A unified genetic, computational and experimental framework identifies functionally relevant residues of the homing endonuclease I-BmoI
- PMID: 20061372
- PMCID: PMC2853131
- DOI: 10.1093/nar/gkp1223
A unified genetic, computational and experimental framework identifies functionally relevant residues of the homing endonuclease I-BmoI
Abstract
Insight into protein structure and function is best obtained through a synthesis of experimental, structural and bioinformatic data. Here, we outline a framework that we call MUSE (mutual information, unigenic evolution and structure-guided elucidation), which facilitated the identification of previously unknown residues that are relevant for function of the GIY-YIG homing endonuclease I-BmoI. Our approach synthesizes three types of data: mutual information analyses that identify co-evolving residues within the GIY-YIG catalytic domain; a unigenic evolution strategy that identifies hyper- and hypo-mutable residues of I-BmoI; and interpretation of the unigenic and co-evolution data using a homology model. In particular, we identify novel positions within the GIY-YIG domain as functionally important. Proof-of-principle experiments implicate the non-conserved I71 as functionally relevant, with an I71N mutant accumulating a nicked cleavage intermediate. Moreover, many additional positions within the catalytic, linker and C-terminal domains of I-BmoI were implicated as important for function. Our results represent a platform on which to pursue future studies of I-BmoI and other GIY-YIG-containing proteins, and demonstrate that MUSE can successfully identify novel functionally critical residues that would be ignored in a traditional structure-function analysis within an extensively studied small domain of approximately 90 amino acids.
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References
-
- Capra JA, Singh M. Predicting functionally important residues from sequence conservation. Bioinformatics. 2007;23:1875–1882. - PubMed
-
- Watson JD, Laskowski RA, Thornton JM. Predicting protein function from sequence and structural data. Curr. Opin. Struct. Biol. 2005;15:275–284. - PubMed
-
- Martin LC, Gloor GB, Dunn SD, Wahl LM. Using information theory to search for co-evolving residues in proteins. Bioinformatics. 2005;21:4116–4124. - PubMed
-
- Tillier ER, Lui TW. Using multiple interdependency to separate functional from phylogenetic correlations in protein alignments. Bioinformatics. 2003;19:750–755. - PubMed
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