Context <p>Damnacanthal (<b>DAM</b>) is a naturally occurring anthraquinone with notable anticancer activity. In this study, five DAM derivatives (WM1–WM5) have been theoretically investigated, and the results are compared with the reference DAM molecule (R) to elucidate structural relationships governing biological activity and drug efficacy. <b>WM3</b> displayed the highest λ_max, and the lowest excitation energy, attributed to the strong electron-withdrawing bromo substituent in the acceptor moiety. The <b>WM4</b> molecule showed the lowest LUMO energy and bandgap among all. Furthermore, structure-based molecular docking against the CHK1 receptor demonstrated that all derivatives (WM1–WM5) possess stronger binding affinities than the reference compound and the co-crystallized ligand, supporting their enhanced anticancer potential. Strong charge transfer and H-bonding&#xa0;interactions are made possible by the synergistic action of electron-donating OH&#xa0;groups and an electron-withdrawing aldehyde group in <b>WM4</b>, which results in increased biological activity. So, overall, these findings highlight WM4 as a promising optoelectronic and anticancer candidate, offering valuable insights for the rational design of DAM-based therapeutic agents. <b>WM4</b> exhibits the best performance despite differences in optoelectronic parameters. It integrates the highest docking affinity with advantageous electronic characteristics like low reduced energy bandgap (high reactivity and potential interaction), making it the most promising candidate for anticancer activity.</p> Method <p>Density functional theory (<b>DFT</b>) and time-dependent DFT (<b>TD-DFT</b>) were used to conduct computational studies of <b>WM1–WM5</b> and the reference molecule (<b>R</b>). The B3LYP/6-311G(d,p) level of theory was used for all geometric optimization, excited-state evaluations, and electronic property simulations. The CPCM model was used to investigate the effects of chloroform solvent on adsorption. Different parameters like optimal geometries, binding energies, excitation energies, frontier molecular orbitals (<b>FMOs</b>), transition density matrices (<b>TDMs</b>), molecular electrostatic potential (<b>MEP</b>), and density of states (<b>DOS</b>) were evaluated. Structure-based virtual screening was carried out by using the <b>CHKl</b> receptor to investigate drug-protein interactions. Docking simulations were performed to evaluate binding affinities and interaction patterns by utilizing AutoDock Vina.</p>