Literature DB >> 10902154

Protein folds in the worm genome.

M Gerstein1, J Lin, H Hegyi.   

Abstract

We survey the protein folds in the worm genome, using pairwise and multiple-sequence comparison methods (i.e. FASTA and PSI-blast). Overall, we find that approximately 250 folds match approximately 8000 domains in approximately 4500 ORFs, about 32 matches per fold involving a quarter of the total worm ORFs. We compare the folds in the worm genome to those in other model organisms, in particular yeast and E. coli, and find that the worm shares more folds with the phylogenetically closer yeast than with E. coli. There appear to be 36 folds unique to the worm compared to these two model organisms, and many of these are obviously implicated in aspects of multicellularity. The most common fold in the worm genome is the immunoglobulin fold, and many of the common folds are repeated in various combinations and permutations in multidomain proteins. In addition, an approach is presented for the identification of "sure" and "marginal" membrane proteins. When applied to the worm genome, this reveals a much greater relative prevalence of proteins with seven transmembrane helices in comparison to the other completely sequenced genomes, which are not of metazoans. Combining these analyses with some other simple filters allows one to identify ORFs that potentially code for soluble proteins of unknown fold, which may be promising targets for experimental investigation in structural genomics. A regularly updated worm fold analysis will be available from bioinfo.mbb.yale.edu/genome/worm.

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Year:  2000        PMID: 10902154     DOI: 10.1142/9789814447331_0004

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  5 in total

1.  PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information.

Authors:  J Qian; B Stenger; C A Wilson; J Lin; R Jansen; S A Teichmann; J Park; W G Krebs; H Yu; V Alexandrov; N Echols; M Gerstein
Journal:  Nucleic Acids Res       Date:  2001-04-15       Impact factor: 16.971

2.  Cross-talk between catalytic and regulatory elements in a DEAD motor domain is essential for SecA function.

Authors:  G Sianidis; S Karamanou; E Vrontou; K Boulias; K Repanas; N Kyrpides; A S Politou; A Economou
Journal:  EMBO J       Date:  2001-03-01       Impact factor: 11.598

3.  SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics.

Authors:  P Bertone; Y Kluger; N Lan; D Zheng; D Christendat; A Yee; A M Edwards; C H Arrowsmith; G T Montelione; M Gerstein
Journal:  Nucleic Acids Res       Date:  2001-07-01       Impact factor: 16.971

4.  GeneCensus: genome comparisons in terms of metabolic pathway activity and protein family sharing.

Authors:  J Lin; J Qian; D Greenbaum; P Bertone; R Das; N Echols; A Senes; B Stenger; M Gerstein
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

5.  Digging for dead genes: an analysis of the characteristics of the pseudogene population in the Caenorhabditis elegans genome.

Authors:  P M Harrison; N Echols; M B Gerstein
Journal:  Nucleic Acids Res       Date:  2001-02-01       Impact factor: 16.971

  5 in total

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