Toward Consistent Assignment of Structural Domains in Proteins

Veretnik, Stella; Bourne, Philip E.; Alexandrov, Nickolai N.; Shindyalov, Ilya N.

doi:10.1016/j.jmb.2004.03.053

Cited by 65 publications

(53 citation statements)

References 37 publications

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“…This paper cites some examples of proteins (1AVHA, 1TAHB, 5FBP, 1GPB, 1SMR, and 1CHRA) for which there is no consensus on domain definitions between the established methods. On examining these proteins by our method, we find that the results obtained from both PBG as well as PScG representation agree very well with CATH and to a good extent with AUTHORS (This is an annotation given by Veretnik et al 9 for domain definitions given by the authors of the respective crystal structure papers as compiled by Islam et al 5 ).…”

Section: Comparison Of the Present Methods With Scop Cath And Domainsupporting

confidence: 61%

“…Subsequent to the completion of the current work, Veretnik et al 9 reported their findings on domain definitions by various methods. This paper cites some examples of proteins (1AVHA, 1TAHB, 5FBP, 1GPB, 1SMR, and 1CHRA) for which there is no consensus on domain definitions between the established methods.…”

Section: Comparison Of the Present Methods With Scop Cath And Domainmentioning

confidence: 99%

“…before the entry is made in the database. Veretnik et al 9 have recently published an exhaustive comparison of various algorithmic and expert methods of domain assignment and commented on the inconsistencies present in various methods. They have also listed out the central issues that have to be addressed for arriving at a consistent definition of structural domains.…”

Section: Introductionmentioning

confidence: 99%

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Identification of domains and domain interface residues in multidomain proteins from graph spectral method

2005

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We present a novel method for the identification of structural domains and domain interface residues in proteins by graph spectral method. This method converts the three-dimensional structure of the protein into a graph by using atomic coordinates from the PDB file. Domain definitions are obtained by constructing either a protein backbone graph or a protein side-chain graph. The graph is constructed based on the interactions between amino acid residues in the three-dimensional structure of the proteins. The spectral parameters of such a graph contain information regarding the domains and subdomains in the protein structure. This is based on the fact that the interactions among amino acids are higher within a domain than across domains. This is evident in the spectra of the protein backbone and the side-chain graphs, thus differentiating the structural domains from one another. Further, residues that occur at the interface of two domains can also be easily identified from the spectra. This method is simple, elegant, and robust. Moreover, a single numeric computation yields both the domain definitions and the interface residues.

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Section: Comparison Of the Present Methods With Scop Cath And Domainsupporting

confidence: 61%

Section: Comparison Of the Present Methods With Scop Cath And Domainmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of domains and domain interface residues in multidomain proteins from graph spectral method

2005

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“…A domain is either defined based on sequence (regions that display a significant level of sequence similarity), function (the minimal part of a gene that is capable of performing a function) or structure (compact, spatially distinct units of protein structure) [38]. When the structure of the protein is known, its domains are usually defined by a combination of visual inspection of the structure with automated methods that take into account the globular nature of domains (for a review of existing methods, see [38]). It would be of practical interest to delineate domain boundaries in protein sequence alone, as this information would facilitate structure and function prediction.…”

Section: Blv62: Information In Each Dimensionmentioning

confidence: 99%

A Geometric Representation of Protein Sequences

Wang

et al. 2007

2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007)

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The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the visualization of protein sequences facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D) space derived from substitution matrices provides an adequate representation from which the domain content of a protein can be predicted. In addition, we show that each dimension of the feature space can be related to a physical property of the amino acids.

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“…One could also match known structures using structural alignment (25). Parsing the chains into structural domains could be done as described above for sequence matching and augmented with automated domain finding programs (26).…”

Section: Discussionmentioning

confidence: 99%

Growth of novel protein structural data

Levitt

2007

Proc. Natl. Acad. Sci. U.S.A.

145

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Contrary to popular assumption, the rate of growth of structural data has slowed, and the Protein Data Bank (PDB) has not been growing exponentially since 1995. Reaching such a dramatic conclusion requires careful measurement of growth of novel structures, which can be achieved by clustering entry sequences, or by using a novel index to down-weight entries with a higher number of sequence neighbors. These measures agree, and growth rates are very similar for entire PDB files, clusters, and weighted chains.

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Toward Consistent Assignment of Structural Domains in Proteins

Cited by 65 publications

References 37 publications

Identification of domains and domain interface residues in multidomain proteins from graph spectral method

Identification of domains and domain interface residues in multidomain proteins from graph spectral method

A Geometric Representation of Protein Sequences

Growth of novel protein structural data

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