Combination of atomic force microscopy and mass spectrometry for the target protein in the serum samples of children with autism spectrum disorders

Показана возможность детекции целевых белков, ассоциированных с развитием аутистических расстройств у детей, с помощью комбинированного метода АСМ/МС. Метод основан на комбинации аффинного обогащения белков из биообразцов, их АСМ-визуализации и МС-анализе с количественной детекцией целевых белков.Possibility of detection of target proteins associated with development of autistic disorders in children with use of combined AFM/MS method is demonstrated. The proposed method is based on the combination of affine enrichment of proteins from biological samples, visualization of these proteins by AFM and MS analysis with quantitative detection of target proteins.Работа выполнена при поддержке гранта РНФ 14-25-00132. Шумов И.Д. является получателем стипендии Президента РФ молодым ученым и аспирантам, осуществляющим перспективные научные исследования и разработки по приоритетным направлениям модернизации российской экономики на 2016-2018 годы (СП-4280.2016.4)

Diversity of Plant Sterols Metabolism: The Impact on Human Health, Sport, and Accumulation of Contaminating Sterols

The way of plant sterols transformation and their benefits for humans is still a question under the massive continuing revision. In fact, there are no receptors for binding with sterols in mammalians. However, possible biotransformation to steroids that can be catalyzed by gastro-intestinal microflora, microbial cells in prebiotics or cytochromes system were repeatedly reported. Some products of sterols metabolization are capable to imitate resident human steroids and compete with them for the binding with corresponding receptors, thus affecting endocrine balance and entire physiology condition. There are also tremendous reports about the natural origination of mammalian steroid hormones in plants and corresponding receptors for their binding. Some investigations and reports warn about anabolic effect of sterols, however, there are many researchers who are reluctant to believe in and have strong opposing arguments. We encounter plant sterols everywhere: in food, in pharmacy, in cosmetics, but still know little about their diverse properties and, hence, their exact impact on our life. Most of our knowledge is limited to their cholesterol-lowering influence and protective effect against cardiovascular disease. However, the world of plant sterols is significantly wider if we consider the thousands of publications released over the past 10 years

Use of the Molecular Dynamics Method to Investigate the Stability of α-α-Corner Structural Motifs in Proteins

This study investigated the stability of structural motifs via molecular dynamics, using α-α-corners as an example. A molecular dynamics experiment was performed on a sample of α-α-corners selected by the authors from the PDB database. For the first time during a molecular dynamics experiment, we investigated the characteristics of structural motifs by describing their geometry, including the interplanar distance, area of polygon of the helices projections intersection, and torsion angles between axes of helices in helical pairs. The torsion angles for the constriction amino acids in the equilibrium portion of the molecular dynamics trajectory were analyzed. Using the molecular dynamics method, α-α-corners were found to be autonomous structures that are stable in aquatic environments

Development of Russian market for postgenome technologies

We performed the analysis of the markets and sectors of the economy, the development of which is ensured by the implementation of the priority 20v «the transition to personalized medicine, high-tech health care and health protection technologies» in the field of post-genomic technologies, including genome editing and molecular profiling, based on the analysis of big data, considering the key Russian and foreign strategic and forecast documents, forecasts of large corporations and consulting agencies, news and scientific open Russian and foreign resources. the analysis showed the active development of the market for post-genomic technologies in Russia. Market segments demonstrated high growth rates, following in line with global trends. State institutions had adopted a number of programs aimed at supporting and developing the sector of practical implementation of post-genomic technologies. the policy of the Government of the Russian Federation, aimed at importing foreign drugs and medical products, created a full cycle of domestic production of targeted drugs for personalized therapy of malignant tumors

Managing of Unassigned Mass Spectrometric Data by Neural Network for Cancer Phenotypes Classification

Mass spectrometric profiling provides information on the protein and metabolic composition of biological samples. However, the weak efficiency of computational algorithms in correlating tandem spectra to molecular components (proteins and metabolites) dramatically limits the use of “omics” profiling for the classification of nosologies. The development of machine learning methods for the intelligent analysis of raw mass spectrometric (HPLC-MS/MS) measurements without involving the stages of preprocessing and data identification seems promising. In our study, we tested the application of neural networks of two types, a 1D residual convolutional neural network (CNN) and a 3D CNN, for the classification of three cancers by analyzing metabolomic-proteomic HPLC-MS/MS data. In this work, we showed that both neural networks could classify the phenotypes of gender-mixed oncology, kidney cancer, gender-specific oncology, ovarian cancer, and the phenotype of a healthy person by analyzing ‘omics’ data in ‘mgf’ data format. The created models effectively recognized oncopathologies with a model accuracy of 0.95. Information was obtained on the remoteness of the studied phenotypes. The closest in the experiment were ovarian cancer, kidney cancer, and prostate cancer/kidney cancer. In contrast, the healthy phenotype was the most distant from cancer phenotypes and ovarian and prostate cancers. The neural network makes it possible to not only classify the studied phenotypes, but also to determine their similarity (distance matrix), thus overcoming algorithmic barriers in identifying HPLC-MS/MS spectra. Neural networks are versatile and can be applied to standard experimental data formats obtained using different analytical platforms

Dataset of 3β-Corner and 3β-Corner-like Structures

The study is devoted to the creation of a dataset of protein structural motifs of the 3β-corner type. The relevance and importance of creating a dataset of 3β-corners is determined by the fact that this structure can be an embryo or a ready-made structural block in the process of protein folding, and can also act as an independent object of research in the field of structural biology. The dataset also contains 3β-corner-like structures that are geometrically similar to 3β-corners. The dataset consists of 45,896 structures. For each motif, its characteristics are presented: the name of the protein in which the 3β-corner is recognized, the method and resolution of the protein structure, the coordinates of localization in the protein, the secondary structure of the amino acid sequence, the gyration radius, the solvent-accessible area, and the composition of the elements of the secondary structure. The dataset will allow a comprehensive study of structures on a large scale and advance the understanding of the features and patterns of their structural organization

Mass Spectrometric Identification of Proteins Enhanced by the Atomic Force Microscopy Immobilization Surface

An approach to highly-sensitive mass spectrometry detection of proteins after surface-enhanced concentrating has been elaborated. The approach is based on a combination of mass spectrometry and atomic force microscopy to detect target proteins. (1) Background: For this purpose, a technique for preliminary preparation of molecular relief surfaces formed as a result of a chemical or biospecific concentration of proteins from solution was developed and tested on several types of chip surfaces. (2) Methods: mass spectrometric identification of proteins using trailing detectors: ion trap, time of flight, orbital trap, and triple quadrupole. We used the electrospray type of ionization and matrix-assisted laser desorption/ionization. (3) Results: It is shown that when using locally functionalized atomically smooth surfaces, the sensitivity of the mass spectrometric method increases by two orders of magnitude as compared with measurements in solution. Conclusions: It has been demonstrated that the effective concentration of target proteins on specially prepared surfaces increases the concentration sensitivity of mass spectrometric detectors—time-of-flight, ion trap, triple quadrupole, and orbital ion trap in the concentration range from up to 10−15 M