12/17/2023 0 Comments Isoelectric point calculator peptideProteins are relatively big molecules with a plethora of charged residues. Isoelectric point predictions were validated separately for peptides and proteins as they differ substantially. To compare the performance of Isoelectric Point Calculator 15, other pKa sets and two programs based on SVM (pIR) and ANN (pIPredict) were tested. Presented results shows that IPC overperform all currently, available algorithms. Here, I present IPC program which is based on the optimization using a basin-hopping procedure. The problem of computational prediction of pI was already addressed by two other research groups using artificial neural networks (ANN) and support vector machines (SVM). This is the approach, presented in this study. On the other hand, pKa values or pI can be derived computationally giving the large sets of proteins or peptides for which pI information is known. It should be kept in mind that the values of dissociation constants used in the calculations are usually derived empirically and can vary substantially depending on the experimental setup such as temperature or buffer ionic strength (herein presented method, Isoelectric Point Calculator, is compared to 15 such pKa sets). Overall, the net charge of the protein or peptide is strongly related to the solution (buffer) pH and can be approximated using the Henderson-Hasselbalch equation. Additionally, the charge of the amine and carboxyl terminal groups contribute to pI and can greatly affect pI of short peptides. Although molecular techniques for protein analysis have changed, the interpretation of the results from those techniques in many cases rely on accurate estimations of pI for reference polypeptides.įor polypeptides, pI depends mostly on the acid dissociation constants ( pKa) of the ionizable groups of seven charged amino acids: glutamate (δ-carboxyl group), aspartate (ß-carboxyl group), cysteine (thiol group), tyrosine (phenol group), histidine (imidazole side chains), lysine (ε-ammonium group) and arginine (guanidinium group). Nevertheless, before the mass spectrometry is applied, the sample is digested by trypsin into short peptides and then fractionated by isoelectric focusing into so called fractions which allows to reduce MS analysis complexity. Therefore, 2D-PAGE has been today replaced in many cases by gel-free techniques such as high-throughput mass spectrometry (MS). Unfortunately, 2D-PAGE suffers from several intrinsic technical problems (e.g., performs poorly for very large, very small, extremely acidic or basic proteins). One of the oldest, but still widely used technique is 2-D polyacrylamide gel electrophoresis (2D-PAGE), where proteins are separated in two dimensions on a gel and identified using estimated molecular weight and isoelectric point ( pI is the pH value at which the net charge of a macromolecule is zero, and therefore its electrophoretic mobility is stopped). Over the years, many techniques were introduced to allow to accomplish the task. The procedure relies on physicochemical properties of amino acids such as a molecular mass or a charge. Next, individual proteins are separated and finally identified. This article was reviewed by Frank Eisenhaber and Zoltán GáspáriĪnalysis of proteins starts from the heterogeneous mixture (lysate) from which protein fraction needs to be isolated. The IPC service is freely available at Peptide and protein datasets used in the study and the precalculated pI for the PDB and some of the most frequently used proteomes are available for large-scale analysis and future development. Moreover, the prediction of pI using the IPC pKa’s leads to fewer outliers, i.e., predictions affected by errors greater than a given threshold. According to the presented benchmarks, the newly developed IPC pKa sets outperform previous algorithms by at least 14.9 % for proteins and 0.9 % for peptides (on average, 22.1 % and 59.6 %, respectively), which corresponds to an average error of the pI estimation equal to 0.87 and 0.25 pH units for proteins and peptides, respectively. Here, I present the Isoelectric Point Calculator (IPC), a web service and a standalone program for the accurate estimation of protein and peptide pI using different sets of dissociation constant ( pKa) values, including two new computationally optimized pKa sets. Additionally, pI estimation can be helpful during protein crystallization trials. Accurate estimation of the isoelectric point ( pI) based on the amino acid sequence is useful for many analytical biochemistry and proteomics techniques such as 2-D polyacrylamide gel electrophoresis, or capillary isoelectric focusing used in combination with high-throughput mass spectrometry.
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