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  4. Enhancement of initial equivalency for protein structure alignment based on encoded local structures
 
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Enhancement of initial equivalency for protein structure alignment based on encoded local structures

Journal
IEEE Transactions on Information Technology in Biomedicine
Journal Volume
16
Journal Issue
6
Pages
1185-1192
Date Issued
2012
Author(s)
Hung, K.
Wang, J.-C.
Chen, C.-W.
Chuang, C.-L.
Tsai, K.-N.
CHUNG-MING CHEN  
CHENG-WEI CHEN  
DOI
10.1109/TITB.2012.2204892
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/463820
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870928544&doi=10.1109%2fTITB.2012.2204892&partnerID=40&md5=24ba652130b15b5d6ecfe33b09b260e0
Abstract
Most alignment algorithms find an initial equivalent residue pair followed by an iterative optimization process to explore better near-optimal alignments in the surrounding solution space of the initial alignment. It plays a decisive role in determining the alignment quality since a poor initial alignment may make the final alignment trapped in an undesirable local optimum even with an iterative optimization. We proposed a vector-based alignment algorithm with a new initial alignment approach accounting for local structure features called MIRAGE-align. The new idea is to enhance the quality of the initial alignment based on encoded local structural alphabets to identify the protein structure pair whose sequence identity falls in or below twilight zone. The statistical analysis of alignment quality based on Match Index (MI) and computation time demonstrated that MIRAGE-align algorithm outperformed four previously published algorithms, i.e., the residue-based algorithm (CE), the vector-based algorithm (SSM), TM-align, and Fr-TM-align. MIRAGE-align yields a better estimate of initial solution to enhance the quality of initial alignment and enable the employment of a non-iterative optimization process to achieve a better alignment.
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Type
journal article

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