Computer-aided identification of dengue virus NS2B/NS3 protease inhibitors: an integrated molecular modelling approach for screening of phytochemicals

Abstract

Globally, dengue (DENV) fever has appeared as the most widespread vector-borne disease, affecting more than 100 million individuals annually. No approved anti-DENV therapy or preventive vaccine is available yet. DENV NS3 protein is associated with protease activity and is essential for viral replication process within the host cell. NS2B is linked with NS3 protein as a cofactor. Hence, NS3/NS2B is a potential druggable target for developing inhibitors against dengue virus. In the present study, a dataset of Beta vulgaris L.-based natural compounds was developed. Virtual ligand screening of 30 phytochemicals was carried out to find novel inhibitors against the NS2B/NS3 protein. Spatial affinity, drug-likeness, and binding behaviors of selected phytochemicals were analyzed. Post-simulation analysis, including Principal Component Analysis (PCA), MMGBSA, and Co-relation analysis, was also performed to provide deep insight for elucidating protein-ligand complexes. This computer-aided screening scrutinized four potent phytochemicals, including betavulgaroside II, vitexin xyloside, epicatechin, and isovitexin2-O-xyloside inhibitors exhibiting optimal binding with viral NS3/NS2B protein. Our study brings novel scaffolds against DENV NS2B/NS3 of serotype-2 to act as lead molecules for further biological optimization. In future, this study will prompt the exploration and development of adjuvant anti-DENV therapy based on natural compounds.

Communicated by Ramaswamy H. Sarma

Keywords:

• Dengue virus
• NS2B/NS3 protease
• antiviral activity
• phytochemicals
• ADMET analysis
• molecular docking
• molecular dynamic simulations

Author’s contribution

Conceptualization, study design: Sidra Rehman; funding acquisition: Imran Shahid; Data curation: Isra Umbreen Mufti, Muhammad Sufyan, Abdullah R. Alzahrani; Formal analysis: Ibrahim Mufadhi M Alanazi, Methodology: Muhammad Sufyan, Isra Umbreen Mufti; Project administration: Sidra Rehman; Resources: Imran Shahid; Software: Muhammad Sufyan, Isra Umbreen Mufti; Supervision: Sidra Rehman; Writing - original draft: Isra Umbreen Mufti, Naiyer Shahzad, Ibrahim Abdel Aziz Ibrahim; Writing-review & editing:Sidra Rehman; Proofreading, editing, and corrections: Sidra Rehman, Imran Shahid.

Disclosure statement

The authors declare that they have no conflict of interest.

Additional information

Funding

The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, for funding this research work through project number IFP22UQU4330924DSR015.