Depression is a common and debilitating neuropsychiatric disorder that necessitates the exploration of novel and effective therapeutic strategies. In this study, a green and efficient synthetic method was developed for the preparation of dihydropyrido [2,3-d]pyrimidine derivatives using TiO₂ nanoparticles as a reusable nanocatalyst under mild conditions. The multicomponent reaction approach employed offers high atom economy, environmental friendliness, and operational simplicity. After structural characterization, the electronic properties, frontier molecular orbitals, and reactivity indices of the synthesized compounds were investigated using density functional theory (DFT). Moreover, molecular docking simulations were performed to predict the binding affinities of the derivatives toward central nervous system (CNS) targets associated with antidepressant activity. A comparative computational analysis with the standard antidepressant Paroxetine indicated similar electronic profiles and potential interactions with the target proteins. Although these results are promising, it is important to note that the predicted antidepressant potential is based solely on in silico data and requires further experimental validation. This integrated computational and synthetic approach provides valuable insights for the early-stage design of novel antidepressant candidates.