Identification of acetylcholinesterase inhibitors from traditional medicinal plants for Alzheimer's disease using in silico and machine learning approaches.

ABSTRACT: Acetylcholinesterase (AChE) holds significance in Alzheimer's disease (AD), where cognitive impairment correlates with insufficient acetylcholine levels. AChE's role involves the breakdown of acetylcholine, moderating cholinergic neuron activity to prevent overstimulation and signal termination. Hence, inhibiting AChE emerges as a potential treatment avenue for AD. A library of 2500 compounds, derived from 25 traditionally used medicinal plants, was constructed using the IMPAAT database of traditional medicinal plants. The canonical SMILES of these compounds were collected and underwent virtual screening based on physicochemical properties, with subsequent determination of IC₅₀ values for the screened compounds followed by analysis using machine learning (ML). Subsequently, a mo

SUBMITTER: Islam MT 

PROVIDER: S-EPMC11526779 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature