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Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface

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Abstract

SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite the widespread availability of vaccines, the virus continues to exist in the population in an endemic state which allows for the continued emergence of new variants. Most of the current vaccines target the spike glycoprotein interface of SARS-CoV-2, creating a selection pressure favoring viral immune evasion. Antivirals targeting other molecular interactions of SARS-CoV-2 can help slow viral evolution by providing orthogonal selection pressures on the virus. GRP78 is a host auxiliary factor that mediates binding of the SARS-CoV-2 spike protein to human cellular ACE2, the primary pathway of cell infection. As GRP78 forms a ternary complex with SARS-CoV-2 spike protein and ACE2, disrupting the formation of this complex is expected to hinder viral entry into host cells. Here, we developed a model of the GRP78-Spike RBD-ACE2 complex. We then used that model together with hot spot mapping of the GRP78 structure to identify the putative binding site for spike protein on GRP78. Next, we performed structure-based virtual screening of known drug/candidate drug libraries to identify binders to GRP78 that are expected to disrupt spike protein binding to the GRP78, and thereby preventing viral entry to the host cell. A subset of these compounds has previously been shown to have some activity against SARS-CoV-2. The identified hits are starting points for the further development of novel SARS-CoV-2 therapeutics, potentially serving as proof-of-concept for GRP78 as a potential drug target for other viruses.

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Data availability

All data and material are available in the supplementary information.

References

  1. Nicola M, Alsafi Z, Sohrabi C et al (2020) The socio-economic implications of the coronavirus pandemic (COVID-19): a review. Int J Surg 78:185–193. https://doi.org/10.1016/j.ijsu.2020.04.018

    Article  PubMed  PubMed Central  Google Scholar 

  2. Harvey WT, Carabelli AM, Jackson B et al (2021) SARS-CoV-2 variants, spike mutations and immune escape. Nat Rev Microbiol 19:409–424. https://doi.org/10.1038/s41579-021-00573-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Van Egeren D, Novokhodko A, Stoddard M et al (2021) Risk of rapid evolutionary escape from biomedical interventions targeting SARS-CoV-2 spike protein. PLoS ONE 16:e0250780. https://doi.org/10.1371/journal.pone.0250780

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Gaurav A, Agrawal N, Al-Nema M, Gautam V (2022) Computational approaches in the discovery and development of therapeutic and prophylactic agents for viral diseases. Curr Top Med Chem 22:2190–2206. https://doi.org/10.2174/1568026623666221019110334

    Article  CAS  PubMed  Google Scholar 

  5. Sahoo BM, Bhattamisra SK, Das S et al (2022) Computational approach to combat COVID-19 infection: emerging tools for accelerating drug research. Curr Drug Discov Technol 19:e170122200314. https://doi.org/10.2174/1570163819666220117161308

    Article  CAS  PubMed  Google Scholar 

  6. Shanmugam A, Venkattappan A, Gromiha MM (2022) Structure based drug designing approaches in SARS-CoV-2 spike inhibitor design. Curr Top Med Chem 22:2396–2409. https://doi.org/10.2174/1568026623666221103091658

    Article  CAS  PubMed  Google Scholar 

  7. Mehmood A, Nawab S, Wang Y et al (2022) Discovering potent inhibitors against the Mpro of the SARS-CoV-2: a medicinal chemistry approach. Comput Biol Med 143:105235. https://doi.org/10.1016/j.compbiomed.2022.105235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mehmood A, Nawab S, Jia G et al (2023) Supervised screening of Tecovirimat-like compounds as potential inhibitors for the monkeypox virus E8L protein. J Biomol Struct Dyn. https://doi.org/10.1080/07391102.2023.2245042

    Article  PubMed  Google Scholar 

  9. Lan J, Ge J, Yu J et al (2020) Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature 581:215–220. https://doi.org/10.1038/s41586-020-2180-5

    Article  CAS  PubMed  Google Scholar 

  10. Shang J, Wan Y, Luo C et al (2020) Cell entry mechanisms of SARS-CoV-2. Proc Natl Acad Sci U S A 117:11727–11734. https://doi.org/10.1073/pnas.2003138117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Papageorgiou AC, Mohsin I (2020) The SARS-CoV-2 spike glycoprotein as a drug and vaccine target: structural insights into its complexes with ACE2 and antibodies. Cells 9:2343. https://doi.org/10.3390/cells9112343

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Yuen K-S, Ye Z-W, Fung S-Y et al (2020) SARS-CoV-2 and COVID-19: the most important research questions. Cell Biosci 10:40. https://doi.org/10.1186/s13578-020-00404-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Mostafa-Hedeab G et al (2020) ACE2 as drug target of COVID-19 virus treatment, simplified updated review. rbmb.net 9:97–105. https://doi.org/10.29252/rbmb.9.1.97

    Article  CAS  Google Scholar 

  14. Rangel HR, Ortega JT, Maksoud S et al (2020) SARS-CoV-2 host tropism: an in silico analysis of the main cellular factors. Virus Res 289:198154. https://doi.org/10.1016/j.virusres.2020.198154

    Article  CAS  PubMed  Google Scholar 

  15. Elfiky AA, Ibrahim IM, Ismail AM, Elshemey WM (2021) A possible role for GRP78 in cross vaccination against COVID-19. J Infect 82:282–327. https://doi.org/10.1016/j.jinf.2020.09.004

    Article  CAS  PubMed  Google Scholar 

  16. Carlos AJ, Ha DP, Yeh D-W et al (2021) The chaperone GRP78 is a host auxiliary factor for SARS-CoV-2 and GRP78 depleting antibody blocks viral entry and infection. J Biol Chem 296:100759. https://doi.org/10.1016/j.jbc.2021.100759

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Yang J, Nune M, Zong Y et al (2015) Close and allosteric opening of the polypeptide-binding site in a human Hsp70 chaperone BiP. Structure 23:2191–2203. https://doi.org/10.1016/j.str.2015.10.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ibrahim IM, Abdelmalek DH, Elshahat ME, Elfiky AA (2020) COVID-19 spike-host cell receptor GRP78 binding site prediction. J Infect 80:554–562. https://doi.org/10.1016/j.jinf.2020.02.026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Dominguez C, Boelens R, Bonvin AMJJ (2003) HADDOCK: a protein−protein docking approach based on biochemical or biophysical information. J Am Chem Soc 125:1731–1737. https://doi.org/10.1021/ja026939x

    Article  CAS  PubMed  Google Scholar 

  20. van Zundert GCP, Rodrigues JPGLM, Trellet M et al (2016) The HADDOCK2.2 web server: user-friendly integrative modeling of biomolecular complexes. J Mol Biol 428:720–725. https://doi.org/10.1016/j.jmb.2015.09.014

    Article  CAS  PubMed  Google Scholar 

  21. Yang J, Zong Y, Su J et al (2017) Conformation transitions of the polypeptide-binding pocket support an active substrate release from Hsp70s. Nat Commun 8:1201. https://doi.org/10.1038/s41467-017-01310-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Yoneda Y, Steiniger SCJ, Čapková K et al (2008) A cell-penetrating peptidic GRP78 ligand for tumor cell-specific prodrug therapy. Bioorg Med Chem Lett 18:1632–1636. https://doi.org/10.1016/j.bmcl.2008.01.060

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Kim Y, Lillo AM, Steiniger SCJ et al (2006) Targeting heat shock proteins on cancer cells: selection, characterization, and cell-penetrating properties of a peptidic GRP78 ligand. Biochemistry 45:9434–9444. https://doi.org/10.1021/bi060264j

    Article  CAS  PubMed  Google Scholar 

  24. Brenke R, Kozakov D, Chuang GY, Beglov D, Hall D, Landon MR, Mattos C, Vajda S (2009) Fragment-based identification of druggable “hot spots” of proteins using Fourier domain correlation techniques. Bioinformatics. https://doi.org/10.1093/bioinformatics/btp036

    Article  PubMed  PubMed Central  Google Scholar 

  25. Kozakov D, Grove LE, Hall DR et al (2015) The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins. Nat Protoc 10:733–755. https://doi.org/10.1038/nprot.2015.043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kozakov D, Hall DR, Napoleon RL et al (2015) New frontiers in druggability. J Med Chem 58:9063–9088. https://doi.org/10.1021/acs.jmedchem.5b00586

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Friesner RA, Banks JL, Murphy RB et al (2004) Glide: a new approach for rapid, accurate docking and scoring—1: method and assessment of docking accuracy. J Med Chem 47:1739–1749. https://doi.org/10.1021/jm0306430

    Article  CAS  PubMed  Google Scholar 

  28. Friesner RA, Murphy RB, Repasky MP et al (2006) Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein−ligand complexes. J Med Chem 49:6177–6196. https://doi.org/10.1021/jm051256o

    Article  CAS  PubMed  Google Scholar 

  29. Halgren TA, Murphy RB, Friesner RA et al (2004) Glide: a new approach for rapid, accurate docking and scoring—2: enrichment factors in database screening. J Med Chem 47:1750–1759. https://doi.org/10.1021/jm030644s

    Article  CAS  PubMed  Google Scholar 

  30. Sterling T, Irwin JJ (2015) ZINC 15—ligand discovery for everyone. J Chem Inf Model 55:2324–2337. https://doi.org/10.1021/acs.jcim.5b00559

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Gaulton A, Bellis LJ, Bento AP et al (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 40:D1100–D1107. https://doi.org/10.1093/nar/gkr777

    Article  CAS  PubMed  Google Scholar 

  32. Schrödinger release 2022–3: QikProp (2021) Schrödinger, LLC, New York

  33. Di L, Kerns EH (2016) Drug-like properties: concepts, structure design and methods from ADME to toxicity optimization, 2nd edn. Academic Press

    Google Scholar 

  34. Duan J, Dixon SL, Lowrie JF, Sherman W (2010) Analysis and comparison of 2D fingerprints: insights into database screening performance using eight fingerprint methods. J Mol Graph Model 29:157–170. https://doi.org/10.1016/j.jmgm.2010.05.008

    Article  CAS  PubMed  Google Scholar 

  35. Sastry M, Lowrie JF, Dixon SL, Sherman W (2010) Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments. J Chem Inf Model 50:771–784. https://doi.org/10.1021/ci100062n

    Article  CAS  PubMed  Google Scholar 

  36. Weston S, Coleman CM, Haupt R et al (2020) Broad anti-coronaviral activity of FDA approved drugs against SARS-CoV-2 in vitro and SARS-CoV in vivo. Microbiology 26:865

    Google Scholar 

  37. MARSH W (2007) Tricyclic antidepressants. In: Enna SJ, Bylund DB, Elsevier Science (FIRM) (eds) xPharm: the comprehensive pharmacology reference. Amsterdam: Elsevier, pp 1–3. https://doi.org/10.1016/B978-008055232-3.61066-9

    Google Scholar 

  38. Quinones QJ et al (2008) GRP78: a chaperone with diverse roles beyond the endoplasmic reticulum. Histol histopathol 23(11):1409–1416. https://doi.org/10.14670/HH-23.1409

    Article  CAS  PubMed  Google Scholar 

  39. Gurusinghe KRDSNS, Mishra A, Mishra S (2018) Glucose-regulated protein 78 substrate-binding domain alters its conformation upon EGCG inhibitor binding to nucleotide-binding domain: molecular dynamics studies. Sci Rep 8:5487. https://doi.org/10.1038/s41598-018-22905-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Halford B (2022) How Pfizer scientists transformed an old drug lead into a COVID-19 antiviral Behind the scenes of the medicinal chemistry campaign that led to the pill Paxlovid

  41. Focosi D, McConnell S, Shoham S et al (2023) Nirmatrelvir and COVID-19: development, pharmacokinetics, clinical efficacy, resistance, relapse, and pharmacoeconomics. Int J Antimicrob Agents 61:106708. https://doi.org/10.1016/j.ijantimicag.2022.106708

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. De Clercq E, Li G (2016) Approved antiviral drugs over the past 50 years. Clin Microbiol Rev 29:695–747. https://doi.org/10.1128/CMR.00102-15

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Kenji C. Walker for thoughtful discussions related to the properties of intranasally delivered drugs.

Funding

The research leading to these results received funding the National Science Foundation under grant NSF-2200052 to DJ-M.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA

    Maria Lazou, Jonathan R. Hutton & Diane Joseph-McCarthy

  2. Fractal Therapeutics Inc., Cambridge, MA, 02139, USA

    Arijit Chakravarty

Authors
  1. Maria Lazou
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  4. Diane Joseph-McCarthy
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Contributions

ML, AC and DJM are responsible for the study conception and design. ML and JRH were responsible for all computations. ML, AC, and DJM contributed to the interpretation of the results and edited the manuscript. DJM oversaw the project.

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Correspondence to Diane Joseph-McCarthy.

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Lazou, M., Hutton, J.R., Chakravarty, A. et al. Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface. J Comput Aided Mol Des 38, 6 (2024). https://doi.org/10.1007/s10822-023-00546-w

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