In silico Design of Sulfenylated 5-Aminopyrazole Derivatives, Novel Butyrylcholinesterase Inhibitors for the Treatment of Alzheimer's Disease
TL;DR
Overall, the integrated modelling strategy identified structurally plausible BuChE-binding candidates and provides a computational basis for selecting APS analogues for subsequent synthesis, biochemical testing, and experimental evaluation.
Abstract
Alzheimer’s disease (AD) is a neurodegenerative disorder associated with cholinergic dysfunction, and butyrylcholinesterase (BuChE) becomes increasingly relevant as disease pathology progresses. This study aimed to design sulfenylated 5-aminopyrazole (APS) analogues as potential human BuChE inhibitors using an integrated computer-aided workflow. A structure-based quantitative structure–activity relationship (QSAR) model was developed using the human BuChE–tacrine crystal structure (PDB 4BDS) and 15 APS derivatives, comprising 12 compounds in the training set and three in the external validation set. Molecular docking, binding-energy and residue-level interaction analyses were combined with a 3D-QSAR pharmacophore model, virtual screening, and in silico ADME prediction. The selected QSAR model explained 98% of the variation in experimental inhibitory activity and showed strong validation performance. The pharmacophore model also demonstrated a close relationship between experimental and predicted activity, with R² = 0.93 and cross-validated R² = 0.92. Virtual screening of 49 newly designed APS analogues identified APSA22, APSA28, APSA35, and APSA39 among the most promising candidates on the basis of predicted inhibitory activity. QikProp analysis indicated favourable theoretical pharmacokinetic characteristics for these prioritised analogues. Overall, the integrated modelling strategy identified structurally plausible BuChE-binding candidates and provides a computational basis for selecting APS analogues for subsequent synthesis, biochemical testing, and experimental evaluation.