Neuropeptides are a group of neuronal signaling molecules that regulate physiological and behavioral processes in animals. Here, we used in silico mining to predict the polypeptide composition of available transcriptomic data of Turbinaria peltata. In total, 118 transcripts encoding putative peptide precursors were discovered. One neuropeptide Y/F-like peptide, named TpNPY, was identified and selected for in silico structural, in silico binding, and pharmacological studies. In our study, the anti-inflammation effect of TpNPY was evaluated using an LPS-stimulated C8-D1A astrocyte cell model. Our results demonstrated that TpNPY, at 0.75-3 μM, inhibited LPS-induced NO production and reduced the expression of iNOS in a dose-dependent manner. Furthermore, TpNPY reduced the secretion of proinflammatory cytokines. Additionally, treatment with TpNPY reduced LPS-mediated elevation of ROS production and the intracellular calcium concentration. Further investigation revealed that TpNPY downregulated the IKK/IκB/NF-κB signaling pathway and inhibited expression of the NLRP3 inflammasome. Through molecular docking and using an NPY receptor antagonist, TpNPY was shown to have the ability to interact with the NPY Y1 receptor. On the basis of these findings, we concluded that TpNPY might prevent LPS-induced injury in astrocytes through activation of the NPY-Y1R.