Biomeditsinskaya khimiya最新文献_第2页

The role of probiotics in the regulation of expression of genes supporting antioxidant status and functionality of mouse testes in LPS-induced inflammatory processes. 在lps诱导的炎症过程中，益生菌在调节小鼠睾丸抗氧化状态和功能的基因表达中的作用。

Biomeditsinskaya khimiya Pub Date : 2025-02-01 DOI: 10.18097/PBMCR1490

P I Babenkova, E A Chirkin, M Yu Syromyatnikov, O V Zvereva, A A Tolkacheva, O S Korneeva, A P Gureev

{"title":"The role of probiotics in the regulation of expression of genes supporting antioxidant status and functionality of mouse testes in LPS-induced inflammatory processes.","authors":"P I Babenkova, E A Chirkin, M Yu Syromyatnikov, O V Zvereva, A A Tolkacheva, O S Korneeva, A P Gureev","doi":"10.18097/PBMCR1490","DOIUrl":"10.18097/PBMCR1490","url":null,"abstract":"Systemic lipopolysaccharide (LPS)-induced inflammation has a significant impact on various organs, including the male reproductive system. In this study, we have demonstrated that LPS-induced inflammation causes oxidative stress in mouse testes, reduces expression of genes encoding the catalytic subunit of glutamate-cysteine ligase (Gclc) and superoxide dismutase 2 (Sod2). Inflammation suppressed transcription of genes involved in differentiation and metabolic regulation of testicular cells and sperm maturation: in the LPS group, the expression of the Amh, Lepr, Eif2b4 genes was approximately 3 times lower compared to the control group. The intake of probiotic microorganisms caused a decrease in the intensity of lipid peroxidation, which was manifested in a decrease in the level of conjugated dienes (CD) compared to the LPS group, contributed to maintaining the level of expression of genes supporting the antioxidant status, as well as genes supporting the functionality of the mouse testes. The data obtained suggest that probiotics may be considered as potential tools for maintaining male reproductive function under conditions of inflammatory processes.","PeriodicalId":8889,"journal":{"name":"Biomeditsinskaya khimiya","volume":"71 1","pages":"51-58"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565898","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}

引用次数: 0

The SPR analysis of the interaction of inactivated poliovirus vaccine attenuated strains with antibodies. 脊髓灰质炎灭活疫苗减毒株与抗体相互作用的SPR分析。

Biomeditsinskaya khimiya Pub Date : 2025-02-01 DOI: 10.18097/PBMCR1507

O V Gnedenko, Yu Yu Ivin, A N Piniaeva, A N Zyrina, I V Levin, N S Borisenko, D D Zhdanov, A S Ivanov, A V Lisitsa, A A Ishmukhametov, A I Archakov

引用次数: 0

The study of biodegradation of galanin and its N-terminal fragments in a model system in vitro. 丙氨酸及其n端片段在体外模型系统中的生物降解研究。

Biomeditsinskaya khimiya Pub Date : 2025-02-01 DOI: 10.18097/PBMCR1540

D V Avdeev, O Yu Selyutina, M V Sidorova, O I Pisarenko

引用次数: 0

Biomarkers of hepatocellular carcinoma: status and prospects. 肝细胞癌的生物标志物：现状与展望。

Biomeditsinskaya khimiya Pub Date : 2025-02-01 DOI: 10.18097/PBMCR1543

E S Zorina, S N Naryzhny

{"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":"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.","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}

引用次数: 0

The role of the PPM1D gene in tumor pathogenesis. PPM1D基因在肿瘤发病中的作用。

Biomeditsinskaya khimiya Pub Date : 2025-02-01 DOI: 10.18097/PBMCR1495

A S Kucheryavenko, E A Muzyko, V N Perfilova, K D Kaplanov, M Yu Frolov

引用次数: 0

Chronobiotics: classifications of existing circadian clock modulators, future perspectives. 时间生物学：现有生物钟调节剂的分类，未来展望。

Biomeditsinskaya khimiya Pub Date : 2024-12-01 DOI: 10.18097/PBMC20247006381

I A Solovev, D A Golubev

{"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":"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.","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}

引用次数: 0

Multi-target neural network model of anxiolytic activity of chemical compounds using correlation convolution of multiple docking energy spectra. 基于多对接能谱关联卷积的化合物抗焦虑活性多目标神经网络模型。

Biomeditsinskaya khimiya Pub Date : 2024-12-01 DOI: 10.18097/PBMC20247006428

P M Vassiliev, M A Perfilev, A V Golubeva, A N Kochetkov, D V Maltsev

{"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":"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.","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}

引用次数: 0

Conformational dynamics of the enzyme-substrate complex of protein kinase A with pseudosubstrate SP20 and adenosine triphosphate. 蛋白激酶A与假底物SP20和三磷酸腺苷的酶-底物复合物的构象动力学。

Biomeditsinskaya khimiya Pub Date : 2024-12-01 DOI: 10.18097/PBMC20247006421

T I Mulashkina, M S Leonova, M G Khrenova

引用次数: 0

Large-scale prediction of biological activities with Active-IT system. 基于Active-IT系统的生物活动大规模预测。

Biomeditsinskaya khimiya Pub Date : 2024-12-01 DOI: 10.18097/PBMC20247006435

V L Almeida, O D H Dos Santos, J C D Lopes

{"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":"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.","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}

引用次数: 0

Extracting information on virus-human interactions and on antiviral compounds based on automated analysis of large text collections. 基于对大型文本集合的自动分析，提取病毒-人相互作用和抗病毒化合物的信息。

Biomeditsinskaya khimiya Pub Date : 2024-12-01 DOI: 10.18097/PBMC20247006469

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

{"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":"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.","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}

引用次数: 0