As the number of available 3D protein structures increases rapidly, a wider variety of studies can be conducted more efficiently, among which is the design of protein structural alphabet. With the structural alphabet, not only can we describe the global folding structure of a protein as a 1D sequence, but we can also characterize local structures in proteins. Previously, we applied a combinatorial approach to protein structural alphabet design. In our previous work, we verified the usefulness of our structural alphabet by demonstrating the competitive accuracy in protein alignment, compared with alphabets. Here we took a further step by applying motif finding tools to our alphabet with the aim to characterize protein structure local features. Two structure domains, TIM and EGF, were used to evaluate the performance of our structural alphabet. Our method successfully recovered their sub-domains as common motifs in our structural alphabet.