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Similarity Comparison of 3D Protein Structure Based on Riemannian Manifold

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Intelligent Computing Theories and Application (ICIC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10362))

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Abstract

As the representative technology of protein spatial structure exploration, NMR technology provides an unprecedented opportunity for modern life science research. But subsequent large data analysis has become a major problem. It is an important means to study protein structure and functional relationship by known information proteins’ three-dimensional structures to predict the unknown spatial structure of proteins. A method for similarity comparison of 3D protein structures based on Riemannian manifold theory is proposed in this paper. By constructing Cα frames and extracting geometric feature of protein, 3D coordinates of proteins are converted into one dimension sequences with rotation and translation invariance. The Riemann distance is used as the three-dimensional structure similarity degree index. Spatial transformation on protein structure is not needed in this method, which avoiding errors when matching two proteins in the traditional method for registration by the least squares fitting. This method is independent of sequence information completely. It has realistic significance for proteins which do not have a similarity between sequences. Three experiments are designed according to 3 sets of data: proteins of different similarity, ten pairs whose protein structures are more difficult to identify proposed by Fischer, 700 proteins in the HOMSTRAD database. Compared with the traditional method, the experiment results show that the matching accuracy of this method has been greatly enhanced.

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Acknowledgment

The authors thank the members of Machine Learning and Artificial Intelligence Laboratory, School of Computer Science and Technology, Wuhan University of Science and Technology, for their helpful discussion within seminars. This work was supported in part by National Natural Science Foundation of China (No. 61502356).

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Authors and Affiliations

  1. Faculty of Information Engineering, City College Wuhan University of Science and Technology, Wuhan, 430083, China

    Zhou Fengli & Lin Xiaoli

  2. Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System, School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, China

    Lin Xiaoli

Authors
  1. Zhou Fengli
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  2. Lin Xiaoli
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Correspondence to Zhou Fengli .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

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Fengli, Z., Xiaoli, L. (2017). Similarity Comparison of 3D Protein Structure Based on Riemannian Manifold. In: Huang, DS., Jo, KH., Figueroa-García, J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10362. Springer, Cham. https://doi.org/10.1007/978-3-319-63312-1_34

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  • DOI: https://doi.org/10.1007/978-3-319-63312-1_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63311-4

  • Online ISBN: 978-3-319-63312-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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