Skip to main content
SpringerLink
Log in

Structural Organization and Dynamic Characteristics of the Binding Site for Conformational Rearrangement Inhibitors in Hemagglutinins from H3N2 and H7N9 Influenza Viruses

  • Published:
Biochemistry (Moscow) Aims and scope Submit manuscript

Abstract

Computer models of hemagglutinins from the H3N2 and H7N9 influenza viruses were developed to study structural organization and dynamic characteristics of the binding site for the conformational rearrangement inhibitors. The metadynamics was used to map the binding site free energy and to define the volume of its most energetically favorable states. It was demonstrated by simulation of the umifenovir (Arbidol) interaction with hemagglutinin that ligand binding requires an increase in the binding site volume and deformation of its most energetically favorable state. We also identified amino acid residues directly involved in the ligand binding that determine the binding efficiency, as well as the dynamic behavior of the binding site. The revealed features of the binding site structural organization of the influenza virus hemagglutinin should be taken into account when searching for new antiviral drugs capable to modulate its functional properties.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

Similar content being viewed by others

Abbreviations

CV:

collective variable

HA:

hemagglutinin

REFERENCES

  1. Skehel, J. J., and Wiley, D. C. (2000) Receptor binding and membrane fusion in virus entry: the influenza hemagglutinin, Ann. Rev. Biochem., 69, 531-569, doi: 10.1146/annurev.biochem.69.1.531.

    Article  CAS  PubMed  Google Scholar 

  2. Hensley, S. E. (2014) Challenges of selecting seasonal influenza vaccine strains for humans with diverse pre-exposure histories, Curr. Opin. Virol., 8, 85-89, doi: 10.1016/j.coviro.2014.07.007.

    Article  CAS  PubMed  Google Scholar 

  3. Hensley, S. E., Das, S. R., Bailey, A. L., Schmidt, L. M., Hickman, H. D., Jayaraman, A., Viswanathan, K., Raman, R., Sasisekharan, R., Bennink, J. R., and Yewdell, J. W. (2009) Hemagglutinin receptor binding avidity drives influenza A virus antigenic drift, Science, 326, 734-736, doi: 10.1126/science.1178258.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Heider, A., Mochalova, L., Harder, T., Tuzikov, A., Bovin, N., Wolff, T., Matrosovich, M., and Schweiger, B. (2015) Alterations in hemagglutinin receptor-binding specificity accompany the emergence of highly pathogenic avian influenza viruses, J. Virol., 89, 5395-5405, doi: 10.1128/JVI.03304-14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Tharakaraman, K., Raman, R., Viswanathan, K., Stebbins, N. W., Jayaraman, A., Krishnan, A., Sasisekharan, V., and Sasisekharan, R. (2013) Structural determinants for naturally evolving H5N1 hemagglutinin to switch its receptor specificity, Cell, 153, 1475-1485, doi: 10.1016/j.cell.2013.05.035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lvov, D. K., Bogdanova, V. S., Kirillov, I. M., Shchelkanov, M. Yu., Burtseva, E. I., Bovin, N. V., Fedyakina, I. T., Prilipov, A. G., Alhovsky, S. V., Samokhvalova, E. I., Proshina, E. S., Kirillova, E. S., and Syroeshkin, A. V. (2019) Evolution of pandemic influenza virus A(H1N1)pdm09 in 2009-2016: dynamics of receptor specificity of the first hemagglutinin subunit (НA1), Vopr. Virusol., 64, 63-72, doi: 10.18821/0507-4088-2019-64-2-63-72.

    Article  CAS  PubMed  Google Scholar 

  7. Russell, R. J., Kerry, P. S., Stevens, D. J., Steinhauer, D. A., Martin, S. R., Gamblin, S. J., and Skehel, J. J. (2008) Structure of influenza hemagglutinin in complex with an inhibitor of membrane fusion, Proc. Natl. Acad. Sci. USA, 105, 17736-17741, doi: 10.1073/pnas.0807142105.

    Article  PubMed  Google Scholar 

  8. Kadam, R. U., and Wilson, I. A. (2018) A small-molecule fragment that emulates binding of receptor and broadly neutralizing antibodies to influenza A hemagglutinin, Proc. Natl. Acad. Sci. USA, 115, 4240-4245, doi: 10.1073/pnas.1801999115.

    Article  CAS  PubMed  Google Scholar 

  9. Kadam, R. U., and Wilson, I. A. (2017) Structural basis of influenza virus fusion inhibition by the antiviral drug Arbidol, Proc. Natl. Acad. Sci. USA, 114, 206-214, doi: 10.1073/pnas.1617020114.

    Article  CAS  PubMed  Google Scholar 

  10. Han, N., Mu, Y., Miao, H., Yang, Y., Wu, Q., Li, J., Ding, J., Xu, B., and Huang, Z. (2016) The 340-cavity in neuraminidase provides new opportunities for influenza drug development: a molecular dynamics simulation study, Biochem. Biophys. Res. Commun., 470, 130-136, doi: 10.1016/j.bbrc.2016.01.007.

    Article  CAS  PubMed  Google Scholar 

  11. Maier, J. A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K. E., and Simmerling, C. (2015) ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB, J. Chem. Theory Comput., 11, 3696-3713, doi: 10.1021/acs.jctc.5b00255.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Case, D. A., Babin, V., Berryman, J., Betz, R. M., Cai, Q., et al. (2014) Amber 14, University of California, San Francisco.

  13. Barducci, A., Bonomi, M., and Parrinello, M. (2011) Metadynamics, WIREs Comput. Mol. Sci., 1, 826-843, doi: 10.1002/wcms.31.

    Article  CAS  Google Scholar 

  14. Tribello, G. A., Bonomi, M., Branduardi, D., Camilloni, C., and Bussi, G. (2014) PLUMED 2: new feathers for an old bird, Com. Phys. Commun., 185, 604-613, doi: 10.1016/j.cpc.2013.09.018.

    Article  CAS  Google Scholar 

  15. Sanner, M. (1999) Python: a programming language for software integration and development, J. Mol. Graph. Model., 17, 57-61.

    CAS  PubMed  Google Scholar 

  16. Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., and Olson, A. J. (2009) AutoDock4 and autoDocktools4: automated docking with selective receptor flexibility, J. Comput. Chem., 16, 2785-2791, doi: 10.1002/jcc.21256.

    Article  CAS  Google Scholar 

  17. Trott, O., and Olson, A. J. (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading, J. Comput. Chem., 31, 455-461, doi: 10.1002/jcc.21334.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ester, M., Kriegel, H.-P., Sander, J., and Xu, X. (1996) A density-based algorithm for discovering clusters in large spatial databases with noise, Proc. 2nd Int.Conf. Knowl. Discov. Data Mining, AAAI Press, Portland, Oregon, pp. 226-231.

  19. Durrant, J. D., Votapka, L., Sørensen, J., and Amaro, R. E. (2014) POVME 2.0: an enhanced tool for determining pocket shape and volume characteristics, J. Chem. Theory Comput., 10, 5047-5056, doi: 10.1021/ct500381c.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Humphrey, W., Dalke, A., and Schulten, K. (1996) VMD: visual molecular dynamics, J. Mol. Graph. Model., 14, 33-38, doi: 10.1016/0263-7855(96)00018-5.

    Article  CAS  Google Scholar 

  21. Sadovnichy, V., Tikhonravov, A., Voevodin, V., and Opanasenko, V. (2013) “Lomonosov”: supercomputing at Moscow State University, in Contem. High Perform. Comp., Boca Raton, USA, pp. 283-307, doi: 10.1201/9781351104005-11.

Download references

Acknowledgements

The study was performed using the equipment of the Center of Collective Use of super high-performance computational resources of the Lomonosov Moscow State University [21].

Funding

This work was supported by the Russian Foundation for Basic Research (project No. 18-315-00390).

Author information

Authors and Affiliations

  1. Lomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, 119991, Moscow, Russia

    D. D. Podshivalov, E. M. Kirilin, S. I. Konnov & V. K. Švedas

  2. Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119991, Moscow, Russia

    E. M. Kirilin & V. K. Švedas

Authors
  1. D. D. Podshivalov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. M. Kirilin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. I. Konnov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. V. K. Švedas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to D. D. Podshivalov or V. K. Švedas.

Ethics declarations

This article does not contain studies with human participants or animals performed by any of the authors. The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Podshivalov, D., Kirilin, E., Konnov, S. et al. Structural Organization and Dynamic Characteristics of the Binding Site for Conformational Rearrangement Inhibitors in Hemagglutinins from H3N2 and H7N9 Influenza Viruses. Biochemistry Moscow 85, 499–506 (2020). https://doi.org/10.1134/S0006297920040100

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0006297920040100

Keywords

Search

Navigation