Bioinformatic identification of plant peptides.
Plant peptides play a number of important roles in defence, development and many other aspects of plant physiology. Identifying additional peptide sequences provides the starting point to investigate their function using molecular, genetic or biochemical techniques. Due to their small size, identifying peptide sequences may not succeed using the default bioinformatic approaches that work well for average-sized proteins. There are two general scenarios related to bioinformatic identification of peptides to be discussed in this paper. In the first scenario, one already has the sequence of a plant peptide and is trying to find more plant peptides with some sequence similarity to the starting peptide. To do this, the Basic Local Alignment Search Tool (BLAST) is employed, with the parameters adjusted to be more favourable for identifying potential peptide matches. A second scenario involves trying to identify plant peptides without using sequence similarity searches to known plant peptides. In this approach, features such as protein size and the presence of a cleavable amino-terminal signal peptide are used to screen annotated proteins. A variation of this method can be used to screen for unannotated peptides from genomic sequences. Bioinformatic resources related to Arabidopsis thaliana will be used to illustrate these approaches.
Lease
Kevin A
KA
Division of Biological Sciences and Bond Life Sciences Centre, University of Missouri, Columbia, MO, USA.
Walker
John C
JC
D000595:Amino Acid Sequence; D017360:Arabidopsis / Q000737:chemistry / Q000235:genetics; D029681:Arabidopsis Proteins / Q000737:chemistry / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry / Q000235:genetics*; D020539:Sequence Analysis, Protein; D017386:Sequence Homology, Amino Acid
D029681:Arabidopsis Proteins; D010455:Peptides