Ph. D. student, Department of Chemistry, Lobachevsky State University of Nizhny Novgorod
Junior Researcher of Molecular Modeling and Chemoinformatics Laboratory
- Molecular dynamics study for target delivery systems for RNA and protein drugs based on Chitosan and its derivatives.
- Force Fields.
- Neural network potential for metal cluster.
- 2013 – 2017: Department of Chemistry, Lobachevsky State University of Nizhny Novgorod (Bachelor of Science)
- 2017 – 2019: Department of Chemistry, Lobachevsky State University of Nizhny Novgorod (Master of Science)
- 2019 to present: Department of Chemistry, Lobachevsky State University of Nizhny Novgorod (Ph. D. student)
- 2021 – Present: Junior Researcher, the Laboratory of Molecular Modeling and Chemoinformatics, Lobachevsky State University of Nizhny Novgorod.
- 2019 Junior Phd Researcher, Bremen University, HMI group
- 2021 Junior Phd Researcher, Bremen University, HMI group
Russian (native), English (fluent)
MicroRNA is considered today as a prospective pharmacological agent for the development of novel high-technological medicines. Insulin is wildly used in medicine as a drug for diabetes. These two drugs we took as examples of different forms of medicine. In order to keep their active form in the aggressive biological environment, they usually needs protective drug delivery carriers. Chitosan is one of the most potential materials for such carriers owing to many useful properties such as mucoadhesion, ease of modification, low cost and biocompatibility.
We investigate the problem with classical molecular dynamics simulations of chitosan polymer — miRNA and chitosan — Insulin complexes. For chitosan, the degree of protonation and acetylation show a clear influence on the formation of the complexes.
- Glazova, I., et al., Interpolymer interaction in insulin-chitosan complexes. Supramolecular Chemistry, 2019. 31(6): p. 412–423.
- Naumov, V.S., et al., Structural, electronic, and thermodynamic properties of TiO2/organic clusters: performance of DFTB method with different parameter sets. International Journal of Quantum Chemistry, 2021. 121(2): p. e26427.