In Silico Design, ADMET Prediction and Molecular Docking Studies of Novel Cyanopyridine-Substituted 1,3,5-Triazine Derivatives as Potential Anti-Alzheimer Agents

Abstract

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide and is characterized by progressive cognitive impairment, memory loss, and behavioral dysfunction resulting from the degeneration of cholinergic neurons and the accumulation of amyloid-β plaques and neurofibrillary tangles. Despite the availability of several acetylcholinesterase (AChE) inhibitors, including donepezil, rivastigmine, and galantamine, their therapeutic benefits remain limited due to adverse effects, poor selectivity, and inability to halt disease progression. Consequently, the development of novel molecules possessing improved pharmacological efficacy and favorable pharmacokinetic properties remains an important objective in anti-Alzheimer drug discovery.The present study employed an integrated computer-aided drug design (CADD) strategy to design and evaluate fifty novel cyanopyridine-substituted 1,3,5-triazine derivatives as potential anti-Alzheimer agents. The designed molecules were generated by introducing structurally diverse aromatic, heterocyclic, and aliphatic amines onto the cyanopyridine–1,3,5-triazine scaffold in order to optimize receptor binding affinity and drug-like characteristics. Molecular structures were constructed using ChemDraw Ultra 8.0, followed by prediction of physicochemical properties, Lipinski's Rule of Five compliance, gastrointestinal absorption, aqueous solubility, synthetic accessibility, and overall pharmacokinetic behavior using SwissADME. Molecular docking studies were subsequently performed using the CDOCKER module of Discovery Studio 3.0 against acetylcholinesterase (PDB ID: 1EVE) to investigate ligand–protein interactions and estimate binding affinities. The computational screening demonstrated that the majority of designed compounds satisfied accepted drug-likeness criteria and exhibited favorable ADMET profiles. Molecular docking identified several derivatives possessing significantly stronger binding affinities than other library members. Among the evaluated molecules, CPT-19, CPT-14, CPT-15, CPT-13, and CPT-12 exhibited the most favorable docking scores, suggesting stable interactions within the catalytic gorge of acetylcholinesterase through hydrogen bonding, hydrophobic interactions, π–π stacking, and van der Waals contacts. These findings indicate that structural modification of the cyanopyridine–1,3,5-triazine scaffold can substantially improve molecular recognition toward the target enzyme. Overall, the present investigation demonstrates the usefulness of integrated in silico methodologies for rapid identification of promising anti-Alzheimer lead compounds. The identified derivatives warrant further chemical synthesis followed by in vitro enzymatic evaluation, cellular assays, pharmacokinetic studies, and in vivo validation to establish their therapeutic potential.