http://www.isoelectricpointdb2.org - Proteome Isoelectric Point Database 2.0
Proteome-pI 2.0 is an updated version of an online database containing the information about predicted isoelectric points.
The isoelectric point, the pH at which a particular molecule carries no net electrical charge, is an important parameter for many analytical biochemistry and proteomics techniques, especially for 2D gel electrophoresis (2D-PAGE), capillary isoelectric focusing, liquid chromatography-mass spectrometry, and X-ray protein crystallography.
The following changes have been introduced:
- the number of proteomes included has been increased four-fold (from 5,029 to 20,115);
- new algorithms for isoelectric point prediction have been added (21 algorithms in total);
- the prediction of pKa dissociation constants for over 61 million proteins have been included (5.38 Billion predictions in total);
- the prediction of isoelectric point for in silico digests of proteomes with the five most commonly used proteases (trypsin, chymotrypsin, trypsin+LysC, LysN, ArgC) have been added (9.58 Billion peptides).
The database allows the retrieval of virtual 2D-PAGE plots and the development of customized fractions of proteome based on isoelectric point and molecular weight.
Moreover, Proteome-pI 2.0 facilitates statistical comparisons of the various prediction methods as well as biological investigation of protein isoelectric point space in all kingdoms of life (updated statistics available at "Statistics" section). The database includes various statistics and tools for interactive browsing, searching, and sorting. It can be searched and browsed by organism name, average isoelectric point, molecular weight, or amino acid frequencies. Proteins with extreme pI values are also available. For individual proteomes, users can retrieve proteins of interest given the method, isoelectric point, and molecular weight ranges (this particular feature can be highly useful to limit potential targets in the analysis of 2DPAGE gels or before conducting mass spectrometry).
Finally, some general statistics (total number of proteins, amino acids, average sequence length, amino acid, and di-amino acid frequencies) and datasets corresponding to major protein databases such as UniProtKB/TrEMBL and the NCBI non-redundant (nr) database have also been precalculated (see "Download" section).
