pICalculax: Improved Prediction of Isoelectric Point for Modified Peptides

Abstract

The isoelectric point of a peptide is a physicochemical property that can be accurately predicted from the sequence of the peptide when the peptide is built from natural amino acids. Peptides can however have chemical modifications, such as phosphorylations, amidations, and unnatural amino acids, which can result in erroneous predictions if not accounted for. Here we report on an open source program, pICalculax, which in an extensible way can handle pI calculations of modified peptides. Tests on a database of modified peptides and experimentally determined pI values show an improvement in pI predictions when taking the modifications into account. The correlation coefficient improves from 0.45 to 0.91, and the root-mean-square deviation likewise improves from 3.3 to 0.9. The program is available at https://github.com/EBjerrum/pICalculax.

pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides

“…Bjerrum et al 46 validated their method on about 100 pI data points of peptides with noncanonical modifications that were retrieved from the Reaxys database. 52 We used the Reaxys IDs provided by Bjerrum et al 46 and retrieved the data from Reaxys for our validation. However, while browsing the original references, we discovered that many data points that are attributed as experimental data in the Reaxys database were not measured but calculated.…”

“…Despite the evident need for pI prediction methods for modified peptides, there is still a lack of free and robust tools. There are tools that provide isoelectric point predictions for natural peptides in the form of web services, − free or licensed standalone software. − A few more tools support some common PTMs but only in a limited number. , In addition, Bjerrum et al published a tool that can handle noncanonical amino acids . Its limitations, however, are that the method relies on licensed software for structure-to-sequence conversion and only implements a small set of 17 rules to predict p K a of noncanonical side chains.…”

“… 48 , 49 In addition, Bjerrum et al published a tool that can handle noncanonical amino acids. 46 Its limitations, however, are that the method relies on licensed software 50 for structure-to-sequence conversion and only implements a small set of 17 rules to predict p K a of noncanonical side chains. Moreover, the lack of a front-end service to facilitate its usage further hinders its uptake.…”

“…Experimental Data Sets for Validation. Bjerrum et al 46 validated their method on about 100 pI data points of peptides with noncanonical modifications that were retrieved from the Reaxys database. 52 We used the Reaxys IDs provided by Bjerrum et al 46 and retrieved the data from Reaxys for our validation.…”

Exploring protein phosphorylation by combining computational approaches and biochemical methods

“…The magnitude of this shift depends strongly on amino acid composition, secondary structure and number of concurrently-phosphorylated residues [18] , [19] . There are several p I prediction algorithms which calculate the influence of different PTMs, including phosphorylation, but such theoretical approaches are not exempt from errors and their accuracy for phosphorylated proteins depends on neighboring phosphoresidues and protein folding [20] , [21] .…”