Background: Alzheimer's disease (AD) is characterized by neurodegeneration linked to amyloid-β (Aβ) plaques and tau protein tangles. Protein kinase C alpha (PKCα) plays a crucial role in modulating amyloid-β protein precursor (AβPP) processing, potentially mitigating AD progression. Consequently, PKCα stands out as a promising target for AD therapy.
Objective: Despite the identification of numerous inhibitors, the pursuit of more effective and precisely targeted PKCα inhibitors remains crucial.
Methods: In this study, we employed an integrated virtual screening approach of molecular docking and molecular dynamics (MD) simulations to identify phytochemical inhibitors of PKCα from the IMPPAT database.
Results: Molecular docking screening via InstaDock identified compounds with strong binding affinities to PKCα. Subsequent ADMET and PASS analyses filtered out compounds with favorable pharmacokinetic profiles. Interaction analysis using Discovery Studio Visualizer and PyMOL further elucidated binding conformations of selected compounds with PKCα. Top hits underwent 200 ns MD simulations using GROMACS to validate stability of the interactions. Finally, we propose two phytochemicals, Kammogenin and Imperialine, with appreciable drug-likeliness and binding potential with PKCα.
Conclusions: Taken together, the findings suggest Kammogenin and Imperialine as potential PKCα inhibitors, highlighting their therapeutic promise for AD after further validation.
Keywords: ADMET analysis; Alzheimer's disease; PASS analysis; amyloid-β; phytochemicals; protein kinase C alpha; virtual screening.