Моделирование процесса межмолекулярного взаимодействия для подбора антидотов, нейтрализующих токсическое воздействие на компоненты клеточной мембраны
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Modeling of the process of intermolecular interaction for the selection of antidotes neutralizing the toxic impact on the components of the cellular membrane

idAzhmuhamedov I.M., Zharkikh L.I. 

UDC 501, 004.942, 615.91
DOI: 10.26102/2310-6018/2020.

  • Abstract
  • List of references
  • About authors

To study the effects of toxicants on a living organism and the selection of effective antidotes, studies are usually carried out in vivo or at least in vitro, which is a very laborious and costly process. In addition, such studies are not always possible because of ethical considerations. Experiments on living creatures in the most countries are very strictly regulated by law. To eliminate or at least drastically reduce the number of in vivo experiments, it is necessary to use a special apparatus of mathematical modeling. Based on this, the mathematical modeling's technique of the intermolecular interactions process of cell membrane molecules with toxicants and antidotes to them is proposed in the paper. The main idea of the work is to study the formation's process of stable bonds of toxicants' molecules and antidotes with molecules of the cell membrane components , by identifying the active centers of this interaction. It uses specially created algorithms for constructing the structure of a conglomerate of two molecules, analysis and evaluation of the formation of a hydrogen bond between them. For this purpose, systems analysis, quantum chemical calculations, and modular programming are used to calculate the properties of individual molecules and the conglomerate as a whole. All received information is stored in specially designed databases. For a more visual presentation of the results, an original scheme for displaying the signatures of blocked active centers of the cell membrane for the antidotes in question has been proposed. The method of computer modeling outlined in the article allows a targeted search for antidotes to a given toxicant by creating a list ranked by the degree of effectiveness of antidotes.

1. Abilova Z.Z., ZHarkih L.I., Alykov N.M. Matematicheskoe modelirovanie vozdejstviya levomicetina na n-acetilgalaktozamin [Mathematical modeling of the effects of chloramphenicol on n-acetylgalactosamine]. Ecological systems and devices. 2016;1:32-37 (in Russian).

2. Abilova Z.Z., Zharkih L.I., Alykov N.M. Matematicheskoe modelirovanie processov vozdejstviya levomicetina na strukturnye komponenty kletochnoj membrany [Mathematical modeling of the effects of chloramphenicol on the structural components of the cell membrane]. Ecological systems and devices. 2016;5:15-26 (in Russian).

3. Abilova Z.Z., Ramazanova K.I., Zharkih L.I., Alykov N.M. Matematicheskoe modelirovanie vozdejstviya flutamida i levomicetina na fosfolipid [Mathematical modeling of the effects of flutamide and chloramphenicol on phospholipid]. Ecological systems and devices. 2015;5:21-27 (in Russian).

4. Alikberova L.YU., Savinkina E.V., Davydova M.N. Osnovy stroeniya veshchestva. Metodicheskoe posobie [Fundamentals of the structure of matter. Toolkit]. M.: MITHT. 2004. [Electronic resource]. (In Russ.) Available at: http://alhimik.ru/stroenie (accessed .2019).

5. Bejder R. Atomy v molekulah. Kvantovaya teoriya [Atoms in the molecules. Quantum theory]. M.: Mir. 2001:532 (in Russian).

6. Zharkih L.I., Azhmuhamedov I.M. Algoritm opredeleniya aktivnyh centrov mezhmolekulyarnogo vzaimodejstviya [Algorithm for determining active centers of intermolecular interaction]. Caspian Journal: Management and High Technologies. 2018;1(41):144-151 (in Russian).

7. Zatolokina M.A., Pol'skoj V.S., Zueva S.V. i dr. Matematicheskoe modelirovanie i prognozirovanie – kak metody nauchnogo poznaniya v medicine i biologii [Mathematical modeling and forecasting - as methods of scientific knowledge in medicine and biology]. International Journal of Experimental Education. 2015;124:539-543 (in Russian).

8. Zacepina G.N. Svojstva i struktura vody [Properties and structure of water]. M.: MGU, 1974:168 (in Russian).

9. Zefirov N.S., Kuchanov S.I. (red.) Primenenie teorii grafov v himii [Application of graph theory in chemistry]. Novosibirsk: Nauka. 1988:306 (in Russian).

10. Kolpak E.P., Gorbunova E.A., Balykina YU.E., Gasratova N.A. Matematicheskaya model' odinochnoj populyacii na bilokal'nom areale [A mathematical model of a single population on a bilocal area]. Young scientist. 2014;1:28-33 (in Russian).

11. Kuk D. Kvantovaya teoriya molekulyarnyh sistem. Edinyj podhod [Quantum theory of molecular systems. Single approach]. Transl. From English. M.: Intellect, 2012:256.

12. Lar'kina M.S., Saprykina E.V., Kadyrova T.V., Ermilova T.V., Peshkina R.V. Antioksidantnaya aktivnost' ekstrakta vasil'ka sherohovatogo pri toksicheskom porazhenii pecheni krys [Antioxidant activity of the cornflower rough extract in rat liver toxicity]. Questions of biological, medical and pharmaceutical chemistry. 2011;8:25-28 (in Russian).

13. Minkin V.I., Simkin B.YA., Minyaev R.M. Teoriya stroeniya molekul [Theory of the structure of molecules]. M.: Vysshaya shkola. 1979:408 (in Russian).

14. Ovchinnikov YU.A. Bioorganicheskaya himiya [Bioorganic chemistry]. M.: Education. 1987:816 (in Russian).

15. Pohoden'ko-CHudakova I.O., Vil'kickaya K.V. Makroskopicheskie izmeneniya posle hirurgicheskogo lecheniya n. alveolaris inferior, pervichno podvergnutogo toksicheskomu vozdejstviyu [Macroscopic changes after surgical treatment n. alveolaris inferior, primarily exposed to toxic effects]. Vyatka Medical Bulletin. 2013;4:17-19 (in Russian).

16. . Ryzhko I.V., Mishan'kin B.N., Curaeva R.I., Shcherbanyuk A.I., Anisimov B.I. Infekcionno-toksicheskaya model' chumy myshej [Infectious-toxic model of mouse plague]. Journal of Microbiology, Epidemiology and Immunobiology. 2009;3:46-50 (in Russian).

17. Strajer L. Biohimiya [Biochemistry]. Transl. From English. M.: Mir. 1984;1:232 (in Russian).

18. Trizno N.N., Galimzyanov H.M., Nikulina D.M., Spiridonova V.A., Golubkina E.V., Dyukareva O.S., Trizno M.N. Izmeneniya gemostaziologicheskogo profilya krys pri hronicheskom vozdejstvii serovodorodsoderzhashchego gaza i vozmozhnosti ih korrekcii [Changes in the hemostasiology profile of rats during chronic exposure to hydrogen sulfidecontaining gas and the possibility of their correction]. Astrakhan Medical Journal. 2017;12(2):75-81 (in Russian).

19. Trizno N.N., Golubkina E.V., Trizno M.N., Dyukareva O.S. Sostoyanie sistemy gemostaza u krys posle hronicheskoj intoksikacii serovodorodsoderzhashchim gazom [The state of the hemostatic system in rats after chronic intoxication with hydrogen sulfide-containing gas]. Modern problems of science and education. 2017;4:75 (in Russian).

20. Usov K.I., Gus'kova T.A., Yushkov G.G. Rol' piridoksina gidrohlorida v razvitii tolerantnosti organizma zhivotnyh k toksicheskomu dejstviyu izoniazida [The role of pyridoxine hydrochloride in the development of animal organism tolerance to the toxic effect of isoniazid]. Tuberculosis and lung diseases. 2018;96(6):51-57 (in Russian).

21. Enciklopediya Krugosvet [Encyclopedia Krugosvet]. [Electronic resource]. (In Russ.) Available at: https://www.krugosvet.ru/enc/nauka_i_tehnika/himiya/vodorodnaya_svyaz.html (accessed 09.05.2019).

22. ChemOffice Professional [Electronic resource]. URL: https://www.perkinelmer.com/Product/chemoffice-professional-chemofficepro (accessed 09.12.2019).

23. Kleandrova V.V., Luan F., González-Díaz H., Ruso J. M., Melo A., SpeckPlanche A., Cordeiro M.N. Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions. Environment International. 2014;73:288-294.

24. Luan F., Kleandrova V. ., González-Díaz H., Ruso J.M., Melo A., Speck-Planche A., Cordeiro M.N.D.S. Computer-aided nanotoxicology: assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel QSTR perturbation approach. Nanoscale. 2014;6(18):10623-10630.

25. Singh K.P., Gupta S., Ghorbanzadeh M., Fatemi M.H., Karimpour M., Puzyn T., Li J.H. Nano-QSAR modeling for predicting biological activity of diverse nanomaterials. RSC Advances. 2014;4(26):213-215.

26. The General Atomic and Molecular Electronic Structure System. [Electronic resource]. Available at: www.msg.chem.iastate.edu/gamess/index.html (accessed 09.12.2019).

Azhmuhamedov Iskandar Maratovich
Doctor of Technical Sciences, Professor
Email: aim_agtu@mail.ru

ORCID |

Astrakhan State University

Astrakhan, Russian Federation

Zharkikh Lesya Ivanovna
Candidate of Technical Sciences
Email: lesy_g@mail.ru

Astrakhan State University

Astrakhan, Russian Federation

Keywords: active centers of intermolecular interaction, signature of the active centers of the components of the cell membrane, identification of the cell membrane of organs of living organisms, active centers of toxic effects blocked by the antidote

For citation: Azhmuhamedov I.M., Zharkikh L.I. Modeling of the process of intermolecular interaction for the selection of antidotes neutralizing the toxic impact on the components of the cellular membrane. Modeling, Optimization and Information Technology. 2020;8(1). URL: https://moit.vivt.ru/wp-content/uploads/2020/02/AzhmukhamedovZharkikh_1_20_1.pdf DOI: 10.26102/2310-6018/2020. (In Russ).

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Published 31.03.2020