Superpose

superpose - structural alignment based on secondary structure matching. It is part of the CCP4 package and was written by Eugene Krissinel of the European Bioinformatics Institute, Cambridge, UK.

Background

"While high sequence similarity almost always implies structural similarity, the opposite is not true. It is therefore expected that three-dimensional alignment will provide more significant clues to protein function and properties than sequence alignment alone".

Most similarity measures are based on the evaluation of the size of common substructures, for example the length of alignment (the longer, the better), and a measure of the distance between them, such as r.m.s.d. (the lower, the better).

Several approaches to protein structure alignment have been explored over the past decade. The techniques used include:

• comparison of distance matrices (DALI; Holm & Sander, 1993);
• analysis of differences in vector distance plots (Orengo & Taylor, 1996);
• minimization of the soap-bubble surface area between two protein backbones (Falicov & Cohen, 1996);
• dynamic programming on pairwise distances between the proteins' residues (Subbiah et al., 1993; Gerstein & Levitt, 1996, 1998);
• secondary-structure elements (SSEs) (Singh & Brutlag, 1997);
• three-dimensional clustering (Vriend & Sander, 1991; Mizuguchi & Go, 1995);
• graph theory (Mitchell et al., 1990; Alexandrov, 1996; Grindley et al., 1993);
• combinatorial extension of alignment path (CE; Shindyalov & Bourne, 1998);
• vector alignment of SSEs (VAST; Gibrat et al., 1996);
• depth-first recursive search on SSE (DEJAVU; Kleywegt & Jones, 1997); and
• many others (Zuker & Somorjai, 1989; Taylor & Orengo, 1989; Godzik & Skolnick, 1994; Russell & Barton, 1992; Sali & Blundell, 1990; Barakat & Dean, 1991; Leluk et al., 2003; Jung & Lee, 2000; Kato & Takahashi, 2001).

External links

• superpose - man page