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Feature amplified voting algorithm for functional analysis of protein superfamily

BACKGROUND: Identifying the regions associated with protein function is a singularly important task in the post-genomic era. Biological studies often identify functional enzyme residues by amino acid sequences, particularly when related structural information is unavailable. In some cases of protein...

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Autores principales: Hung, Che-Lun, Lee, Chihan, Lin, Chun-Yuan, Chang, Chih-Hung, Chung, Yeh-Ching, Yi Tang, Chuan
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999344/
https://www.ncbi.nlm.nih.gov/pubmed/21143781
http://dx.doi.org/10.1186/1471-2164-11-S3-S14
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author Hung, Che-Lun
Lee, Chihan
Lin, Chun-Yuan
Chang, Chih-Hung
Chung, Yeh-Ching
Yi Tang, Chuan
author_facet Hung, Che-Lun
Lee, Chihan
Lin, Chun-Yuan
Chang, Chih-Hung
Chung, Yeh-Ching
Yi Tang, Chuan
author_sort Hung, Che-Lun
collection PubMed
description BACKGROUND: Identifying the regions associated with protein function is a singularly important task in the post-genomic era. Biological studies often identify functional enzyme residues by amino acid sequences, particularly when related structural information is unavailable. In some cases of protein superfamilies, functional residues are difficult to detect by current alignment tools or evolutionary strategies when phylogenetic relationships do not parallel their protein functions. The solution proposed in this study is Feature Amplified Voting Algorithm with Three-profile alignment (FAVAT). The core concept of FAVAT is to reveal the desired features of a target enzyme or protein by voting on three different property groups aligned by three-profile alignment method. Functional residues of a target protein can then be retrieved by FAVAT analysis. In this study, the amidohydrolase superfamily was an interesting case for verifying the proposed approach because it contains divergent enzymes and proteins. RESULTS: The FAVAT was used to identify critical residues of mammalian imidase, a member of the amidohydrolase superfamily. Members of this superfamily were first classified by their functional properties and sources of original organisms. After FAVAT analysis, candidate residues were identified and compared to a bacterial hydantoinase in which the crystal structure (1GKQ) has been fully elucidated. One modified lysine, three histidines and one aspartate were found to participate in the coordination of metal ions in the active site. The FAVAT analysis also redressed the misrecognition of metal coordinator Asp57 by the multiple sequence alignment (MSA) method. Several other amino acid residues known to be related to the function or structure of mammalian imidase were also identified. CONCLUSIONS: The FAVAT is shown to predict functionally important amino acids in amidohydrolase superfamily. This strategy effectively identifies functionally important residues by analyzing the discrepancy between the sequence and functional properties of related proteins in a superfamily, and it should be applicable to other protein families.
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spelling pubmed-29993442010-12-09 Feature amplified voting algorithm for functional analysis of protein superfamily Hung, Che-Lun Lee, Chihan Lin, Chun-Yuan Chang, Chih-Hung Chung, Yeh-Ching Yi Tang, Chuan BMC Genomics Research BACKGROUND: Identifying the regions associated with protein function is a singularly important task in the post-genomic era. Biological studies often identify functional enzyme residues by amino acid sequences, particularly when related structural information is unavailable. In some cases of protein superfamilies, functional residues are difficult to detect by current alignment tools or evolutionary strategies when phylogenetic relationships do not parallel their protein functions. The solution proposed in this study is Feature Amplified Voting Algorithm with Three-profile alignment (FAVAT). The core concept of FAVAT is to reveal the desired features of a target enzyme or protein by voting on three different property groups aligned by three-profile alignment method. Functional residues of a target protein can then be retrieved by FAVAT analysis. In this study, the amidohydrolase superfamily was an interesting case for verifying the proposed approach because it contains divergent enzymes and proteins. RESULTS: The FAVAT was used to identify critical residues of mammalian imidase, a member of the amidohydrolase superfamily. Members of this superfamily were first classified by their functional properties and sources of original organisms. After FAVAT analysis, candidate residues were identified and compared to a bacterial hydantoinase in which the crystal structure (1GKQ) has been fully elucidated. One modified lysine, three histidines and one aspartate were found to participate in the coordination of metal ions in the active site. The FAVAT analysis also redressed the misrecognition of metal coordinator Asp57 by the multiple sequence alignment (MSA) method. Several other amino acid residues known to be related to the function or structure of mammalian imidase were also identified. CONCLUSIONS: The FAVAT is shown to predict functionally important amino acids in amidohydrolase superfamily. This strategy effectively identifies functionally important residues by analyzing the discrepancy between the sequence and functional properties of related proteins in a superfamily, and it should be applicable to other protein families. BioMed Central 2010-12-01 /pmc/articles/PMC2999344/ /pubmed/21143781 http://dx.doi.org/10.1186/1471-2164-11-S3-S14 Text en Copyright ©2010 Chung et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Hung, Che-Lun
Lee, Chihan
Lin, Chun-Yuan
Chang, Chih-Hung
Chung, Yeh-Ching
Yi Tang, Chuan
Feature amplified voting algorithm for functional analysis of protein superfamily
title Feature amplified voting algorithm for functional analysis of protein superfamily
title_full Feature amplified voting algorithm for functional analysis of protein superfamily
title_fullStr Feature amplified voting algorithm for functional analysis of protein superfamily
title_full_unstemmed Feature amplified voting algorithm for functional analysis of protein superfamily
title_short Feature amplified voting algorithm for functional analysis of protein superfamily
title_sort feature amplified voting algorithm for functional analysis of protein superfamily
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999344/
https://www.ncbi.nlm.nih.gov/pubmed/21143781
http://dx.doi.org/10.1186/1471-2164-11-S3-S14
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