Literature DB >> 15273305

A classification of disulfide patterns and its relationship to protein structure and function.

Abhas Gupta1, Herman W T Van Vlijmen, Juswinder Singh.   

Abstract

We report a detailed classification of disulfide patterns to further understand the role of disulfides in protein structure and function. The classification is applied to a unique searchable database of disulfide patterns derived from the SwissProt and Pfam databases. The disulfide database contains seven times the number of publicly available disulfide annotations. Each disulfide pattern in the database captures the topology and cysteine spacing of a protein domain. We have clustered the domains by their disulfide patterns and visualized the results using a novel representation termed the "classification wheel." The classification is applied to 40,620 protein domains with 2-10 disulfides. The effectiveness of the classification is evaluated by determining the extent to which proteins of similar structure and function are grouped together through comparison with the SCOP and Pfam databases, respectively. In general, proteins with similar disulfide patterns have similar structure and function, even in cases of low sequence similarity, and we illustrate this with specific examples. Using a measure of disulfide topology complexity, we find that there is a predominance of less complex topologies. We also explored the importance of loss or addition of disulfides to protein structure and function by linking classification wheels through disulfide subpattern comparisons. This classification, when coupled with our disulfide database, will serve as a useful resource for searching and comparing disulfide patterns, and understanding their role in protein structure, folding, and stability. Proteins in the disulfide clusters that do not contain structural information are prime candidates for structural genomics initiatives, because they may correspond to novel structures.

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Year:  2004        PMID: 15273305      PMCID: PMC2279833          DOI: 10.1110/ps.04613004

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  22 in total

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Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003.

Authors:  Brigitte Boeckmann; Amos Bairoch; Rolf Apweiler; Marie-Claude Blatter; Anne Estreicher; Elisabeth Gasteiger; Maria J Martin; Karine Michoud; Claire O'Donovan; Isabelle Phan; Sandrine Pilbout; Michel Schneider
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

3.  Protein structure alignment by incremental combinatorial extension (CE) of the optimal path.

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Review 4.  Ly-6-domain proteins--new insights and new members: a C-terminal Ly-6 domain in sperm acrosomal protein SP-10.

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Journal:  Tissue Antigens       Date:  1996-08

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Review 6.  Protein disulfide bond determination by mass spectrometry.

Authors:  Jeffrey J Gorman; Tristan P Wallis; James J Pitt
Journal:  Mass Spectrom Rev       Date:  2002 May-Jun       Impact factor: 10.946

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Authors:  P M Harrison; M J Sternberg
Journal:  J Mol Biol       Date:  1996-12-06       Impact factor: 5.469

8.  SCOP: a structural classification of proteins database for the investigation of sequences and structures.

Authors:  A G Murzin; S E Brenner; T Hubbard; C Chothia
Journal:  J Mol Biol       Date:  1995-04-07       Impact factor: 5.469

9.  The CRIPTO/FRL-1/CRYPTIC (CFC) domain of human Cripto. Functional and structural insights through disulfide structure analysis.

Authors:  Susan F Foley; Herman W T van Vlijmen; Raymond E Boynton; Heather B Adkins; Anne E Cheung; Juswinder Singh; Michele Sanicola; Carmen N Young; Dingyi Wen
Journal:  Eur J Biochem       Date:  2003-09

Review 10.  Disulfide proteome in the analysis of protein function and structure.

Authors:  Hiroyuki Yano; Shigeru Kuroda; Bob B Buchanan
Journal:  Proteomics       Date:  2002-09       Impact factor: 3.984

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  7 in total

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2.  Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins.

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Journal:  Bioinformatics       Date:  2015-08-07       Impact factor: 6.937

3.  Amino acid patterns around disulfide bonds.

Authors:  José R F Marques; Rute R da Fonseca; Brett Drury; André Melo
Journal:  Int J Mol Sci       Date:  2010-11-18       Impact factor: 5.923

4.  Identification and Characterization of a Novel Family of Cysteine-Rich Peptides (MgCRP-I) from Mytilus galloprovincialis.

Authors:  Marco Gerdol; Nicolas Puillandre; Gianluca De Moro; Corrado Guarnaccia; Marianna Lucafò; Monica Benincasa; Ventislav Zlatev; Chiara Manfrin; Valentina Torboli; Piero Giulio Giulianini; Gianni Sava; Paola Venier; Alberto Pallavicini
Journal:  Genome Biol Evol       Date:  2015-07-21       Impact factor: 3.416

5.  Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

Authors:  David T Barkan; Xiao-Li Cheng; Herodion Celino; Tran T Tran; Ashok Bhandari; Charles S Craik; Andrej Sali; Mark L Smythe
Journal:  BMC Bioinformatics       Date:  2016-11-23       Impact factor: 3.169

6.  Secreted Cysteine-Rich Repeat Proteins "SCREPs": A Novel Multi-Domain Architecture.

Authors:  Michael Maxwell; Eivind A B Undheim; Mehdi Mobli
Journal:  Front Pharmacol       Date:  2018-11-20       Impact factor: 5.810

7.  A word of caution about biological inference - Revisiting cysteine covalent state predictions.

Authors:  Eva Tüdős; Bálint Mészáros; András Fiser; István Simon
Journal:  FEBS Open Bio       Date:  2014-03-12       Impact factor: 2.693

  7 in total

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