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INTREPID—INformation-theoretic TREe traversal for Protein functional site IDentification
Author(s) -
Sriram Sankararaman,
Kimmen Sjölander
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn474
Subject(s) - tree traversal , computer science , exploit , identification (biology) , computational biology , tree (set theory) , phylogenetic tree , sequence alignment , data mining , artificial intelligence , biology , genetics , peptide sequence , mathematics , algorithm , gene , ecology , mathematical analysis , computer security
Identification of functionally important residues in proteins plays a significant role in biological discovery. Here, we present INTREPID--an information-theoretic approach for functional site identification that exploits the information in large diverse multiple sequence alignments (MSAs). INTREPID uses a traversal of the phylogeny in combination with a positional conservation score, based on Jensen-Shannon divergence, to rank positions in an MSA. While knowledge of protein 3D structure can significantly improve the accuracy of functional site identification, since structural information is not available for a majority of proteins, INTREPID relies solely on sequence information. We evaluated INTREPID on two tasks: predicting catalytic residues and predicting specificity determinants.

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