Abstract: In this paper, we represent protein structure by using
graph. A protein structure database will become a graph database.
Each graph is represented by a spectral vector. We use Jacobi
rotation algorithm to calculate the eigenvalues of the normalized
Laplacian representation of adjacency matrix of graph. To measure
the similarity between two graphs, we calculate the Euclidean
distance between two graph spectral vectors. To cluster the graphs,
we use M-tree with the Euclidean distance to cluster spectral vectors.
Besides, M-tree can be used for graph searching in graph database.
Our proposal method was tested with graph database of 100 graphs
representing 100 protein structures downloaded from Protein Data
Bank (PDB) and we compare the result with the SCOP hierarchical
structure.