Computational insights and experimental breakthroughs in identifying next-generation acetylcholinesterase inhibitors
The study aimed to identify the potential acetylcholinesterase (AChE) inhibitors for effective Alzheimer's treatment from existing FDA-approved drugs through a drug repurposing technique via computational tools. Further, to evaluate the anti-Alzheimer's potency of the identified drug with the help of a suitable drug delivery system through in vivo pharmacological studies. The molecular docking and dynamics simulation studies indicated that letrozole has a significant binding affinity of -9.6 kcal/mol and a better interaction with AChE. The physicochemical properties of letrozole-encapsulated solid lipid nanoparticles (L-SLNs) were characterized and confirmed. Initially, acute toxicity tests of L-SLNs were performed according to OECD 423 guidelines. Biochemical studies revealed that L-SLNs significantly decreased brain Acetylcholine esterase activity induced by scopolamine, but L-SLNs significantly increased AChE activity compared to the Shaam control group. Histopathological evaluation of brain regions revealed significant insights into the neuroprotective potential of L-SLNs in an Alzheimer's disease (AD) rat model. Treatment with L-SLNs demonstrated dose-dependent neuroprotection across all studied brain regions. At a low dose of L-SLNs (2.5 mg/kg), neuronal and glial cells in the cortical and hippocampal regions showed improved regularity, although some disorganization persisted. At a mid-dose of L-SLNs (5 mg/kg), the histopathological architecture further normalized, with neurons and glial cells exhibiting regular arrangement and morphology akin to normal cells. The high dose of L-SLNs (10 mg/kg) provided the most significant protection, with neuronal and glial cells displaying near-normal arrangement and morphology in the cortical, hippocampal, and Substantia Nigra regions. This study highlights the importance of SLNs-based drug delivery systems in improving the efficacy of existing therapeutic agents in neurodegenerative conditions.
Authors
- Selvaraj Kunjiappan (ORCID: https://orcid.org/0000-0002-6741-5118)
- Damodar Nayak Ammunje (ORCID: https://orcid.org/0000-0002-3904-4700)
- Panneerselvam Theivendren (ORCID: https://orcid.org/0000-0002-8197-4688)
- Parasuraman Pavadai (ORCID: https://orcid.org/0000-0002-0779-4750)
- Kumarappan Chidamabaram
- Nandini Markuli Sadashivappa
- Basavana Gowda Hosur Dinesh (ORCID: https://orcid.org/0000-0002-2306-4969)
- B.S. Hemanth Kumar (ORCID: https://orcid.org/0009-0006-3115-8849)
- Sandra Ross Olakkengil Shajan (ORCID: https://orcid.org/0009-0008-1467-2701)
- Devaraj Hanumanthappa
- Shivaraj Kumar Walikar
- Srinivas Ganjipete (ORCID: https://orcid.org/0009-0005-6692-1843)
Institutions
- Vels University (IN)
- M S Ramaiah University of Applied Sciences (IN)
- Department of Biotechnology (IN)
- King Khalid University (SA)
Publication Details
- Journal
- Scientific Reports
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1038/s41598-025-17733-4
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50