Searching for similarities of proteins using Structured-based query, has a vital role in many applications like drug discovery and drug design, disease diagnosis and treatment and protein classification. Indexing the protein structure is one approach of searching protein structure for similarities. In this paper we proposed a method to enhance the memory space for storing the indexed data without affecting other performance criteria. Our technique starts by extracting the local feature vectors of proteins structures. Normalization is applied to these vectors components. Finally we use the generalized suffix array to index these vectors. Suffix array is used to return the maximal structural similarities as a result for a structured query. The experimental results, which based on the structural classification of protein (SCOP) dataset, show that our method outperforms existing similar methods in memory utilization. Our results show an enhancement in the memory usage with factor exceeds 50%.