[The sequence coverage in different methods of mass spectrometry data analysis obtained on model proteins]. / Stepen' pokrytiia aminokislotnoi posledovatel'nosti pri ispol'zovanii razlichnykh metodov analiza mass-spektrometricheskikh dannykh, poluchennykh na model'nykh belkakh.

The aim of this study was to evaluate sequence coverage of five model proteins (CYB5A, SMAD4, RAB27B, FECH, and CXXC1) by means of shotgun proteomic data analysis employing different methods of data treatment including database-dependent search engines (MASCOT and X!Tandem) and de novo sequencing software ((PEAKS, Novor, and PepNovo+). In order to achieve maximal results, multiprotease hydrolysis including enzymes trypsin, LYS-C, ASPN and GluC was performed in solution and using the FASP method. High resolution mass spectrometry was carried out with a Q EXACTIVE HF hybrid mass spectrometer in the positive ionization mode; parent ions with the highest intensity and a charge range from +2 to +6 were fragmented in the HCD mode. 27 experiments were carried out (hydrolysis with each of 5 enzymes in solution, 4 for the FASP protocol, three technical repeats). Using parameters limiting false identification of peptides, the search engines and de novo sequencing software gave similar results. The degree of sequence coverage was not at least 40%, and in the best cases it reached 80-90%. The use of de novo sequencing software resulted in identification of the Y12H amino acid substitution in one model protein (CYB5A).

[Correction of the electrophoretic shift in virtual 2D SDS-PAGE electrophoresis]. / Korrektsiia élektroforeticheskogo sdviga v virtual'nom 2D SDS-PAGE élektroforeze.

Virtual electrophoresis in proteomics can be used to search localization of proteins and their proteoforms (especially those existing in low concentrations), to identify proteoforms found in experiments etc. Although the problem of predicting the isoelectric point is well studied, the need of electrophoretic shift correction is usually ignored. Researchers simply use the brutto molecular weight of the protein. In this study four data sets taken from the literature sources and the SWISS-2DPAGE database have been used to build correction equations for prediction of the electrophoretic shift (123, 72, 118 and 470 points, respectively). Two groups of models were built. The first model was based on the amino acid composition of proteins, the second one, on analysis of parameters calculated by amino acid sequences (theoretical molecular weight, hydrophobicity, charge distribution, ability to form helix structures). The coefficient of determination ranged from 0.35 to 0.75 in each single set, but cross-prediction between samples did not gave satisfactory results. At the same time, the direction of correction was predicted correctly in 74% of cases. After combining of the samples and dividing pooled data into 2 representative sets, the coefficient of determination during in the process of learning ranged from 0.44 to 0.51, and R2 of predictions were not less than 0.39. The direction of correction was predicted correctly in 80% of cases. This prediction models have been integrated into the program pIPredict v.2, freely available at http://www.ibmc.msk.ru/LPCIT/pIPredict.

[ProteoСat: a tool for planning of proteomic experiments].

ProteoCat is a computer program has been designed to help researchers in the planning of large-scale proteomic experiments. The central part of this program is the subprogram of hydrolysis simulation that supports 4 proteases (trypsin, lysine C, endoproteinases AspN and GluC). For the peptides obtained after virtual hydrolysis or loaded from data file a number of properties important in mass-spectrometric experiments can be calculated or predicted. The data can be analyzed or filtered to reduce a set of peptides. The program is using new and improved modification of our methods developed to predict pI and probability of peptide detection; pI can also be predicted for a number of popular pKa's scales, proposed by other investigators. The algorithm for prediction of peptide retention time was realized similar to the algorithm used in the program SSRCalc. ProteoCat can estimate the coverage of amino acid sequences of proteins under defined limitation on peptides detection, as well as the possibility of assembly of peptide fragments with user-defined size of "sticky" ends. The program has a graphical user interface, written on JAVA and available at http://www.ibmc.msk.ru/LPCIT/ProteoCat.

[pIPredict: a computer tool for predicting isoelectric points of peptides and proteins].

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.