Motif-x is a powerful algorithm which was developed at the Harvard Medical School, USA for the analysis of sequences that surround identified phosphorylation sites by mass spectrometry-based proteomics. Large sets of input sequences can be submitted to the web server centered on selected phosphorylated residues to generate motif maps in the surrounding sequences. The length of the sequence surrounding the selected phosphorylated residue can be selected in the input page, along with the background genome. Background genomes can currently be selected from five organisms and selecting the closest one increases the statistical robustness of the analysis.
Motif-x works on a similar principle to the NCBI BLAST functions which have made the analysis of post-genomic data feasible and accessible to an extended network of researchers. Web tools like Motif-x are part of a group of applications that are setting the standards in a new generation of sequence analysis software with the use of increasingly sophisticated algorithms. The Motif-x algorithm is basically designed to extract over-represented patterns from any set of sequences. The introductory web page describes the algorithm as an iterative strategy that builds successive motifs through comparison with a dynamic statistical background.
I personally used Motif-x extensively during a phospho-proteomics project where we identified several novel phosphorylation sites in Arabidopsis. Our data was organized as a series of peptides which were identified with specific amino acid residues as phosphorylated. These phosphorylated residues were centered so that only a selected number of residues from the sequence were surrounding the site on either side. We personally set this number as six residues on either side although in Motif-x this input value is variable. Our mass-spectrometry analysis revealed over 3000 phosphorylated peptides and we were able to analyze all of these on the Motif-x web server without the need to download java applets or executable software onto our workstations. This reflects the processing capability of the Motif-x algorithm. Data was presented in a very user-friendly format, statistically highlighting residues which were over-represented to form specific motif patterns. Motifs identified by this web tool were consequently published by us in peer-reviewed journals, which validated the quality of the analysis.
I highly recommend Motif-x for next generation sequence analysis. Since web access is free, users are recommended to try it out with test sequences which are available from several genomic databases.
Research Associate
Dept of Biological Sciences
Royal Holloway University of London