title:An Accurate, Sensitive, and Scalable Method to
Identify Functional Sites in Protein Structures
author:Hui Yao, David M. Kristensen, Ivana Mihalek
Mathew E. Sowa, Chad Shaw, Marek Kimme, Lydia Kavraki
and Olivier Lichtarge
year:2003
place of publish:
abstract:
Functional sites determine the activity and interactions of proteins and as
such constitute the targets of most drugs. However, the exponential
growth of sequence and structure data far exceeds the ability of experimental
techniques to identify their locations and key amino acids. To fill
this gap we developed a computational Evolutionary Trace method that
ranks the evolutionary importance of amino acids in protein sequences.
Studies show that the best-ranked residues form fewer and larger structural
clusters than expected by chance and overlap with functional sites,
but until now the significance of this overlap has remained qualitative.
Here, we use 86 diverse protein structures, including 20 determined by
the structural genomics initiative, to show that this overlap is a recurrent
and statistically significant feature. An automated ET correctly identifies
seven of ten functional sites by the least favorable statistical measure,
and nine of ten by the most favorable one. These results quantitatively
demonstrate that a large fraction of functional sites in the proteome may
be accurately identified from sequence and structure. This should help
focus structure–function studies, rational drug design, protein engineering,
and functional annotation to the relevant regions of a protein.
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