Discovery of a novel CaMKⅡα inhibitor by machine learning, molecular docking and molecular dynamics simulation

CaMKIIα is a central regulator of synaptic plasticity and memory, and its pathological overactivation has been strongly linked to neurodegenerative and neuropsychiatric disorders. However, there remains a significant demand for discovery of potent and novel CaMKIIα inhibitors. This study constructed an integrated virtual screening workflow that combined machine learning, molecular docking, and drug-likeness evaluation. By screening 1.55 million compounds from the ChemDiv library, 10 candidates selected for subsequent experimental validation. Among these, an oxadiazole derivative, compound 2, was identified as a novel inhibitor with an IC₅₀ of 3.18 µM, introducing a novel scaffold for CaMKIIα inhibition. Molecular dynamics simulations was performed to demonstrated the stability of the CaMKIIα-compound 2 complex and the contribution of specific residues. This work provides a practical framework for the virtual screening of kinase inhibitors and presents a novel hit for CaMKIIα-targeted drug development.