The Determination of Druglikeness, Pharmacokinetic Profile, Toxicity Parameters, and Anti-Alzheimer Activity of Amiloride: A Detailed in silico Investigation
Abstract
Objective: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by complex molecular mechanisms, including amyloid-β accumulation and synaptic dysfunction. In this context, the present study aimed to perform a comparative in silico evaluation of amiloride and memantine in terms of their interactions with ASIC, along with their pharmacokinetic and toxicity-related properties. Materials and Methods: The structural and pharmacokinetic properties of amiloride and memantine were assessed using in silico approaches, including molecular docking, ADME prediction, and toxicity profiling. Molecular docking analyses were performed against the ASIC receptor (PDB ID: 2QTS) using Molegro Virtual Docker. Drug-likeness and pharmacokinetic parameters were evaluated based on established computational platforms, and toxicity endpoints were predicted using in silico toxicity models. Results: Docking analysis indicated that amiloride exhibited a higher predicted binding affinity for the ASIC receptor than memantine. Both compounds complied with Lipinski’s rule of five, suggesting acceptable drug-likeness. In silico ADME predictions revealed differences in pharmacokinetic behavior, particularly in blood–brain barrier permeability, with amiloride showing limited central nervous system penetration compared to memantine. Toxicity predictions suggested that both compounds possess mixed safety profiles, with varying probabilities across different toxicity endpoints. Conclusion: The present in silico findings suggest that amiloride may interact more favorably with the ASIC receptor compared to memantine under computational conditions. However, given the predictive nature of the employed methods, these results should be interpreted cautiously. Overall, amiloride may represent a potential lead compound for further experimental investigation in ASIC-related mechanisms of Alzheimer’s disease.
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References
- 1. Forlenza OV, Diniz BS, Gattaz WF. Diagnosis and biomarkers of predementia in Alzheimer's disease. BMC Med. 2010;8:89. doi.org/10.1186/1741-7015-8-89
- 2. Long JM, Holtzman DM. Alzheimer's Disease: An update on pathobiology and treatment strategies. Cell. 2019;179(2):312-339.
- 3. Siddappaji KK, Gopal S. Molecular mechanisms in Alzheimer's disease and the impact of physical exercise with advancements in therapeutic approaches. AIMS Neurosci. 2021;8(3):357-389.
- 4. Mount C, Downton C. Alzheimer's disease: progress or profit? Nat Med. 2006;12(7):780-784. 5. Ke PC, Sani MA, Ding F, et al. Implications of peptide assemblies in amyloid diseases. Chemical Society Reviews. 2017;46(21):6492-6531.
- 6. Bisaglia M, Venezia V, Piccioli P, et al. Acetaminophen protects hippocampal neurons and PC12 cultures from amyloid β-peptides induced oxidative stress and reduces NF-κB activation. Neurochemistry international. 2002;41(1):43-54.
- 7. Takeda K, Uda A, Mitsubori M, et al. Mitochondrial ubiquitin ligase alleviates Alzheimer’s disease pathology via blocking the toxic amyloid-β oligomer generation. Communications Biology. 2021;4(1): 192-199.
- 8. Murakawa-Hirachi T, Mizoguchi Y, Ohgidani M, Haraguchi Y, Monji A. Effect of memantine, an anti-Alzheimer’s drug, on rodent microglial cells in vitro. Scientific Reports. 2021;11(1):6151-6160.
- 9. Cummings J, Lee G, Nahed P, et al. Alzheimer's disease drug development pipeline. Alzheimer's & Dementia: Translational Research & Clinical Interventions. 2022;8(1):12295. doi.org/10.1002/trc2.12295
Details
Primary Language
English
Subjects
Physiopathology, Systems Physiology
Journal Section
Research Article
Authors
Ziya Çakır
*
0009-0003-0329-1974
Türkiye
Çiğdem Bilkan
0000-0002-3347-673X
Türkiye
Burhan Ertekin
0000-0003-2804-047X
Türkiye
Publication Date
June 21, 2026
Submission Date
August 3, 2025
Acceptance Date
May 7, 2026
Published in Issue
Year 2026 Volume: 11 Number: 2