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Several variants of models for predicting the IC50 values of inhibitors of influenza virus neuraminidase are presented for both individual strains and also for combinations of data for neuraminidases of several strains. They are based on the use of calculated energy contributions to the amount of change in the free energy of enzyme-inhibitor complexes. In contrast to previous works, aimed at the complex modeling, we added a procedure of comparison of the docking variants with one of the neuraminidase inhibitors, for which the structure of the complexes was determined experimentally. Selection of reference molecules for the comparison of structure similarity was made using the Tanimoto metrics and the limit of the RMSD value for a similar part of the structure was no more than 2 Å. Using this limitation and filtering datasets for a particular strain by the Q2 value obtained in the leave-one-out control procedure it was possible to construct equations for predicting the IC50 value with a Q2 value close to the minimum confidence threshold (0.57 in this work). Taking into consideration that in this version of the prediction models, a minimum set of energy contributions is used, which does not employ expensive calculations of entropy contributions, the result obtained supports the correctness of using a generalized model based on the data on the position of known ligands to predict the inhibition of neuraminidase of the influenza virus of various strains.

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Several variants of models for predicting the IC50 values of inhibitors of influenza virus neuraminidase are presented for both individual strains and for combinations of data for neuraminidases of several strains. They are based on the use of calculated energy contributions to the amount of change in the free energy of enzyme-inhibitor complexes. In contrast to previous works, aimed at the complex modeling, we added a procedure of comparison of the docking variants with one of the neuraminidase inhibitors, for which the structure of the complexes was determined experimentally. The choice of the comparison structure was made according to the similarity of structures evaluated using the Tanimoto metrics and the limit of the RMSD value for a similar part of the structure was no more than 2 Å. Using this limitation and filtering datasets for a particular strain by the Q2 value obtained in the leave-one-out control procedure it is possible to construct equations for predicting the IC50 value with a Q2 value close to the minimum confidence threshold (0.57 in this work). Taking into consideration that in this version of the prediction, a minimum set of energy contributions is used, which does not provide for expensive calculations of entropy contributions, the result obtained supports the correctness of using a generalized model based on the data on the position of known ligands to predict the inhibition of neuraminidase of the influenza virus of various strains.

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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).

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Three de novo sequencing programs (Novor, PEAKS and PepNovo+) have been used for identification of 48 individual human proteins constituting the Universal Proteomics Standard Set 2 (UPS2) ("Sigma-Aldrich", USA). Experimental data have been obtained by tandem mass spectrometry. The MS/MS was performed using pure UPS2 and UPS2 mixtures with E. coli extract and human plasma samples. Protein detection was based on identification of at least two peptides of 9 residues in length or one peptide containing at least 13 residues. Using these criteria 13 (Novor), 20 (PEAKS) and 11 (PepNovo+) proteins were detected in pure UPS2 sample. Protein identifications in mixed samples were comparable or worse. Better results (by ~20%) were obtained using prediction included high quality identified fragment (TAG) containing at least 7 residues and unidentified additional masses at N- and C-termini (PepNovo+). The latter approach confidently recognized mass-spectrometric artefacts (and probably PTM). Atypical mass changes missed in UNIMOD DB were found (PepNovo+) to be statistically significant at the C-terminus (+23.02, +26.04 and +27.03). Using peptides containing these modifications and milder detection threshold 41 of 48 UPS2 proteins were identified.

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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.

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A universal model of inhibition of neuraminidases from various influenza virus strains by a particular has been developed. It is based on known 3D data for neuraminidases from three influenza virus strains (A/Tokyo/3/67, A/tern/Australia/G70C/75, B/Lee/40) and modeling of 3D structure of neuraminidases from other strains (A/PR/8/34 è A/Aichi/2/68). Using docking and molecular dynamics, we have modeled 235 enzyme-ligand complexes for 89 compounds with known IC50 values. Selection of final variants among three results obtained for each enzyme-ligand pair and calculation of independent variables for generation of linear regression equations was performed using MM-PBSA/MM-GBSA. This resulted in the set of equations individual strains and the equations pooling all the data. Thus using this approach it is possible to predict inhibition for neuraminidase from each the considered strains by a particular inhibitor and to predict the range of its action on neuraminidases from various influenza virus strains.

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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.

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A new method for screening of essential peptides for protein detection and quantification analysis in the direct positive electrospray mass spectrometry has been proposed. Our method is based on the prediction of the normalized abundance of the mass spectrometric peaks using a linear regression model. This method has the following limitations: (i) selected peptides should be taken so that at pH 2.5 the tested peptides must be presented mainly as the 2+ and 3+ ions; (ii) only peptides having C-terminal lysine or arginine residues are considered. The amino acid composition of the peptide, the peptide concentration, the ratio of the polar surface of peptide to common surface and ratio of the polar volume to common volume are used as independent variables in equation. Several combinations of variables were considered and the best linear regression model had a determination coefficient in leave-one-out validation procedure equal 0.54. This model confidently discriminates peptides with high response ability and peptides with low response ability, and therefore it allows to select only the most promising peptides. This screening method, a plain and fast, can be successfully applied to reduce the list of observed peptides.

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Peculiarities in the lattice dynamics of the Kondo insulator Y bB(12) have been studied by inelastic neutron scattering. Selected phonon modes were traced above and below the temperature region (T ~ 50 K) where the gap opens in the electron density of states. The intensities of some low-energy modes exhibit an anomalous temperature dependence for q vectors close to the Brillouin zone boundary, suggesting a renormalization of the phonon eigenvectors. This effect is thought to arise from a coupling with magnetic excitations of the same symmetry, which exist at nearby energies. It is argued that this magnetovibrational coupling may in turn play a role in the steep temperature crossover existing in Y bB(12) between the low-temperature (Kondo insulator) and high-temperature (incoherent spin-fluctuation) regimes, which is rapidly suppressed by lighter Zr substitution.

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Many approaches to discovering the interaction energy of molecular transition dipoles use the well-known coefficient xi(phi, psi (1) psi (2)) = (cos phi - 3 cos psi (1) cos psi (2))(2), where phi, Psi (1), and Psi (2) are inter-dipole angles. Unfortunately, this formula often yields rather approximate results, in particular, when it is applied to closely positioned molecules. This problem is of great importance when dealing with energy migration in photosynthetic organisms, because the major part of excitation transfers in their chlorophyllous antenna proceed between closely positioned molecules. In this paper, the authors introduce corrected values of the orientation factor for several types of mutual orientation of molecules exchanging with electronic excitations for realistic ratios of dipole lengths and spacing. The corrected magnitudes of interaction energies of neighboring bacteriochlorophyll molecules in LH2 and LH1 light-absorbing complexes are calculated for the class of photosynthetic purple bacteria. Some advantageous factors are revealed in their mutual positions and orientations in vivo.

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The interaction of betulin diacetate with formaldehyde by the Prins reaction in various media was studied. As a result, 3beta,28-di-O-acetyl-30-hydroxymethyl-(20)29-lupene, 3beta-acetyl-28-hydroxy-(20)29-lupene, and 3beta,28-di-O-acetoxy-19-(5',6'-dihydro-2'H-pyran-4'-yl)-20,29,30-trinorlupane were obtained.

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Inelastic neutron scattering experiments have been performed on the archetype compound YbB(12), using neutron polarization analysis to separate the magnetic signal from the phonon background. With decreasing temperature, components characteristic for a single-site spin-fluctuation dynamics are suppressed, giving place to specific, strongly Q-dependent, low-energy excitations near the spin-gap edge. This crossover is discussed in terms of a simple crystal-field description of the incoherent high-temperature state and a predominantly local mechanism for the formation of the low-temperature singlet ground state.