Biomeditsinskaya khimiya最新文献

{"title":"The study of biodegradation of galanin and its N-terminal fragments in a model system in vitro.","authors":"D V Avdeev, O Yu Selyutina, M V Sidorova, O I Pisarenko","doi":"10.18097/PBMCR1540","DOIUrl":"10.18097/PBMCR1540","url":null,"abstract":"<p><p>Exogenous N-terminal fragments of galanin, which are agonists of the GalR2 receptor, have therapeutic potential in experimental cardiac pathology. This implies the need to study their proteolytic stability in biological environments. The aim of this work was to evaluate the proteolytic degradation of galanin G1 (GWTLNSAGYLLGPHAIDNHRSFSDKHGLT-NH2), its natural and modified fragments G2 and G3 (WTLNSAGYLLGPHA-OH and WTLNSAGYLLGPβAH-OH, respectively) in human plasma. The peptides were obtained by solid-phase synthesis using the Fmoc methodology, purified by HPLC; their structure was confirmed by MALDI-TOF mass spectrometry and 1H-NMR spectroscopy. The kinetics of galanins G1-G3 degradation in blood plasma was studied by 1H-NMR spectroscopy based on changes in the intensity of Trp2 signals at 310 K. The results indicate a higher proteolytic stability of the G3 peptide compared to the natural G2 fragment and full-length galanin G1. They indicate the potential of using modified peptide agonists of GalR2 receptors to protect vital organs in pathophysiological conditions.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"71 1","pages":"71-76"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarkers of hepatocellular carcinoma: status and prospects.","authors":"E S Zorina, S N Naryzhny","doi":"10.18097/PBMCR1543","DOIUrl":"10.18097/PBMCR1543","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) also known as hepatocellular cancer is one of the most common and aggressive types of primary malignant liver neoplasms. This type of cancer accounts for up to 90% of all primary liver tumors and is the third leading cause of cancer death worldwide. Despite the advances in modern medicine, diagnostics and treatment of HCC remain challenging, especially in the later stages, when the patient's prognosis significantly worsens and treatment options are very limited. More than half a century has passed since Yu.S. Tatarinov discovered embryo-specific α-globulin in the blood of people with primary liver cancer in 1963, which was later called alpha-fetoprotein (AFP), but unfortunately, the number of specific and sensitive biomarkers for HCC remains very limited. In this regard, many scientific papers are devoted to the search and study of potential HCC biomarkers, which are essential for early diagnostics, prognosis, and development of new therapeutic strategies. Proteomic studies represent one of the promising approaches to investigate both molecular mechanisms of HCC occurrence and HCC biomarkers. Identification of specific protein profiles characteristic of tumor cells can contribute to the identification of new biomarkers that can be used not only for early detection of the disease, but also for monitoring its progression, assessing the response to therapy and predicting the clinical outcome. This review discusses current achievements in the search for potential biomarkers of HCC, as well as the prospects for their clinical use.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"71 1","pages":"7-18"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of the PPM1D gene in tumor pathogenesis.","authors":"A S Kucheryavenko, E A Muzyko, V N Perfilova, K D Kaplanov, M Yu Frolov","doi":"10.18097/PBMCR1495","DOIUrl":"10.18097/PBMCR1495","url":null,"abstract":"<p><p>The PPM1D gene and its protein product (serine-threonine protein phosphatase, PPM1D or Wip1) are involved in regulation of cell's DNA damage response, cell cycle control, and repair. Amplification, overexpression, or mutations of the PPM1D gene have a significant impact on cell responses to stress factors and genetic instability as well as impairments of processes of double-strand break repair, nucleotide excision repair, base excision repair, cell cycle, and apoptosis. PPM1D dephosphorylates and thus inactivates p53, proteins that respond to DNA strand integrity damage, cell cycle checkpoint proteins, and apoptotic proteins. This contributes to tumor development, growth, and maintenance of the tumor phenotype. In this review we consider data on the role of the PPM1D gene in the formation and maintenance of various oncological processes, including tumors of the mammary glands, ovaries, prostate gland, esophagus, stomach, intestines, liver and pancreas, hemoblastoses, and others.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"71 1","pages":"19-28"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chronobiotics: classifications of existing circadian clock modulators, future perspectives.","authors":"I A Solovev, D A Golubev","doi":"10.18097/PBMC20247006381","DOIUrl":"10.18097/PBMC20247006381","url":null,"abstract":"<p><p>The review summarizes recent achievements and future prospects in the use of chronobiotics for regulating circadian rhythms regulation. Special attention is paid to the mechanisms' action, their classification, and the impact of chemical interventions on the biological clock. Chronobiotics defined as a diverse group of compounds capable of restoring disrupted circadian functions, addressing challenges such as irregular work schedules, artificial light exposure or ageing. The review categorizes these compounds by their pharmacological effects, molecular targets, and chemical structures, underlining their ability to enhance or inhibit key circadian components like CLOCK, BMAL1, PER, and CRY. A particular focus is placed on the therapeutic applications of chronobiotics, including their potential for treating sleep disorders, metabolic issues, and age-related rhythm disturbances, underscoring their wide-ranging applicability in health care. Chronobiotic compounds have promising roles in maintaining physiological rhythms, supporting healthy aging, and enhancing personalised health care. Given their diverse therapeutic potential, chronobiotics are positioned as a significant avenue for further clinical application, marking them as a crucial area of ongoing research and innovation.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"381-393"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-target neural network model of anxiolytic activity of chemical compounds using correlation convolution of multiple docking energy spectra.","authors":"P M Vassiliev, M A Perfilev, A V Golubeva, A N Kochetkov, D V Maltsev","doi":"10.18097/PBMC20247006428","DOIUrl":"https://doi.org/10.18097/PBMC20247006428","url":null,"abstract":"<p><p>Anxiety disorders are one of the most common mental health pathologies in the world. They require searc h and development of novel effective pharmacologically active substances. Thus, the development of new approaches to the search for anxiolytic substances by artificial intelligence methods is an important area of modern bioinformatics and pharmacology. In this work, a multi-target model of the dependence of the anxiolytic activity of chemical compounds on their integral affinity to relevant target proteins based on the correlation convolution of multiple docking energy spectra has been constructed using the method of artificial neural networks. The training set of the structure and activity of 537 known anxiolytic substances was formed on the basis of the previously created database, and optimized 3D models of these compounds were built. 22 biotargets presumably relevant to anxiolytic activity were identified and their valid 3D models were found. For each biotarget, 27 multiple docking spaces have been formed throughout its entire volume. Multiple ensemble molecular docking of 537 known anxiolytic compounds into all spaces of relevant target proteins has been performed. The correlation convolution of the calculated energy spectra of multiple docking was carried out. Using seven training options based on artificial multilayer perceptron neural networks, the multi-target model of depending anxiolytic activity chemical compounds on 22 parameters of the correlation convolution of the multiple docking spectra energy was constructed. The predictive ability of the created model was characterized Acc = 91.2% and AUCROC = 94.4%, with statistical significance of p < 1×10⁻¹⁵. The found model is currently used in the search for new substances with high anxiolytic activity.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"428-434"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conformational dynamics of the enzyme-substrate complex of protein kinase A with pseudosubstrate SP20 and adenosine triphosphate.","authors":"T I Mulashkina, M S Leonova, M G Khrenova","doi":"10.18097/PBMC20247006421","DOIUrl":"https://doi.org/10.18097/PBMC20247006421","url":null,"abstract":"<p><p>The phosphorylation reaction, catalyzed by the enzyme protein kinase A (PKA), plays one of the key roles in the work of the glutamatergic system, primarily involved in memory functioning. The analysis of the dynamic behavior of the enzyme-substrate complex allows one to learn the mechanism of the enzymatic reaction. According to the results of classical molecular dynamics calculations followed by hierarchical clustering, the most preferred proton acceptor during the phosphorylation reaction catalyzed by PKA is the carboxyl group of the amino acid residue Asp166; however, the γ-phosphate group of ATP can also act as an acceptor.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"421-427"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-scale prediction of biological activities with Active-IT system.","authors":"V L Almeida, O D H Dos Santos, J C D Lopes","doi":"10.18097/PBMC20247006435","DOIUrl":"https://doi.org/10.18097/PBMC20247006435","url":null,"abstract":"<p><p>Traditional testing methods in pharmaceutical development can be time-consuming and costly, but in silico evaluation tools can offer a solution. Our in-house Active-IT system, a Ligand-Based Virtual Screening (LBVS) tool, was developed to predict the biological and pharmacological activities of small organic molecules. It includes four independent modules for generating molecular descriptors (3D-Pharma), machine learning modeling (ExCVBA), a database of bioactivity models, and a prediction module. Activity data collected from the PubChem BioAssay database was used for modelling SVM and Naïve Bayes machine learning methods. Models have been constructed using a recursive stratified partition method and validated through an activity randomization (Y-random) process. Over 3500 bioassays were modeled, each comprising 30 SVM and 30 Naïve Bayes models and 60 randomized models. Bioassays with low performance or discrimination between regular and randomized were discarded. Using the Active-IT system we have evaluated three bioactive compounds of Ayahuasca tea. The predictions were thoroughly validated using known targets described in several public databases. The external validation results are noteworthy, with 16 of 33 (48.5% with p-value.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"435-441"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extracting information on virus-human interactions and on antiviral compounds based on automated analysis of large text collections.","authors":"O A Tarasova, N Yu Biziukova, E A Stolbova, L A Stolbov, R R Taktashov, D A Karasev, N S Ionov, S M Ivanov, A V Dmitriev, A V Rudik, D S Druzhilovskiy, B N Sobolev, D A Filimonov, V V Poroikov","doi":"10.18097/PBMC20247006469","DOIUrl":"https://doi.org/10.18097/PBMC20247006469","url":null,"abstract":"<p><p>The development of effective antivirals is of great importance due to the threat associated with the rapid spread of viral infections. The accumulation of data in scientific publications and in databases of biologically active compounds provides an opportunity to extract specific information about interactions between chemicals and their viral and host targets. This information can be used for elucidation of knowledge about potential antiviral activity of chemical compounds, their side effects and toxicities. Our study aims to extract knowledge about virus-host interactions and potential antiviral agents based on the mining of massive amounts of scientific publications. With a set of previously developed algorithms, we have extracted comprehensive information on virus-host interactions and chemical compounds that interact with both viral and host targets. We collected data on the interactions of several viruses, including hepatitis B and C viruses, SARS-CoV-2, influenza A and B, and herpes simplex viruses, with (1) the host (human body), (2) potential antiviral agents, and, also extracted information on the interactions between potential antiviral agents and host proteins. Based on the data analysis performed, we created a freely available knowledge base on the interaction of chemical compounds with viral proteins and their host targets, allowing the exploration of both well-studied and recently discovered novel virus-host-chemical-compound interactions.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"469-474"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalization of a computational systems biology model of blood platelet calcium signaling.","authors":"F A Balabin, J D D Korobkina, S V Galkina, M A Panteleev, A N Sveshnikova","doi":"10.18097/PBMC20247006394","DOIUrl":"https://doi.org/10.18097/PBMC20247006394","url":null,"abstract":"<p><p>Anuclear blood cells, platelets, are the basis for the formation of blood clots in human vessels. While antiplatelet therapy is most often used after ischemic events, there is a need for its personalization due to the limited effectiveness and risks of bleeding. Previously, we developed a series of computational models to describe intracellular platelet signaling and a set of experimental methods to characterize the platelets of a given patient. To build a personalized model of platelet signaling, we also conducted research on platelet proteomics. The aim of this study was to personalize the central module of intracellular platelet signaling responsible for the formation of calcium oscillations in response to activation. The model consists of 26 ordinary differential equations. To personalize the model, proteomics data were used and unknown model parameters were selected based on experimental data on the shape and frequency of calcium oscillations in single platelets. As a result of the study, it has been shown that the key personalized parameters of the platelet oscillatory response are the degree of asymmetry of a single calcium spike and the maximum frequency of oscillations. Based on the listed experimentally determined parameters and proteomics data, an algorithm for personalization of the model has been proposed. Here we considered three healthy pediatric donors of different ages. Based on the models, personal curves of platelet calcium response to activation were obtained. The analysis of the models has shown that while there is a large heterogeneity of individual indicators of intracellular signaling, such as the activity of calcium pumps (SERCA) and inositoltriphosphate (IP₃) receptors (IP₃R), these indicators compensate each other in each donors. This observation is confirmed by the analysis of proteomics data from 15 healthy patients: this analysis demonstrates a correlation between the total amount of SERCA and IP₃R. Thus, several new features of human platelet calcium signaling are shown and an algorithm for personalizing its model is proposed.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"394-402"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling, synthesis and in vitro testing of peptides based on unusual amino acids as potential antibacterial agents.","authors":"A S Sargsyan, L T Karapetyan, A V Mkhitaryan, L A Stepanyan, T H Sargsyan, Yu M Danghyan, A V Sargsyan, G G Oganezova, N A Hovhannisyan","doi":"10.18097/PBMC20247006413","DOIUrl":"https://doi.org/10.18097/PBMC20247006413","url":null,"abstract":"<p><p>Currently non-protein amino acids and synthetic peptides are widely used as blocks in drug design. Many proteases are of great interest for pharmacology due to their key role in various pathologies. Bacterial collagenase (EC 3.4.24.3) is quite an attractive target for drug development as the inhibitors of bacterial collagenolytic protease may stop propagation of diseases caused by infections. The interaction of peptides containing unusual amino acids with Clostridium histolyticum collagenase has been evaluated by molecular docking followed by the measurement of enzyme inhibition by selected compounds. According to the docking analysis, 4 compounds were selected and synthesized for further research. Measurement of enzyme activity revealed that all tested compounds inhibited collagenase activity with IC50 values ranging within 1.45-2.08 μM. The antibacterial activity of synthesized compounds against some resistant strains was characterized by MICs values ranging within 4.6-9.2 μg/ml.</p>","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"70 6","pages":"413-420"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}