Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach

Abstract

One of the viral diseases that affect millions of people around the world, particularly in developing countries, is Japanese encephalitis (JE). In this study, the conserved protein of this virus, that is, non-structural protein 5 (NS5), was used as a target protein for this study, and a compound library of 749 antiviral molecules was screened against NS5. The current study employed machine learning-based virtual screening combined with molecular docking. Here, three hits (24360, 123519051 and 213039) had lower binding energies (< −8 kcal/mol) than the control, S-Adenosyl-L-homocysteine (SAH). All the compounds showed significant H-bond interactions with functional residues, which were also observed by the control. Molecular dynamics simulation, MM/GBSA for binding free energy analysis, principal component analysis and free energy landscape were also performed to study the stability of the complex formation. All three compounds had similar root mean square deviation trends, which were comparable to the control, SAH. Post-MD, the 123519051-receptor complex had the highest number of H-bonds (4 to 5) after the control, out of which three exhibited the highest percentage occupancy (50%, 24% and 79%). Both docking and MD, 123519051 showed an H-bond with the residue Gly111, which was also found for the control-protein complex. 123519051 showed the lowest binding free energy with ΔG_bind of −89 kJ/mol. Steered molecular dynamics depicted that 123519051 had the maximum magnitude of dissociation (1436.43 kJ/mol/nm), which was more than the control, validating its stable complex formation. This study concluded that 123519051 is a binder and could inhibit the protein NS5 of JE.

Communicated by Ramaswamy H. Sarma

Keywords:

• Japanese encephalitis
• non-structural protein 5
• machine learning
• molecular docking
• molecular dynamics simulation

Acknowledgement

The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work. The authors would like to thank the Deanship of Scientific Research at Shaqra University for supporting this work.

Author’s contributions

Conceptualisation, A.Y.M.A., F.R.K. and F.A.-O.; Data curation; Formal analysis, A.Y.M.A., F.R.K., Z.R., A.H., B.S.A., N.S.A., H.M.A., F.F.A.A., F.F.A., A.A., F.A.-O.; Methodology A.Y.M.A., F.R.K., Z.R., A.H., B.S.A., N.S.A., H.M.A., F.F.A.A., F.F.A., A.A., F.A.-O.; Supervision, F.R.K. and F.A.-O.; Validation, A.Y.M.A., F.R.K., Z.R., A.H., B.S.A., N.S.A., H.M.A., F.F.A.A., F.F.A., A.A., F.A.-O.; Writing—original draft, A.Y.M.A., F.R.K. and F.A.-O.; Writing—review and editing, A.Y.M.A., F.R.K., Z.R., A.H., B.S.A., N.S.A., H.M.A., F.F.A.A., F.F.A., A.A., F.A.-O.; All authors reviewed the final version of the manuscript and consented to submission to the Journal of Biomolecular Structure and Dynamics.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.