unified genetic, computational and experimental framework identifies functionally relevant residues of the homing endonuclease I-BmoI
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 previ...
Gespeichert in:
Veröffentlicht in: | Nucleic acids research 2010-04, Vol.38 (7), p.2411-2427 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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 ~90 amino acids. |
---|---|
ISSN: | 0305-1048 1362-4962 |
DOI: | 10.1093/nar/gkp1223 |