to identify new therapeutic indications existing pharmaceuticals. Methods: We employed drug-target network approach computationally repurpose FDA-approved drugs from databases such as DrugBank. A literature review was conducted select candidates not previously reported pharmacoprotective against PD. Subsequent in vitro evaluation utilized Cell Counting Kit-8 (CCK8) assays assess the neuroprotective effects of selected compounds SH-SY5Y cell model induced by 1-methyl-4-phenylpyridinium (MPP+). Furthermore, an vivo mouse 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) developed investigate mechanisms action potential identified candidates. Results: Our 176 candidates, with 28 their anti-Parkinsonian lack prior PD-related reporting. CCK8 showed significant neuroprotection cells Omaveloxolone Cyproheptadine. In MPTP-induced model, Cyproheptadine inhibited interleukin-6 (IL-6) expression prevented Tyrosine Hydroxylase (TH) downregulation via MAPK/NFκB pathway, while alleviated TH downregulation, potentially through Kelch-like ECH-associated protein 1 (KEAP1)-NF-E2-related factor 2 (Nrf2)/antioxidant response element (ARE) pathway. Both preserved dopaminergic neurons improved neurological deficits PD model. Conclusion: This study elucidates treatment application computational repurposing, thereby underscoring its efficacy discovery strategy.

Language: Английский

hESC-derived extracellular vesicles enriched with MFGE-8 and the GSH redox system act as senotherapeutics for neural stem cells in ischemic stroke DOI
Youngseok Lee, Jihun Lee,

Jeongjun Kim

et al.

Free Radical Biology and Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Computational drug repurposing in Parkinson’s disease: Omaveloxolone and cyproheptadine as promising therapeutic candidates DOI Creative Commons
Xin Guo, Jie Wang, Hongyang Fan

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 8, 2025

Background: Parkinson's disease (PD), a prevalent and progressive neurodegenerative disorder, currently lacks effective satisfactory pharmacological treatments. Computational drug repurposing represents promising efficient strategy for discovery, aiming to identify new therapeutic indications existing pharmaceuticals. Methods: We employed drug-target network approach computationally repurpose FDA-approved drugs from databases such as DrugBank. A literature review was conducted select candidates not previously reported pharmacoprotective against PD. Subsequent in vitro evaluation utilized Cell Counting Kit-8 (CCK8) assays assess the neuroprotective effects of selected compounds SH-SY5Y cell model induced by 1-methyl-4-phenylpyridinium (MPP+). Furthermore, an vivo mouse 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) developed investigate mechanisms action potential identified candidates. Results: Our 176 candidates, with 28 their anti-Parkinsonian lack prior PD-related reporting. CCK8 showed significant neuroprotection cells Omaveloxolone Cyproheptadine. In MPTP-induced model, Cyproheptadine inhibited interleukin-6 (IL-6) expression prevented Tyrosine Hydroxylase (TH) downregulation via MAPK/NFκB pathway, while alleviated TH downregulation, potentially through Kelch-like ECH-associated protein 1 (KEAP1)-NF-E2-related factor 2 (Nrf2)/antioxidant response element (ARE) pathway. Both preserved dopaminergic neurons improved neurological deficits PD model. Conclusion: This study elucidates treatment application computational repurposing, thereby underscoring its efficacy discovery strategy.

Language: Английский

Citations

0