StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase
1 Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
2 National Science Foundation, Arlington, VA 22230, USA
3 Department of Microbiology and Immunology, University of California, San Francisco, CA 94143, USA
BMC Bioinformatics 2011, 12:226 doi:10.1186/1471-2105-12-226Published: 2 June 2011
Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures.
Here we present StralSV (
StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/ webcite.