Motivation: To test whether protein folding constraints and secondary structure sequence preferences significantly reduce the space of amino acid words in proteins, we compared the frequencies of four- and five-amino acid word clumps (independent words) in proteins to the frequencies predicted by four random sequence models.Results: While the human proteome has many overrepresented word clumps, these words come from large protein families with biased compositions (e.g. Zn-fingers). In contrast, in a non-redundant sample of Pfam-AB, only 1 of four-amino acid word clumps (4.7 of 5mer words) are 2-fold overrepresented compared with our simplest random model [MC(0)], and 0.1 (4mers) to 0.5 (5mers) are 2-fold overrepresented compared with a window-shuffled random model. Using a false discovery rate q-value analysis, the number of exceptional four- or five-letter words in real proteins is similar to the number found when comparing words from one random model to another. Consensus overrepresented words are not enriched in conserved regions of proteins, but four-letter words are enriched 1.18- to 1.56-fold in -helical secondary structures (but not -strands). Five-residue consensus exceptional words are enriched for -helix 1.43- to 1.61-fold. Protein word preferences in regular secondary structure do not appear to significantly restrict the use of sequence words in unrelated proteins, although the consensus exceptional words have a secondary structure bias for -helix. Globally, words in protein sequences appear to be under very few constraints; for the most part, they appear to be random.Contact: email@example.comSupplementary information: Supplementary data are available at Bioinformatics online.
Bioinformatics – Oxford University Press
Published: Feb 1, 2010