PHOSIDA Database Enhances Research Involving Posttranslational…

PHOSIDA¹ first began as a small public database of phosphorylation sites identified by the Mann group.² The name “PHOSIDA” first originated from the phrase “the phosphorylation site database.” Since its creation, the database has expanded to contain other types of posttranslational modifications. In addition to more than 70,000 phosphorylation sites, the data repository now includes more than 3,600 acetylated lysines and 6,367 N-glycosylated asparagines. The database also boasts the largest acetylome and N-glycoproteome determined so far.³

PHOSIDA is home to 6,000 modification sites developed from HeLa cells exposed to growth factor stimulation and 20,000 additional human sites derived from kinase-enriched samples. The PHOSIDA database also contains 25,000 mouse phosphorylation sites. Additionally, fly, worm, and yeast proteins are also represented. The database is also the most comprehensive repository of prokaryotic phosphoproteomes.

Beyond the data platform of PHOSIDA, there is a prediction platform that employs highly accurate species-specific phosphorylation and acetylation site predictors, to determine modified sites on proteins based on their sequence. The database contains built-in tools that allow for retrieval of posttranslational modification matches with other popular databases, such as Swiss-Prot, ELM, and PhosphoSite.

These tools are also able to identify de novo consensus sequences. PHOSIDA is also carefully maintained. Modified peptides and proteins are regularly reassigned to up-to-date database versions. Acceptance of posttranslational modifications is based on stringent criteria, with very low false-positive rates throughout the database. PHOSIDA has continued to improve its functionality over time, thanks to feedback from the scientific community. PHOSIDA is now fully searchable via accession number, gene name, description, sequence, and gene ontology. The built-in search filters can also locate modified proteins by their location or function.

Future plans for improvement include an expanded toolkit with more options available for analysis. The current motif finder will also be extended to identify de novo motifs for any posttranslational modification.

References

1. PHOSIDA Posttranslational Modification Database, www.phosida.com

2. Olsen, J.V., et al. (2006) ‘Global, in vivo, and site-specific phosphorylation dynamics in signaling networks‘, Cell, 127 (3), (pp. 635-648)

3. Gnad, F., et al. (2011) ‘PHOSIDA 2011: the posttranslational modification database‘, Nucleic Acids Research, 39 (Database issue), (pp. D253-D260)