Abstract

The detection and alignment of locally conserved regions (motifs) in multiple sequences can provide insight into protein structure, function, and evolution. A new Gibbs sampling algorithm is described that detects motif-encoding regions in sequences and optimally partitions them into distinct motif models; this is illustrated using a set of im-munoglobulin fold proteins. When applied to sequences sharing a single motif, the sampler can be used to clas-sify motif regions into related submodels, as is illustrated using helix-turn-helix DNA-binding proteins. Other statistically based procedures are described for searching a database for sequences matching motifs found by the sampler. When applied to a set of 32 very distantly related bacterial integral outer membrane proteins, the sam-pler revealed that they share a subtle, repetitive motif. Although BLAST (Altschul SF et al., 1990, J Mol Biol 215:403-410) fails to detect significant pairwise similarity between any of the sequences, the repeats present in these outer membrane proteins, taken as a whole, are highly significant (based on a generally applicable statisti-cal test for motifs described here). Analysis of bacterial porins with known trimeric 0-barrel structure and related proteins reveals a similar repetitive motif corresponding to alternating membrane-spanning 0-strands. These &strands occur on the membrane interface (as opposed to the trimeric interface) of the &barrel. The broad con-servation and structural location of these repeats suggests that they play important functional roles.

Citations