Skvortsov V S, Alekseychuk N N, Khudyakov D V, Romero Reyes I V
Biomed Khim. 2015 Jan-Feb;61(1):83-91. doi: 10.18097/pbmc20156101083.
The data on approximate values of isoelectric point (pI) of peptides obtained during their fractionation by isoelectric focusing can be successfully used for the calculation of the pKa's scale for amino acid residues. This scale can be used for pI prediction. The data of peptide fractionation also provides information about various posttranslational modifications (PTM), so that the prediction of pI may be performed for a wide range of protein forms. In this study, pKa values were calculated using a set of 13448 peptides (including 300 peptides with PTMs significant for pI calculation). The pKa constants were calculated for N-terminal, internal and C-terminal amino acid residues separately. The comparative analysis has shown that our scale increases the accuracy of pI prediction for peptides and proteins and successfully competes with traditional scales and such methods as support vector machines and artificial neural networks. The prediction performed by this scale, can be made in our program pIPredict with GUI written in JAVA as executable jar-archive. The program is freely available for academic users at http://www.ibmc.msk.ru/LPCIT/pIPredict. The software has also the possibility of pI predicting by some other scales; it recognizes some PTM and has the ability to use a custom scale.
通过等电聚焦对肽进行分级分离时获得的肽等电点(pI)近似值数据,可成功用于计算氨基酸残基的pKa值标度。该标度可用于pI预测。肽分级分离的数据还提供了有关各种翻译后修饰(PTM)的信息,因此可以对多种蛋白质形式进行pI预测。在本研究中,使用一组13448个肽(包括300个对pI计算有显著影响的PTM肽)计算pKa值。分别计算了N端、内部和C端氨基酸残基的pKa常数。比较分析表明,我们的标度提高了肽和蛋白质pI预测的准确性,并成功地与传统标度以及支持向量机和人工神经网络等方法相竞争。通过该标度进行的预测可以在我们用JAVA编写的带有GUI的pIPredict程序中作为可执行jar存档进行。该程序可供学术用户在http://www.ibmc.msk.ru/LPCIT/pIPredict免费使用。该软件还可以用其他一些标度进行pI预测;它能识别一些PTM,并具有使用自定义标度的能力。