Title: Identification of protein hot regions by combining structure-based classification, energy-based clustering and sequence-based conservation in evolution

Authors: Jing Hu; Haomin Gan; Nansheng Chen; Xiaolong Zhang

Addresses: School of Computer Science and Technology, Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, Hubei, China; Molecular Biology and Biochemistry, Simon Fraser University, Burnaby/Surrey, British Columbia, Canada ' School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' Molecular Biology and Biochemistry, Simon Fraser University, Burnaby/Surrey, British Columbia, Canada ' School of Computer Science and Technology, Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, Hubei, China

Abstract: Revealing the protein hot regions is the key point for understanding the protein-protein interaction, while due to the long period and labour-consuming of experimental methods, it is very helpful to use computational method to improve the efficiency to predict hot regions. In previous methods, some methods are based on a single side, such as structure, energy, and sequence, every side has its limitations. In this paper, we proposed a new method that combines structure-based classification, energy-based clustering and sequence-based conservation. This method makes full use of three sides of protein features and minimise the limitations of using one single side. Experimental results show that the proposed method increases the prediction accuracy of protein hot regions.

Keywords: hot region; protein structure; energy clustering; sequence conservation; protein-protein interaction.

DOI: 10.1504/IJDMB.2020.109503

International Journal of Data Mining and Bioinformatics, 2020 Vol.24 No.1, pp.74 - 95

Received: 07 Apr 2020
Accepted: 07 Apr 2020
Published online: 10 Sep 2020 *

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