Multiple Alignment


Multiple alignment is a powerful integrative tool that addresses a variety of biological problems, ranging from key functional residue detection to the evolution of a protein family. Traditionally, a multiple alignment was generally constructed as a series of pairwise alignments; however, the recent application of various new computational techniques to the multiple alignment problem has led to a number of interesting new developments.

Keywords: progressive alignment; iterative alignment; hidden Markov model; genetic algorithm; objective function

Figure 1.

The basic progressive alignment procedure, exemplified by a set of five immunoglobulin‐like domains. The sequence names are from the SWISS‐PROT or Protein Data Bank (PDB) databases: 1HNF, human cell adhesion (CD2) protein; CD2_HORSE, horse cell adhesion protein; CD2_RAT, rat cell adhesion protein; MYPS_HUMAN, human myosin‐binding protein; 1WIT, nematode twitchin muscle protein. The first step involves aligning all possible pairs of sequences in order to determine the distances between them. A guide tree is then created and is used to determine the order of the multiple alignment. First, the human and horse CD2 sequences are aligned. These two sequences are then aligned with the rat CD2 sequence. Finally, the myosin‐binding protein sequence is aligned with the twitchin sequence, before being merged with the alignment of the three CD2 sequences. The secondary structure elements of the immunoglobulin‐like domains from the human CD2 (1HNF) and the nematode twitchin (1WIT) proteins are shown above and below the alignment (right arrow, beta sheet; coil, alpha helix).



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Further Reading

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Thompson, Julie, and Poch, Olivier(Sep 2005) Multiple Alignment. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1038/npg.els.0005258]