Expectations from structural genomics revisited: an analysis of structural genomics targets.
BACKGROUND
Current structural genomics projects are being driven by two main goals; to produce a representative set of protein folds that could be used as templates for comparative modeling purposes, and to provide insight into the function of the currently unannotated protein sequences. Such projects may reveal that a newly determined protein structure shares structural similarity with a previously observed structure or that it is a novel fold. The manner in which structure can be used to suggest the function of a protein will depend on the number and diversity of homologous sequences and the extent to which these sequences are functionally characterized.


RESULTS
Using sequence searching methods, we analyzed structural genomics target sequences to ascertain if they were members of functionally characterized protein families, protein families of unknown function, or orphan sequences. This analysis provided an indication of what could be expected to emerge from structural genomics projects. Matches were found to approximately 25% of the current functionally unannotated protein families in the PFAM database (protein families database of alignments and hidden Markov models). The 16% of strict orphan sequences will be the most problematic if their structures reveal novel folds. However, out of the remaining target sequences that match families whose members are largely of unknown function, 28% are particularly interesting in that they are part of protein families with considerable sequence diversity.


CONCLUSIONS
The determination of a new structure of a member of these families is likely to offer considerable insight into possible functional roles of these proteins even if it is a new fold. Mapping the sequence conservation onto the structure may reveal functionally important residues for further study by experimental methods.
Saqi
Mansoor A S
MA
Queen Mary's School of Medicine and Dentistry, Institute of Cell and Molecular Sciences, Barts and The London, Queen Mary, University of London, London, England.
Wild
David L
DL
D030562:Databases, Protein; D023281:Genomics; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000502:physiology
D011506:Proteins