Identification of the most putative RNA-interacting residues in protein is an important and challenging problem in a field of molecular recognition. Structural analysis of protein-RNA complexes reveals a strong correlation between interaction residues and their structure. Building on this viewpoint, we have developed a neural network predictor to correctly identify residues involved in protein-RNA interactions from protein sequence and its structural information. The system has been exhaustedly cross-validated with various strategies differing in input encoding, amount of input information, and network architectures. In addition, we have evaluated performance among functional subsets of complexes. Finally, to reflect the properties of protein-RNA complexes in our dataset, two kinds of post-processing method are adopted. The experimental result shows that our system yields not-trivial performance although the residues in interaction sites are too scarce.