Drug repurposing against the RNA-dependent RNA polymerase domain of dengue serotype 3 by virtual screening and molecular dynamics simulations

Abstract

Dengue is an arboviral disease caused by the dengue flavivirus. The NS5 protein of flaviviruses is a potential therapeutic target, and comprises an RNA-dependent RNA polymerase (RDRP) domain that catalyses viral replication. The aim of this study was to repurpose FDA-approved drugs against the RDRP domain of dengue virus serotype 3 (DENV3) using structure-based virtual screening and molecular dynamics (MD) simulations. The FDA-approved drugs were screened against the RDRP domain of DENV3 using a two-step docking-based screening approach with Glide SP and Glide XP. For comparison, four reported DENV3 RDRP inhibitors were docked as standards. The hitlist was screened based on the docking score of the inhibitor with the lowest docking score (PubChem ID: 118797902; reported IC₅₀ value: 0.34 µM). Five hits with docking scores and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) energy lower than those of 118797902 were selected. The stability of the hit-receptor complexes was investigated using 100 ns MD simulations in an explicit solvent. The results of MD simulations demonstrated that polydatin and betiatide remained stably bound to the receptor, and formed stable interactions with the RDRP domain of DENV3. The hit-receptor interactions were comparable to those of 118797902. The average Prime MM-GBSA energy of polydatin and betiatide was lower than that of 118797902 during simulation, indicating that their binding affinity to DENV3 RDRP was higher than that of the standard. The results of this study may aid in the development of serotype-selective drugs against dengue in the future.

Communicated by Ramaswamy H. Sarma

Keywords:

• Dengue
• neglected tropical disease
• drug repurposing
• virtual screening
• molecular docking
• molecular dynamics simulations

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Council of Scientific and Industrial Research (CSIR), New Delhi, under Grant 09/028(1088)2019-EMR-I; SERB MATRICS under Grant MTR/2019/000343.