Computational-aided design: minimal peptide sequence to block dengue virus transmission into cells

Abstract

Dengue virus (DV) infection is one of the main public health concerns, affecting approximately 390 million people worldwide, as reported by the World Health Organization. Yet, there is no antiviral treatment for DV infection. Therefore, the development of potent and nontoxic anti-DV, as a complement for the existing treatment strategies, is urgently needed. Herein, we investigate a series of small peptides inhibitors of DV antiviral activity targeting the entry process as the promising strategy to block DV infection. The peptides were designed based on our previously reported peptide sequence, DN58opt (TWWCFYFCRRHHPFWFFYRHN), to identify minimal effective inhibitory sequence through molecular docking and dynamics studies. The in silico designed peptides were synthesized using conventional Fmoc solid-phase peptide synthesis chemistry, purified by RP-HPLC and characterized using LCMS. Later, they were screened for their antiviral activity. One of the peptides, AC 001, was able to reduce about 40% of DV plaque formation. This observation correlates well with the molecular mechanics-Poisson–Boltzmann surface area (MM-PBSA) analysis – AC 001 showed the most favorable binding affinity through 60 ns simulations. Pairwise residue decomposition analysis has revealed four key residues that contributed to the binding of these peptides into the DV2 E protein pocket. This work identifies the minimal peptide sequence required to inhibit DV replication and explains the behavior observed on an atomic level using computational study.

Communicated by Ramaswamy H. Sarma

Keywords:

• Dengue envelope inhibitors
• antiviral peptides
• molecular dynamics
• molecular docking

Disclosure statement

The author declares no conflict of interest.

Additional information

Funding

This research work was financially supported by the University of Malaya Small Research Fund under Grant (BK016-2018) and MAKNA Research Grant (PV026-2018). The author (ACA) would like to thank the Malaysia Ministry of Education for the MyBrainSc scholarship.