Target space for structural genomics revisited

Bioinformatics. 2002 Jul;18(7):922-33. doi: 10.1093/bioinformatics/18.7.922.

Abstract

Motivation: Structural genomics eventually aims at determining structures for all proteins. However, in the beginning experimentalists are likely to focus on globular proteins to achieve a rapid basic coverage of protein sequence space. How many proteins will structural genomics have to target? How many proteins will be excluded since we already have structural information for these or since they are not globular? We have to answer these questions in the context of our target selection for the North-East Structural Genomics Consortium (NESG).

Results: We estimated that structural information is available for about 6-38% of all proteins; 6% if we require high accuracy in comparative modelling, 38% if we are satisfied with having a rough idea about the fold. Excluding all regions that are not globular, we found that structural genomics may have to target about 48% of all proteins. This corresponded to a similar percentage of residues of the entire proteomes (52%). We explored a number of different strategies to cluster protein space in order to find the number of families representing these 48% of structurally unknown proteins. For the subset of all entirely sequenced eukaryotes, we found over 18 000 fragment clusters each of which may be a suitable target for structural genomics.

Availability: All data are available from the authors, most results are summarized at: http://cubic.bioc.columbia.edu/genomes/RES/2002_bioinformatics/

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms
  • Cluster Analysis*
  • Database Management Systems
  • Databases, Protein*
  • Eukaryotic Cells / chemistry
  • Genome*
  • Humans
  • Information Storage and Retrieval / methods
  • Internet
  • Models, Chemical
  • Models, Genetic
  • Models, Molecular
  • Models, Statistical
  • Proteins / chemistry*
  • Proteins / classification
  • Proteins / genetics*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Sequence Analysis, Protein / methods*

Substances

  • Proteins