Isoelectric Point Calculator 2.0
Prediction of isoelectric point and pKa dissociation constants using deep learning

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)

Below is the text area where you can paste the amino acid sequence of the analyzed protein (peptide) or multiple sequences in fasta format

  • Input should be ONE sequence in plain text or MULTIPLE sequences in FASTA format
  • Input should be in one letter amino acid code, input can be upper or lower case.
  • All non-amino acid characters will be removed from the sequence.
  • The total limit for the input is 50,000 characters (both the header and the sequence counts). It is ~150 proteins. For processing such a big input you will need to wait for ~20s. Note that as a result, you will get pI (from 22 methods, 22x150=3300 predictions) and pKa predictions (~15,000 predictions for charged residues). In such cases, it is recommended to use output CSV file (search at the very bottom of the prediction page). For bigger datasets split your input into 50k chunks or use the standalone version.
Input example: for Ala-Pro-Lys-His-Ala-Tyr peptide, please enter APKHAY
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Standalone version of the program
IPC 2.0 in Python
(command line, any OS)

Reference: Kozlowski LP (2021) IPC 2.0: prediction of isoelectric point and pKa dissociation constants. Nucleic Acid Res. 49 (W1): W285–W292.

License: IPC is public domain, for details see license

Funding: National Science Centre, Poland [2018/29/B/NZ2/01403]
Contact: Lukasz P. Kozlowski