New Measurement for Correlation of Co-evolution Relationship of Subsequences in Protein

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• 作者：Hongyun Gao ; Xiaoqing Yu ; Yongchao Dou…
• 关键词：Mutual information ; Adjacent ; Correlation ; Subsequence ; Pearson’s correlation coefficient
• 刊名：Interdisciplinary Sciences: Computational Life Sciences
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：4
• 页码：364-372
• 全文大小：721 KB
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• 作者单位：Hongyun Gao (1) (2)
  Xiaoqing Yu (3)
  Yongchao Dou (4)
  Jun Wang (5)
  
  1. School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China
  2. Information and Engineering College, Dalian University, Dalian, 116622, China
  3. College of Sciences, Shanghai Institute of Technology, Shanghai, 201418, China
  4. Center for Plant Science and Innovation, School of Biological Sciences, University of Nebraska, Lincoln, NE, 68588, USA
  5. Department of Mathematics, Shanghai Normal University, Shanghai, 200234, China
  
• 刊物主题：Computer Appl. in Life Sciences; Computational Biology/Bioinformatics; Statistics for Life Sciences, Medicine, Health Sciences; Theoretical and Computational Chemistry; Theoretical, Mathematical and Computational Physics; Computational Science and Engineering;
• 出版者：International Association of Scientists in the Interdisciplinary Areas
• ISSN：1867-1462

文摘

Many computational tools have been developed to measure the protein residues co-evolution. Most of them only focus on co-evolution for pairwise residues in a protein sequence. However, number of residues participate in co-evolution might be multiple. And some co-evolved residues are clustered in several distinct regions in primary structure. Therefore, the co-evolution among the adjacent residues and the correlation between the distinct regions offer insights into function and evolution of the protein and residues. Subsequence is used to represent the adjacent multiple residues in one distinct region. In the paper, co-evolution relationship in each subsequence is represented by mutual information matrix (MIM). Then, Pearson’s correlation coefficient: R value is developed to measure the similarity correlation of two MIMs. MSAs from Catalytic Data Base (Catalytic Site Atlas, CSA) are used for testing. R value characterizes a specific class of residues. In contrast to individual pairwise co-evolved residues, adjacent residues without high individual MI values are found since the co-evolved relationship among them is similar to that among another set of adjacent residues. These subsequences possess some flexibility in the composition of side chains, such as the catalyzed environment. Keywords Mutual information Adjacent Correlation Subsequence Pearson’s correlation coefficient