From Protein Structure to Function with Bioinformatics.pdf

36 L.A. Kelleyto limit the positions and sizes of gaps to likely regions of the template structure,e.g. between conserved secondary structure elements (Madej et al. 1995). Anotherapproach is the ‘frozen approximation’ (Fig. 2.3, left) (Westhead et al. 1995). Wenoted above that the chief problem in calculating the score for a particular residuealigned to a structural position, is that we already need to know how all the otherresidues are aligned, i.e. the environment of the residue. Since we don’t know this,the frozen approximation assumes the environment is that of the template sequenceitself. This is an elegantly simple solution that will clearly be a good approximationwhen the sequence of interest and the template sequence are similar. However, itwill fail when the sequences are highly divergent – which happens to be exactly thekind of case we need to solve.A more subtle variant of the frozen approximation was developed by (Skolnickand Kihara 2000) called the ‘defrosted approximation’ (Fig. 2.3, right). Here theenvironment of a residue is not taken from the template structure, but from an initial trialalignment of the query sequence with the structure using conventional profile-basedalignment techniques. This means at least the environment is based on the correctsequence, although the reliability of the resulting energy calculation will be largelyFig. 2.3 Cartoon representation of threading. Left: The frozen approximation – here residue Mfrom the query sequence is tentatively aligned to V in the template structure. An empirical potentialis then evaluated for having an M residue surrounded by the environment G, L and F – takendirectly from the native template structure. Right: The defrosted approximation. A trial alignmenthas first been generated using, e.g. Profile alignment techniques. The environment around M isnow taken to be the environment resulting from the trial alignment. Faded sections indicate originaltemplate residues