In silico analysis of antiviral phytochemicals efficacy against Epstein–Barr virus glycoprotein H

Abstract

Epstein–Barr virus is a tumor-associated, enveloped virus with glycoprotein receptor gHgL on its surface. gH attaches to epithelial or B cells and mediates internalization. Till date, no specific anti-EBV FDA approved drug is available. Targeting gH may aid in designing virus-specific therapeutics and reducing the drug induced complications in host. We investigated the influence of antiviral phytochemicals on gH using computational approaches. Through molecular docking, we performed binding energy analysis of cellocidin, bruceantin, EGCG, formononetin and sesquiterpene lactones with gH DII/DIII interface, crucial for gH functions. Further, to cause any perturbations in the protein function, the molecules must bind stably to gH. Bruceantin and EGCG interacted with high affinities to gH. Simulation of these two molecules revealed stable binding with gH throughout 100 ns moreover, van der Waal interactions stabilized overall binding. Mutation of amino acids like V265, L269, L315, I423, I459, L474 and F475 involved in stable binding to gH was predicted deleterious to protein function. We obtained no difference in RMSD between these two ligands and minor deviations in the RMSF were noticed compared to gH. Conclusively, our study provided insights into the potential of bruceantin and EGCG to target gH. Different amino acids are involved in binding of each ligand to gH, engagement of certain amino acids may affect the virus binding with epithelial or B cells. The interaction of the ligand with gH may trap it in its native conformation or induce structural flexibility thereby inhibiting the interaction with host receptors or other glycoproteins.

Communicated by Ramaswamy H. Sarma

Keywords:

• EBV
• gH
• phytochemicals
• molecular docking
• MD simulation

Acknowledgements

We appreciate our lab colleagues for insightful discussions and advice. SJ and HCJ acknowledge the Indian Institute of Technology Indore for providing facilities and support.

Authors' contributions

SJ, ANJ, HCJ analyzed and interpreted the data, SJ, ANJ performed the docking and simulation respectively and SJ, ZH were contributors in writing the manuscript. All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

We thank the Council of Scientific and Industrial Research Grant No. 37(1693)/17/EMR-II and Department of Science and Technology as Ramanujan Fellowship Grant No. SB/S2/RJN-132/20/5 and DST-EMR: EMR/2017/001637. We are thankful to the Ministry of Human Resource for fellowship to SJ. ANJ acknowledges NECBH project through IITGhy, funded by DBT (number: BT/COE/34/SP28408/2018 with Project ID: 116) for providing computational facility and ZH acknowledges Tezpur University for fellowship. The funding body has not played any role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript should be declared.