RUDN University chemist synthesized a new compound with strong anti-diabetic properties
In the small intestine, the complex structure of starch is broken down into simpler oligosaccharides by the action of the enzyme α-amylase. Then, under the action of the enzyme α-glucosidase, the resulting oligosaccharides pass into glucose and other monosaccharides. If you inhibit — that is, “turn off” — one or both of these enzymes, the rate of carbohydrate absorption will decrease, and, consequently, the concentration of glucose in the blood will decrease. This antidiabetic effect makes researchers pay more and more attention to the search and synthesis of α-amylase and α-glucosidase inhibitors.
Yuness El Bakri from the RUDN University in collaboration with colleagues 17 have synthesized new derivatives of 1,2,4-triazole. They belong to the class of heterocycles — organic compounds that contain “rings” of carbon atoms and atoms of other elements. Due to their structure, which resembles that of natural products, heterocyclic compounds have interesting biologically active properties.
RUDN chemists studied the structure of new heterocyclic compounds using x-ray diffraction analysis and spectral methods. They then evaluated in vitro the inhibitory activity of all 1,2,4-triazole derivatives and compared them with acarbose, a hypoglycemic drug that inhibits α-glucosidase. All of the new compounds proved to be potent inhibitors of α-glucosidase, and three of them also demonstrated the ability to inhibit α-amylase.
Using molecular docking, a method for modeling the properties of molecules, the researchers showed that three triazole derivatives — 6 — methyl-7H,8H,9H-[1,2,4]triazolo[4,3-b][1,2,4]triazepine-8-one and 6-methyl-7H-[1,2,4]triazolo[4,3-b][1,2,4]triazepine-8(9H)-thion-surpass acarbose in inhibitory activity relative to α — glucosidase.
Based on the results of experiments, RUDN biochemists selected the best conformation of 6-methyl-7H-[1,2,4]triazolo[4,3-b][1,2,4]triazepine-8(9H)-thion in complex with α-glucosidase and performed its molecular dynamic modeling.
Calculations have shown that the degree of inhibition of α-glucosidase is mainly due to the number and strength of bonds between the compound and the active residues of the enzyme. The results obtained allow us to conclude that the synthesized compound is stable.
Younes El Bakri and his colleagues also showed the antioxidant properties of the new compounds. Chemists used a spectrophotometer to measure changes in the optical density of solutions containing specifically colored free radicals (ABTS cation-radical (2,2’-azinobis3-ethylbenzothiazoline-6-sulfonate) and DPPH radical (2,2-diphenyl-1-picrylhydrazyl)), to which antioxidants were added. Using these methods, they determined the ability of the antioxidant to interact with ABTS and DPPH radicals. Also, the antioxidant activity of 1,2,4-triazole derivatives was evaluated by evaluating the ability of antioxidant iron reduction.
The chemists concluded that the 1,2,4-triazole derivatives they obtained are promising for use as antidiabetic drugs. They expect that the properties of these substances will soon become the subject of Toxicological and pharmacological studies in vivo.
Article in the journal Bioorganic Chemistry.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
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Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.