Abstract

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by tau hyperphosphorylation, which contributes to neurofibrillary tangle formation and neuronal loss. Multiple kinases are involved in this process making them potential therapeutic targets. However, the identification of selective inhibitors with favourable pharmacokinetic properties and adequate brain penetration remains a challenge. In this study, thirteen tau-related kinases were prioritized according to the number of predicted tau serine phosphorylation sites identified using a percentile-based filtering approach. Known inhibitors for each kinase were evaluated using Boltz-2 AI-based docking software and predicted binding affinity likelihood (BAL) scores and IC₅₀-like values were combined to rank inhibitors within each kinase-specific set. The selected compounds were subsequently evaluated using SwissADME pharmacokinetic software, focusing on blood-brain barrier permeability, gastrointestinal absorption, P-glycoprotein interaction, and compliance with Lipinski’s rule of five. Molecular selectivity was estimated using experimentally determined IC₅₀ data retrieved from ChEMBL, while protein brain expression and protein–protein interaction data were obtained from the Human Protein Atlas and STRING databases. The results identified kinase inhibitors with favourable predicted pharmacokinetic properties and varying degrees of target selectivity. Together, these analyses provide a framework for prioritizing kinase inhibitors for further investigation and experimental validation in the context of future AD therapy development.