Computational prioritization of multi-target inhibitors: explainable QSAR and docking-based discovery of dual AChE/BACE1 chemotypes.

ABSTRACT: The discovery of dual acetylcholinesterase (AChE) and β-secretase (BACE1) inhibitors remains a promising strategy against multifactorial Alzheimer's disease. Here, rigorously curated ChEMBL-derived data were used to develop explainable QSAR (Quantitative structure-activity relationship) models for dual-inhibition prioritization. Molecules were standardized, near-duplicates were removed using a Tanimoto similarity threshold (≥ 0.80), and physicochemical outliers were filtered prior to modeling. Multiple classifiers (including Light Gradient-Boosting Machine, eXtreme Gradient Boosting, Random Forest, Support Vector Machine, k-Nearest Neighbors and Gradient Boosting Decision Trees) and fingerprints (e.g., RDKit fingerprints, Extended Connectivity Fingerprint) were benchmarked under scaffold-b

SUBMITTER: Bozkır I 

PROVIDER: S-EPMC12852253 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature