Protein structural alignment plays a key role in defining gold standards for a variety of bioinformatics applications. These include homology assessment, phylogenetic tree construction and multiple sequence alignment evaluation. Our recent findings [1] however showed that superposition methods are rather sensitive to structural variation. To sidestep the problem of alignment variability, golden standards are often derived from the more conserved and 'trusted' regions. It therefore remains

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... r which Figure 1 Structure and function analysis of alignment variability by means of the standard deviation of residue shifts over an ensemble of alternate alignments (sigma). (A) Shows the fraction of helical residues increasing with higher variability at the cost of the fraction of coil residues. (B) Shows the even distribution of functional sites (as grouped by Prosite) over a large range of variability.