Three-dimensional protein model similarity analysis based on salient shape index

Abstract

Background: Proteins play a special role in bioinformatics. The surface shape of a protein, which is an important characteristic of the protein, defines a geometric and biochemical domain where the protein interacts with other proteins. The similarity analysis among protein models has become an important topic of protein analysis, by which it can reveal the structure and the function of proteins.

Results: In this paper, a new protein similarity analysis method based on three-dimensional protein models is proposed. It constructs a feature matrix descriptor for each protein model combined by calculating the shape index (SI) and the related salient geometric feature (SGF), and then analyzes the protein model similarity by using this feature matrix and the extended grey relation analysis.

Conclusions: We compare our method to the Multi-resolution Reeb Graph (MRG) skeleton method, the L1-medial skeleton method and the local-diameter descriptor method. Experimental results show that our protein similarity analysis method is accurate and reliable while keeping the high computational efficiency.

Keywords: Protein model; Salient geometric feature; Shape analysis; Shape index.

Fig. 1

Main steps of our similarity analysis for protein models. For a given 3HLN model, the high SI and SGF areas are colored in red on the 3HLN surface, respectively. The distribution of feature matrix is constructed by the SI and SGF distribution vectors

Fig. 2

1HLB protein model and its geometric feature models. a 1HLB protein model. (a-1) Local area of the vertex A. (a-2) Local area of the vertex B. b Gaussian curvature model of 1HLB protein. c Mean curvature model of 1HLB protein. d Shape index model of 1HLB protein. e Salient geometrical feature model of 1HLB protein

Fig. 3

Feature distribution figures of 1HLB protein model. a Shape index feature distribution. b Salient geometric feature distribution. c Feature distribution combination model of 1HLB protein model

Fig. 4

Four protein models (1BPD, 2BPG, 1WRP and 3WRP). Red regions represent salient shape index areas

Fig. 5

Six protein models from Skolnick dataset (2B3I, 1NIN, 1RCD, 1IER, 1DBW and 1B00)

Fig. 6

Ten protein models from Chew–Kedem dataset (1HLM, 1HLB, 2LHB, 1MBA, 5MBN, 1LH2, 1CHR, 2MNR, 5P21, 1GNP)

Fig. 7

Average linkage of Skolnick's dataset by our method

Fig. 8

1BAR and 1RRO protein models with their feature distributions