Co-Clustering Analysis of Protein Secondary Structures

Title:Co-Clustering Analysis of Protein Secondary Structures

Volume: 12 Issue: 3

Author(s): Lichun Ma*, Debby D. Wang, Xinyu Liu, Bin Zou and Hong Yan

Affiliation:

• Department of Electronic Engineering, City University of Hong Kong, 2384 Fong Yun-Wah Building, Kowloon,Hong Kong

Keywords: Protein secondary structure, α-helix, β-strand, co-clustering, clustering.

Abstract: Background: The protein secondary structure provides a crucial link between a protein sequence and its final 3D structure. Thus, accurate prediction of protein secondary structure becomes very important.

Objective: In this study, we try to obtain a subset of highly regular features of the protein secondary structures. Then these features can be used in the prediction of other chains’ secondary structures.

Method: The experiment data was obtained from the Dictionary of Protein Secondary Structure (DSSP), in which eight types of secondary structures are defined. We carried out statistical analysis of the amino acids for each type of secondary structure and then concentrated our attention on α-helix and β-strand, the two most common regular secondary structures. The features of amino acids, neighbors, and hydrogen bonds (α-helix) were extracted. Then a co-clustering based method was conducted to analyze α-helix and β-strand chain-feature matrices, respectively.

Results and Conclusion: By using the features obtained from the co-clustering process, we are able to predict other chains’ structures. The prediction performs well for β-strands and long α-helices but poorly for short α-helices. Then, we further represented the features of each short α-helix by a vector. Afterwards, the prediction was made by comparing the testing vector and the training vectors in coclusters. Results show that the testing accuracy for short α-helices can reach 96% when using amino acid features as a vector. Therefore, the secondary structure of a protein sequence can be predicted with a high accuracy by using the co-clustering based method.

Cite this article as:

Ma Lichun*, Wang D. Debby, Liu Xinyu, Zou Bin and Yan Hong, Co-Clustering Analysis of Protein Secondary Structures, Current Bioinformatics 2017; 12 (3) . https://dx.doi.org/10.2174/1574893612666170111145319

DOI https://dx.doi.org/10.2174/1574893612666170111145319	Print ISSN 1574-8936
Publisher Name Bentham Science Publisher	Online ISSN 2212-392X