Journal of Guangxi Normal University(Natural Science Edition) ›› 2020, Vol. 38 ›› Issue (6): 40-50.doi: 10.16088/j.issn.1001-6600.2020.06.005

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Classification of Protein 3D Structure Based on Adaptive Local Features

ZHANG Ruchang1, QIU Jie2*, WANG Mingtang2, CHEN Qingfeng1*   

  1. 1. School of Computer Electronics and Information, Guangxi University, Nanning Guangxi 530004, China;
    2. School of Computer Science and Engineering, Yulin Normal University, Yulin Guangxi 537000, China
  • Received:2020-03-30 Published:2020-11-30

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Abstract: The three-dimensional spatial structure of protein determine its biological function. Structural similarity between proteins can be a good predictor of functional correlations. In this paper, the Cα atomic distance matrix of protein is decomposed into many small sub-matrices that represent the local structure of the protein. Through the statistical analysis of these local structures, a local feature frequency vector is obtained to calculate the similarity of the protein. Consequently, a new method to measure the similarity of protein structure by adaptive local feature frequency vector (ALFF) is proposed. In the way of selecting the local features of protein in ALFF, OTSU is adopted to determine the most appropriate size of the local features m, and MeanShift is applied to find the representative number of local features k, respectively. Experimental results demonstrate that ALFF can achieve better and faster division of the local substructures of proteins. In addition, compared with the method of manual selection of parameters, ALFF has higher consistency in protein structure classification and better accuracy in TM-score comparison.

Key words: protein structural similarity, local feature, distance matrix, clustering, frequency vector

CLC Number: 

  • TP39
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