An In Silico Approach to Discover Efficient Natural Inhibitors to Tie Up Epstein–Barr Virus Infection

Abstract

Epstein–Barr virus (EBV), also known as human herpesvirus 4, is a member of the herpes virus family. EBV is a widespread virus and causes infectious mononucleosis, which manifests with symptoms such as fever, fatigue, lymphadenopathy, splenomegaly, and hepatomegaly. Additionally, EBV is associated with different lymphocyte-associated non-malignant, premalignant, and malignant diseases. So far, no effective treatment or therapeutic drug is known for EBV-induced infections and diseases. This study investigated natural compounds that inhibit EBV glycoprotein L (gL) and block EBV fusion in host cells. We utilised computational approaches, including molecular docking, in silico ADMET analysis, and molecular dynamics simulation. We docked 628 natural compounds against gL and identified the four best compounds based on binding scores and pharmacokinetic properties. These four compounds, with PubChem CIDs 4835509 (CHx-HHPD-Ac), 2870247 (Cyh-GlcNAc), 21206004 (Hep-HHPD-Ac), and 51066638 (Und-GlcNAc), showed several interactions with EBV gL. However, molecular dynamics simulations indicated that the protein–ligand complexes of CID: 4835509 (CHx-HHPD-Ac) and CID: 2870247 (Cyh-GlcNAc) are more stable than those of the other two compounds. Therefore, CIDs 4835509 and 2870247 (Cyh-GlcNAc) may be potent natural inhibitors of EBV infection. These findings can open a new way for effective drug design against EBV and its associated infections and diseases.

Keywords

• Epstein–Barr virus
• in silico screening
• glycoprotein L
• molecular docking
• MD simulation