Structure‐Guided In Silico Design of CK1α Inhibitors Using Pharmacophore Modeling, De Novo Design, Molecular Dynamics Simulations, and DFT Calculations

ABSTRACT This study investigates casein kinase‐1 alpha (CK1 α ) as a promising target for anticancer drug development, owing to its involvement in critical signaling pathways and its differential expression across various cancer types. We utilized e‐pharmacophore modeling, virtual screening, and breed‐based de novo hybridization to identify novel CK1 α inhibitors from the PubChem database, resulting in the synthesis of two breed compounds (Breed 1 and Breed 2). Molecular dynamics simulations conducted over 300 ns, along with MM‐PBSA calculations, demonstrated that these two breed compounds established more stable complexes with CK1 α than the reference compound, LCI. The free energy landscape indicated that the inhibitors didn't significantly alter CK1 α 's initial configuration. Additionally, density functional theory (DFT) analyses of density of states, molecular electrostatic potential, frontier molecular orbitals, localized orbital locator, electron localization function, and reduced density gradient offered crucial insights into the reactivity of these compounds, highlighting them as promising candidates for effective CK1 α inhibition and advancing the development of potential cancer therapeutics.