Machine learning-guided repurposing of FDA-approved quinolones as dual cholinesterase inhibitors: A multi-level...

Alzheimer's disease (AD) involves progressive cholinergic degeneration, with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) playing key enzymatic roles in its pathology. In this study, we computationally repurposed four FDA-approved quinolone antibiotics, Norfloxacin, Sparfloxacin, Gatifloxacin, and Nalidixic acid, as potential dual-site cholinesterase (ChE) inhibitors using a hybrid in vitro/in silico workflow. Enzyme inhibition assays identified Norfloxacin as the most potent AChE inhibitor (K_I = 1.08 μM), while all compounds displayed non-competitive inhibition toward BChE. Molecular docking and MM-GBSA binding free energy analyses revealed key interactions within the catalytic gorge of AChE, supported by hydrogen bonding with Phe295 and Arg296, as well as π-π contacts with Tyr124. Density functional theory computations highlighted the influence of frontier orbital distribution on binding affinity, particularly for Norfloxacin and Sparfloxacin. An explicit-solvent molecular dynamics simulation of the AChE-Norfloxacin complex further confirmed the stability of the docking-derived binding mode over 100 ns. In an exploratory fashion, SHAP-based machine learning models were applied to a descriptor set derived from QikProp, SwissADME, and Jaguar outputs, suggesting that BBB-related indices and HOMO energy contribute to AChE inhibition, whereas the energy gap is more relevant for BChE; these trends, however, are constrained by the small four-compound dataset and should be regarded as hypothesis-generating. In silico ADME/Tox profiling indicated favorable oral drug-like properties, low predicted CYP450 inhibition liabilities, and physicochemical profiles compatible with CNS-oriented optimization, although passive BBB permeability was not predicted to be high. Finally, systems-level enrichment (STRING, GeneCards) provided a qualitative network context linking ACHE and BCHE to neurodegeneration. Together, these data position Norfloxacin and Sparfloxacin as computationally prioritised candidates whose ChE-related repurposing potential warrants further validation in dedicated cellular and in vivo models.