Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers.

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for "ideal" tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways-by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called "classical plasma proteins", may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of "classical plasma proteins". Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

A database for inventory of proteoform profiles: "2DE-pattern".

The human proteome is composed of a diverse and heterogeneous range of gene products/proteoforms/protein species. Because of the growing amount of information about proteoforms generated by different methods, we need a convenient approach to make an inventory of the data. Here, we present a database of proteoforms that is based on information obtained by separation of proteoforms using 2DE followed by shotgun ESI-LC-MS/MS. The database's principles and structure are described. The database is called "2DE-pattern" as it contains multiple isoform-centric patterns of proteoforms separated according to 2DE principles. The database can be freely used at http://2de-pattern.pnpi.nrcki.ru.

The amyloidogenicity of the influenza virus PB1-derived peptide sheds light on its antiviral activity.

The influenza virus polymerase complex is a promising target for new antiviral drug development. It is known that, within the influenza virus polymerase complex, the PB1 subunit region from the 1st to the 25th amino acid residues has to be is in an alpha-helical conformation for proper interaction with the PA subunit. We have previously shown that PB1(6-13) peptide at low concentrations is able to interact with the PB1 subunit N-terminal region in a peptide model which shows aggregate formation and antiviral activity in cell cultures. In this paper, it was shown that PB1(6-13) peptide is prone to form the amyloid-like fibrillar aggregates. The peptide homo-oligomerization kinetics were examined, and the affinity and characteristic interaction time of PB1(6-13) peptide monomers and the influenza virus polymerase complex PB1 subunit N-terminal region were evaluated by the SPR and TR-SAXS methods. Based on the data obtained, a hypothesis about the PB1(6-13) peptide mechanism of action was proposed: the peptide in its monomeric form is capable of altering the conformation of the PB1 subunit N-terminal region, causing a change from an alpha helix to a beta structure. This conformational change disrupts PB1 and PA subunit interaction and, by that mechanism, the peptide displays antiviral activity.