Molecular dynamics and combined docking studies for the identification of Zaire ebola virus inhibitors

Abstract

Ebola virus (EBOV) is a lethal human pathogen with a risk of global spread of its zoonotic infections, and Ebolavirus Zaire specifically has the highest fatality rate amongst other species. There is a need for continuous effort towards having therapies, as a single licensed treatment to neutralize the EBOV is yet to come into reality. This present study virtually screened the MCULE database containing almost 36 million compounds against the structure of a Zaire Ebola viral protein (VP) 35 and a consensus scoring of both MCULE and CLCDDW docking programs remarked five compounds as potential hits. These compounds, with binding energies ranging from –7.9 to –8.9 kcal/mol, were assessed for predictions of their physicochemical and bioactivity properties, as well as absorption, distribution, metabolism, excretion, and toxicity (ADMET) criteria. The results of the 50 ns molecular dynamics simulations showed the presence of dynamic stability between ligand and protein complexes, and the structures remained significantly unchanged at the ligand-binding site throughout the simulation period. Both docking analysis and molecular dynamics simulation studies suggested strong binding affinity towards the receptor cavity and these selected compounds as potential inhibitors against the Zaire Ebola VP 35. With respect to inhibition constant values, bioavailability radar and other physicochemical properties, compound A (MCULE-1018045960-0-1) appeared to be the most promising hit compound. However, the ligand efficiency and ligand efficiency scale need improvement during optimization, and also validation via in vitro and in vivo studies are necessary to finally make a lead compound in treating Ebola virus diseases.

Communicated by Ramaswamy H. Sarma

Keywords:

• consensus scoring
• Ebolavirus Zaire
• molecular docking
• molecular dynamics
• zoonotic infections

Acknowledgments

M.A.I. appreciates National Research Foundation (NRF), South Africa for Innovation Post-Doctoral Fellowship. M.A.I. is thankful to the CHPC (www.chpc.ac.za) for providing computational resources.

Disclosure statement

The authors declare no conflict of interest and we all approved this article for publication.