RUDN chemist, along with colleagues from the RAS Institutes, simplified the synthesis of antitumor compounds
Many modern anticancer drugs are toxic, difficult to access and/or very expensive. Moreover, tumor cells may develop resistance to the drugs used. Therefore, researchers study the biological properties of molecules in order to obtain new antitumor drugs with optimal properties. One of the common approaches to the search for such drugs is testing of analogues of substances that already showed antitumor activity. Such substances include, in particular, isoxazole derivatives that inhibit — “turn off” — the Hsp90 protein, which is necessary for the survival of tumor cells. However, compounds of this class are inaccessible due to the complexity of the synthesis procedure, which requires, in particular, the complete absence of water molecules, and the reagents are expensive and toxic.
RUDN chemist Viktor Khrustalev and his colleagues developed a method for the synthesis of isomers of these substances, that is, the compounds that are identical in atomic composition but different in the arrangement of atoms in space. Easily accessible derivatives of arylnitromethanes and chloroacetamides were used as raw materials, and the reaction itself was carried out at temperatures not exceeding 80 degrees at atmospheric pressure and did not require anhydrous conditions.
The obtained substances had anticancer activity, but unlike the prototype compounds, they did not inhibit Hsp90 protein. Their mechanism of action is based on the destabilization of the cell division process as they prevent the formation of microtubules, which are important in the process of cell division.
Taxol derivatives, one of the most commonly used antitumor agents, have the same mechanism of action. Basing on the compounds obtained by the scientists, it is possible to create a substitute for an expensive, inaccessible and highly toxic derivatives of taxol in the treatment of cancer.
The work was published in European Journal of Organic 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.
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.
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.