Tool:IPC 2.0: prediction of isoelectric point and pKa dissociation constants
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IPC 2.0 – Isoelectric Point Calculator 2.0 is a web service and a standalone program for the estimation of protein and peptide isoelectric point (pI) and dissociation constant (pKa) values using a mixture of deep learning and support vector regression models.


Input: amino acid sequence(s)

Output: pI values predicted by >15 methods alongside with pKa dissociation constant for charged residues


Isoelectric point, the pH at which a particular molecule carries no net electrical charge, is a critical parameter for many analytical biochemistry and proteomics techniques, especially for 2D gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), X-ray crystallography, and liquid chromatography–mass spectrometry (LC-MS).

According to the benchmarks, the prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster.


IPC 2.0 is available at http://www.ipc2-isoelectric-point.org


Reference: Kozlowski LP (2021) IPC 2.0: prediction of isoelectric point and pKa dissociation constants. Nucleic Acid Res. DOI: 10.1093/nar/gkab295

deep-learning isoelectric-point 2D-PAGE pKa • 695 views
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