Pharmacoinformatics-based identification of chemically active molecules against Ebola virus

Abstract

Ebola is a dangerous virus transmitted by animals and humans and to date there is no curable agent for such a deadly infectious disease. In this study, pharmacoinformatics-based methods were adopted to find effective novel chemical entities against Ebola virus. A well predictive and statistical robust pharmacophore model was developed from known Ebola virus inhibitors collected from the literature. The model explained the significance of each of hydrogen bond acceptor and donor, and two hydrophobic regions for activity. The National Cancer Institute and Asinex (Antiviral library) databases were screened using the final validated pharmacophore model. Initial hits were further screened with a set of criteria and finally eight molecules from both databases were proposed as promising anti Ebola agents. Further molecular docking and molecular dynamics studies were carried out and it was found that the proposed molecules possessed capability to interact with amino residues of Ebola protein as well as retaining equilibrium of protein-ligand systems. Finally, the binding energies were calculated using molecular mechanics Poisson–Boltzmann surface area approach and all proposed molecules showed strong binding affinity towards the Ebola protein receptor.