CALCULATION OF THE STABILITY OF CANDIDATE VACCINES FOR THE PREVENTION OF DENGUE FEVER AND THEIR COMPLEXES WITH TOLL-LIKE RECEPTORS USING MOLECULAR DYNAMICS

Cover Page

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Rational vaccine design requires not only the prediction of immunogenic epitopes, but also a careful assessment of the structural stability of candidates and their ability to effectively interact with innate immunity receptors. The stability of four candidate vaccines and their complexes with toll-like receptors was assessed using molecular dynamics modeling using the Gromacs-2023 software package. The structures of the complexes of the considered chimeric candidate proteins for the Dengue virus vaccine with extracellular domains (ectodomains) of human toll-like receptors TLR4 and TLR8 were obtained as a result of molecular docking performed by the ZDOCK server. The affinity of the complexes was evaluated using the PRODIGY server.

About the authors

A. A Chernyavsky

NRC "Kurchatov Institute"

Email: cherniavskii.aa@phystech.edu
Moscow, Russia

V. I Timofeev

NRC "Kurchatov Institute"

Moscow, Russia

A. A Tyulenev

NRC "Kurchatov Institute"

Moscow, Russia

A. S Ivanovsky

NRC "Kurchatov Institute"

Moscow, Russia

Yu. V Kordonskaya

NRC "Kurchatov Institute"

Moscow, Russia

M. A Marchenkova

NRC "Kurchatov Institute"; Southern Federal University

Moscow, Russia; Rostov-on-Don, Russia

Yu. V Pisarevsky

NRC "Kurchatov Institute"

Moscow, Russia

Yu. A Dyakova

NRC "Kurchatov Institute"

Moscow, Russia

References

  1. Pourzangiabadi M., Najafi H., Fallah A. et al. // Infect. Genet. Evol. 2025. V. 127. P. 105710. https://doi.org/10.1016/j.meegid.2024.105710
  2. Parvizpour S., Pourseif M.M., Razmara J. et al. // Drug Discovery Today. 2020. V. 25. № 6. P. 1034. https://doi.org/10.1016/j.drudis.2020.03.006
  3. Tulenev A.A., Timofeev V.I., Chernyavsky A.A. et al. // Crystallography Reports. 2025. V. 70. № 3. P. 470. https://doi.org/10.1134/S1063774524602600
  4. Rakitina T.V., Smirnova E.V., Podshivalov D.D. et al. // Crystals. 2023. V. 13. № 10. P. 1416. https://doi.org/10.3390/cryst13101416
  5. Kato K., Nakayoshi T., Fukuyoshi S. et al. // Molecules. 2017. V. 22. № 10. P. 1716. https://doi.org/10.3390/molecules22101716
  6. Abass O.A., Timofeev V.I., Sarkar B. et al. // J. Biomol. Struct. Dyn. 2021. V. 40. № 16. P. 7283. https://doi.org/10.1080/07391102.2021.1896387
  7. Moin A.T., Singh G., Ahmed N. et al. // J. Biomol. Struct. Dyn. 2022. V. 41. № 3. P. 833. https://doi.org/10.1080/07391102.2021.2014969
  8. El-Zayat S.R., Sibaii H., Mannaa F.A. // Bull. Natl. Res. Cent. 2019. V. 43. № 1. P. 187. https://doi.org/10.1186/s42269-019-0227-2
  9. Akira S., Takeda K., Kaisho T. // Nat. Immunol. 2001. V. 2. № 8. P. 675. https://doi.org/10.1038/90609
  10. Thada S., Horvath G.L., Müller M.M. et al. // Int. J. Mol. Sci. 2021. V. 22. № 4. P. 1560. https://doi.org/10.3390/ijms22041560
  11. Agu P.C., Afiukwa C.A., Orji O.U. et al. // Sci. Rep. 2023. V. 13. № 1. P. 13398. https://doi.org/10.1038/s41598-023-40160-2
  12. Vakser I.A. // Biophys. J. 2014. V. 107. № 8. P. 1785. https://doi.org/10.1016/j.bpj.2014.08.033
  13. Paggi J.M., Pandit A., Dror R.O. // Annu. Rev. Biochem. 2024. V. 93. № 1. P. 389. https://doi.org/10.1146/annurev-biochem-030222-120000
  14. Abramson J., Adler J., Dunger J. et al. // Nature. 2024. V. 630. P. 493. https://doi.org/10.1038/s41586-024-07487-w
  15. Choudhary P., Feng Z., Berrisford J. et al. // Database. 2024. V. 2024. P. baae041. https://doi.org/10.1093/database/baae041
  16. Lindorff-Larsen K., Piana S., Palmo K. et al. // Proteins. 2010. V. 78. № 8. P. 1950. https://doi.org/10.1002/prot.22711
  17. Jorgensen W.L., Chandrasekhar J., Madura J.D. et al. // J. Chem. Phys. 1983. V. 79. № 2. P. 926. https://doi.org/10.1063/1.445869
  18. Darden T., York D., Pedersen L. // J. Chem. Phys. 1993. V. 98. № 12. P. 10089. https://doi.org/10.1063/1.464397
  19. Ke Q., Gong X., Liao S. et al. // J. Mol. Liq. 2022. V. 365. P. 120116. https://doi.org/10.1016/j.molliq.2022.120116
  20. Bernetti M., Bussi G. // J. Chem. Phys. 2020. V. 153. № 11. P. 114107. https://doi.org/10.1063/5.0020514
  21. Bussi G., Donadio D., Parrinello M. // J. Chem Phys. 2007. V. 126. № 1. P. 014101. https://doi.org/10.1063/1.2408420
  22. Cuendet M.A., van Gunsteren W.F. // J. Chem. Phys. 2007. V. 127. № 18. P. 18410. https://doi.org/10.1063/1.2779878
  23. Pierce B.G., Wiehe K., Hwang H. et al. // Bioinformatics. 2014. V. 30. № 12. P. 1771. https://doi.org/10.1093/bioinformatics/btu097
  24. Xue L.C., Rodrigues J.P., Kastritis P.L. et al. // Bioinformatics. 2016. V. 32. № 23. P. 3676. https://doi.org/10.1093/bioinformatics/btw514

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2025 Russian Academy of Sciences

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).