One of the major challenges in the area of novel drug delivery systems (NDDSs) is finding distinguished ligands for specific receptors represented by many cancer cells in order to enhance their cancer homing efficacy. Exosomes, the so-called natural nanocarriers or "Trojan horses,'' are secreted by the majority of cancer cells. These carriers exchange biomolecular information (e.g. proteins, siRNA, enzymes) between cancer cells and their stromal compartments in order to adjust a variety of cellular behaviours, including metastasis, apoptosis in T cells and angiogenesis. By exhibiting exosomal smart functions and biomimetic traits, exosome-mimicking nanocarriers will be one step ahead of the conventional targeted DDSs for the efficient delivery of antitumor drugs. In the present study, we tried to describe an engineering route to make some surface-functionalized nanoparticles that can mimic the targeting mechanism recruited by tumor-derived exosomes. The ligand-receptor interactions were investigated by molecular dynamics (MD) simulations. In addition, the selected ligand was experimentally studied to verify its improved targeting efficacy. The present study describes a novel targeting method that forces the mucin-domain-containing molecule-4 (TIM4)-embellished nanoparticles (NPs) to swarm towards the cancerous cells. These NPs can interact with the phosphatidylserine (PS) receptor on the surface of several kinds of cancer cells, such as U-87 MG (glioblastoma cell line). The molecular affinity between TIM4 as a homing device and PS, the target receptor, was investigated using MD simulations and surface plasmon resonance (SPR). According to the calculated free energies and the cellular uptake of TIM4-functionalized NPs, it seems that the TIM4/PS complex releases enough free energy to induce endocytosis. Our results emphasize on the potential of the proposed ligand as a good candidate for many targeted drug delivery applications. In this report, we present our proof-of-concept results in order to spotlight the importance of using computer-based simulating methods at the molecular level for the next-generation nanomedicine.