In molecular biology, classification of 3D protein structures is a very important topic. In this paper, from the view of geometry, we propose one kind of feature called SID ( I D , Structure Information Dimension) for describing 3D protein structures in order to perform similarity search and classification. The goal of the approach is to reduce the 3D protein structures matching problem to the comparison of the probability distribution. Experimental results show the proposed approach is effective to pre-classification of 3d proteins, and needs less computation and storage cost comparing to the existing methods, the proposed feature of 3d protein is invariant to the translation, rotation and scale of 3d protein structures.