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Chu CH, Lo WC, Wang HW, Hsu YC, Hwang JK, Lyu PC, Pai TW, Tang CY. Detection and alignment of 3D domain swapping proteins using angle-distance image-based secondary structural matching techniques. PLoS One 2010; 5:e13361. [PMID: 20976204 PMCID: PMC2955075 DOI: 10.1371/journal.pone.0013361] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2010] [Accepted: 09/13/2010] [Indexed: 11/18/2022] Open
Abstract
This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had “opened” their “closed” structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications.
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Affiliation(s)
- Chia-Han Chu
- Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan, Republic of China
| | - Wei-Cheng Lo
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan, Republic of China
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan, Republic of China
| | - Hsin-Wei Wang
- Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan, Republic of China
| | - Yen-Chu Hsu
- Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan, Republic of China
| | - Jenn-Kang Hwang
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan, Republic of China
| | - Ping-Chiang Lyu
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan, Republic of China
| | - Tun-Wen Pai
- Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan, Republic of China
- * E-mail: (T-WP); (CYT)
| | - Chuan Yi Tang
- Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan, Republic of China
- Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan, Republic of China
- * E-mail: (T-WP); (CYT)
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Hasegawa H, Holm L. Advances and pitfalls of protein structural alignment. Curr Opin Struct Biol 2009; 19:341-8. [PMID: 19481444 DOI: 10.1016/j.sbi.2009.04.003] [Citation(s) in RCA: 303] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2009] [Accepted: 04/16/2009] [Indexed: 11/30/2022]
Abstract
Structure comparison opens a window into the distant past of protein evolution, which has been unreachable by sequence comparison alone. With 55,000 entries in the Protein Data Bank and about 500 new structures added each week, automated processing, comparison, and classification are necessary. A variety of methods use different representations, scoring functions, and optimization algorithms, and they generate contradictory results even for moderately distant structures. Sequence mutations, insertions, and deletions are accommodated by plastic deformations of the common core, retaining the precise geometry of the active site, and peripheral regions may refold completely. Therefore structure comparison methods that allow for flexibility and plasticity generate the most biologically meaningful alignments. Active research directions include both the search for fold invariant features and the modeling of structural transitions in evolution. Advances have been made in algorithmic robustness, multiple alignment, and speeding up database searches.
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Affiliation(s)
- Hitomi Hasegawa
- Institute of Biotechnology, University of Helsinki, P.O. Box 56 (Viikinkaari 5), 00014 University of Helsinki, Finland
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