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Epicatechin analogues may hinder human parainfluenza virus infection by inhibition of hemagglutinin neuraminidase protein and prevention of cellular entry

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Abstract

Human parainfluenza viruses (HPIVs) are ( −)ssRNA viruses belonging to Paramyoviridaie family. They are one of the leading causes of mortality in infants and young children and can cause ailments like croup, bronchitis, and pneumonia. Currently, no antiviral medications or vaccines are available to effectively treat parainfluenza. This necessitates the search for a novel and effective treatment. Computer-aided drug design (CADD) methodology can be utilized to discover target-based inhibitors with high accuracy in less time. A library of 45 phytocompounds with immunomodulatory properties was prepared. Thereafter, molecular docking studies were conducted to characterize the binding behavior of ligand in the binding pocket of HPIV3 HN protein. The physicochemical properties for screened compounds were computed, and the top hits from docking studies were further analyzed and validated using molecular dynamics simulation studies using the Desmond module of Schrodinger Suite 2021–1, followed by MM/GBSA analysis. The compounds CID:72276 (1) and CID:107905 (2) emerged as lead compounds of our in silico investigation. Further in vitro studies will be required to prove the efficacy of lead compounds as inhibitors and to determine the exact mechanism of their inhibition.

Graphical abstract

Computational studies predict three natural flavonoids to inhibit the HN protein of HPIV3.

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Data availability

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

Software availability

All the tools and databases used in this study are open source and are freely accessible on the web unless otherwise specified. Discovery Studio Visualizer 2021 is proprietary software distributed for free by BIOVIA. Schrodinger Suite 2021–1 is proprietary fee-based software distributed by Schrodinger Inc. The Desmond module of Schrodinger Suite 2021–1 is distributed free of cost by D. E. Shaw Research under the Academic License.

Abbreviations

ADME/T:

Absorption, distribution, metabolism, excretion, and toxicity

GA:

Genetic algorithm

HPIV:

Human parainfluenza virus

HN:

Hemagglutinin neuraminidase

MDSim:

Molecular dynamics simulation

MM/GBSA:

Molecular mechanics/generalized born model and solvent accessibility

RdRp:

RNA-dependent RNA polymerase

rGyr:

Radius of gyration

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

SASA:

Solvent accessibility surface area

ssRNA:

Single-stranded ribonucleic acid

VSGB:

Variable dielectric generalized Born solvation method

References

  1. Pawełczyk M, Kowalski ML (2017) The role of human parainfluenza virus infections in the immunopathology of the respiratory tract. Curr Allergy Asthma Rep 17(3):16. https://doi.org/10.1007/s11882-017-0685-2

    Article  PubMed  PubMed Central  Google Scholar 

  2. Branche AR, Falsey AR (2016) Parainfluenza virus infection. Semin Respir Crit Care Med 37(4):538–554. https://doi.org/10.1055/s-0036-1584798

    Article  PubMed  PubMed Central  Google Scholar 

  3. Schomacker H, Schaap-Nutt A, Collins PL, Schmidt AC (2012) Pathogenesis of acute respiratory illness caused by human parainfluenza viruses. Curr Opin Virol 2(3):294–299. https://doi.org/10.1016/j.coviro.2012.02.001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Abedi GR, Prill MM, Langley GE, Wikswo ME, Weinberg GA, Curns AT et al (2014) Estimates of parainfluenza virus-associated hospitalizations and cost among children aged less than 5 years in the United States, 1998–2010. J Pediatric Infectious Dis Soc 5(1):7–13. https://doi.org/10.1093/jpids/piu047

    Article  Google Scholar 

  5. Moscona A (1997) Interaction of human parainfluenza virus type 3 with the host cell surface. Pediatr Infect Dis J 16(10):917–924. https://doi.org/10.1097/00006454-199710000-00003

    Article  CAS  PubMed  Google Scholar 

  6. Moscona A (2005) Entry of parainfluenza virus into cells as a target for interrupting childhood respiratory disease. J Clin Invest 115(7):1688–1698. https://doi.org/10.1172/JCI25669

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Porotto M, Palmer SG, Palermo LM, Moscona A (2012) Mechanism of fusion triggering by human parainfluenza virus type III: communication between viral glycoproteins during entry. J Biol Chem 287(1):778–793. https://doi.org/10.1074/jbc.M111.298059

    Article  CAS  PubMed  Google Scholar 

  8. Marcink TC, Yariv E, Rybkina K, Mas V, Bovier FT, des Georges A et al (2020) Hijacking the fusion complex of human parainfluenza virus as an antiviral strategy. mBio. 11(1). https://doi.org/10.1128/mBio.03203-19.

  9. Lawrence MC, Borg NA, Streltsov VA, Pilling PA, Epa VC, Varghese JN et al (2004) Structure of the haemagglutinin-neuraminidase from human parainfluenza virus type III. J Mol Biol 335(5):1343–1357. https://doi.org/10.1016/j.jmb.2003.11.032

    Article  CAS  PubMed  Google Scholar 

  10. Tian W, Chen C, Lei X, Zhao J, Liang J (2018) CASTp 3.0: computed atlas of surface topography of proteins. Nucleic Acids Research 46(W1):W363–W7. https://doi.org/10.1093/nar/gky473

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mizuta K, Tsukagoshi H, Ikeda T, Aoki Y, Abiko C, Itagaki T et al (2014) Molecular evolution of the haemagglutinin–neuraminidase gene in human parainfluenza virus type 3 isolates from children with acute respiratory illness in Yamagata prefecture. Japan 63(4):570–577. https://doi.org/10.1099/jmm.0.068189-0

    Article  CAS  Google Scholar 

  12. Wei C-H, Kao H-Y, Lu Z (2013) PubTator: a web-based text mining tool for assisting Biocuration. Nucleic Acids Res 41(W1):W518–W522

    Article  Google Scholar 

  13. Kim S, Chen J, Cheng T, Gindulyte A, He J, He S et al (2020) PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res 49(D1):D1388–D1395. https://doi.org/10.1093/nar/gkaa971

    Article  CAS  PubMed Central  Google Scholar 

  14. O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open Babel: an open chemical toolbox. Journal of Cheminformatics 3(1):33. https://doi.org/10.1186/1758-2946-3-33

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS et al (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. https://doi.org/10.1002/jcc.21256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rizvi SM, Shakil S, Haneef M (2013) A simple click by click protocol to perform docking: AutoDock 4.2 made easy for non-bioinformaticians. EXCLI journal 12:831–57

    PubMed  PubMed Central  Google Scholar 

  17. Kim S, Thiessen PA, Bolton EE, Bryant SH (2015) PUG-SOAP and PUG-REST: web services for programmatic access to chemical information in PubChem. Nucleic Acids Res 43(W1):W605–W611. https://doi.org/10.1093/nar/gkv396

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Daina A, Michielin O, Zoete V (2017) SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7(1):42717. https://doi.org/10.1038/srep42717

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ghose AK, Viswanadhan VN, Wendoloski JJ (1999) A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J Combinatorial Chem 1(1):55–68. https://doi.org/10.1021/cc9800071

    Article  CAS  Google Scholar 

  20. Lipinski CA (2004) Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol 1(4):337–341. https://doi.org/10.1016/j.ddtec.2004.11.007

    Article  CAS  PubMed  Google Scholar 

  21. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, Gregersen BA et al (2006) Scalable algorithms for molecular dynamics simulations on commodity clusters. Sc ‘06. 84–es. https://doi.org/10.1145/1188455.1188544.

  22. Schrodinger Release 2021–1 (2021) Desmond molecular dynamics system: Schrödinger, LLC, New York, NY, 2021.

  23. Jacobson MP, Friesner RA, **ang Z, Honig B (2002) On the role of the crystal environment in determining protein side-chain conformations. J Mol Biol 320(3):597–608. https://doi.org/10.1016/S0022-2836(02)00470-9

    Article  CAS  PubMed  Google Scholar 

  24. Jacobson MP, Pincus DL, Rapp CS, Day TJ, Honig B, Shaw DE et al (2004) A hierarchical approach to all-atom protein loop prediction. Proteins 55(2):351–367. https://doi.org/10.1002/prot.10613

    Article  CAS  PubMed  Google Scholar 

  25. Schrodinger Release 2021–1 (2021) Prime: Schrödinger, LLC, New York, NY, 2021.

  26. Genheden S, Ryde U (2015) The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin Drug Discov 10(5):449–461. https://doi.org/10.1517/17460441.2015.1032936

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Li J, Abel R, Zhu K, Cao Y, Zhao S, Friesner RA (2011) The VSGB 2.0 model: a next generation energy model for high resolution protein structure modeling. Proteins 79(10):2794–812. https://doi.org/10.1002/prot.23106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Alymova IV, Taylor G, Takimoto T, Lin TH, Chand P, Babu YS et al (2004) Efficacy of novel hemagglutinin-neuraminidase inhibitors BCX 2798 and BCX 2855 against human parainfluenza viruses in vitro and in vivo. Antimicrob Agents Chemother 48(5):1495–1502. https://doi.org/10.1128/aac.48.5.1495-1502.2004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Alymova IV, Watanabe M, Boyd KL, Chand P, Babu YS, Portner A (2009) Efficacy of the novel parainfluenza virus haemagglutinin-neuraminidase inhibitor BCX 2798 in mice - further evaluation. Antivir Ther 14(7):891–898. https://doi.org/10.3851/imp1420

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Watanabe M, Mishin VP, Brown SA, Russell CJ, Boyd K, Babu YS et al (2009) Effect of hemagglutinin-neuraminidase inhibitors BCX 2798 and BCX 2855 on growth and pathogenicity of Sendai/human parainfluenza type 3 chimera virus in mice. Antimicrob Agents Chemother 53(9):3942–3951. https://doi.org/10.1128/aac.00220-09

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Palm K, Stenberg P, Luthman K, Artursson P (1997) Polar molecular surface properties predict the intestinal absorption of drugs in humans. Pharm Res 14(5):568–571. https://doi.org/10.1023/a:1012188625088

    Article  CAS  PubMed  Google Scholar 

  32. Ertl P, Rohde B, Selzer P (2000) Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. J Med Chem 43(20):3714–3717. https://doi.org/10.1021/jm000942e

    Article  CAS  PubMed  Google Scholar 

  33. Prakash M, Basavaraj BV, Chidambara Murthy KN (2019) Biological functions of epicatechin: plant cell to human cell health. J Funct Food 52:14–24. https://doi.org/10.1016/j.jff.2018.10.021

    Article  CAS  Google Scholar 

  34. Nawrot-Hadzik I, Matkowski A, Kubasiewicz-Ross P, Hadzik J (2021) Proanthocyanidins and flavan-3-ols in the prevention and treatment of periodontitis-immunomodulatory effects, animal and clinical studies. Nutrients 13(1):239. https://doi.org/10.3390/nu13010239

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ahmad A, Kaleem M, Ahmed Z, Shafiq H (2015) Therapeutic potential of flavonoids and their mechanism of action against microbial and viral infections—a review. Food Res Int 77:221–235. https://doi.org/10.1016/j.foodres.2015.06.021

    Article  CAS  Google Scholar 

  36. Pretorius JC, Magama S, Zietsman PC (2003) Purification and identification of antibacterial compounds from Euclea crispa subsp crispa (Ebenaceae) leaves. South African J Botany 69(4):579–86. https://doi.org/10.1016/S0254-6299(15)30298-2

    Article  CAS  Google Scholar 

  37. Zakaryan H, Arabyan E, Oo A, Zandi K (2017) Flavonoids: promising natural compounds against viral infections. Adv Virol 162(9):2539–2551. https://doi.org/10.1007/s00705-017-3417-y

    Article  CAS  Google Scholar 

  38. Aquino R, De Simone F, De Tommasi N, Pizza C (1995) Structure and biological activity of triterpenoids and aromatic compounds from medicinal plants. In: Atta ur R, editor. Studies in Natural Products Chemistry, Elsevier, p 113–52

  39. Wang L, Song J, Liu A, **ao B, Li S, Wen Z et al (2020) Research progress of the antiviral bioactivities of natural flavonoids. Nat Prod Bioprospecting 10(5):271–283. https://doi.org/10.1007/s13659-020-00257-x

    Article  Google Scholar 

  40. Lyu SY, Rhim JY, Park WB (2005) Antiherpetic activities of flavonoids against herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) in vitro. Arch Pharmacal Res 28(11):1293–1301. https://doi.org/10.1007/BF02978215

    Article  CAS  Google Scholar 

  41. Borges G, Ottaviani JI, van der Hooft JJJ, Schroeter H, Crozier A (2018) Absorption, metabolism, distribution and excretion of (−)-epicatechin: a review of recent findings. Mol Aspects Med 61:18–30. https://doi.org/10.1016/j.mam.2017.11.002

    Article  CAS  PubMed  Google Scholar 

  42. Müller P, Downard KM (2015) Catechin inhibition of influenza neuraminidase and its molecular basis with mass spectrometry. J Pharm Biomed Anal 111:222–230. https://doi.org/10.1016/j.jpba.2015.03.014

    Article  CAS  PubMed  Google Scholar 

  43. Liu A-L, Wang H-D, Lee SM, Wang Y-T, Du G-H (2008) Structure–activity relationship of flavonoids as influenza virus neuraminidase inhibitors and their in vitro antiviral activities. Bioorg Med Chem 16(15):7141–7147. https://doi.org/10.1016/j.bmc.2008.06.049

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

SB is thankful to Mr. Kishore Venkatesh and Ms. Shelvia Malik of Schrodinger Inc. for providing the temporary license of Schrodinger Suite 2021-1 for PCA and MM/GBSA Analysis. SB expresses his gratitude to Mr. Rajkumar Chakraborty, Ph.D. Scholar, Delhi Technological University, for his valuable input in the process of drafting the manuscript.

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Sidharth Bhasin: conceptualization, methodology, validation, writing — original draft preparation. Megh Nadar: data curation, investigation. Yasha Hasija: supervision, writing — review and editing.

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Correspondence to Yasha Hasija.

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Bhasin, S., Nadar, M. & Hasija, Y. Epicatechin analogues may hinder human parainfluenza virus infection by inhibition of hemagglutinin neuraminidase protein and prevention of cellular entry. J Mol Model 28, 319 (2022). https://doi.org/10.1007/s00894-022-05310-9

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