Multi-step molecular docking and dynamics simulation-based screening of large antiviral specific chemical libraries for identification of Nipah virus glycoprotein inhibitors

• Published in: Biophysical chemistry 2021-03, Vol.270, p.106537, Article 106537
• Main Authors: Kalbhor, Malti Sanjay, Bhowmick, Shovonlal, Alanazi, Amer M., Patil, Pritee Chunarkar, Islam, Md Ataul
• Format: Article
• Language: English
• Subjects: MM-GBSA / MM-PBSA; Molecular docking; Molecular dynamics; Nipah virus glycoprotein; Virtual screening
• ISSN: 0301-4622; 1873-4200
• DOI: 10.1016/j.bpc.2020.106537

Nipah virus (NiV) infections are highly contagious and can cause severe febrile encephalitis. An outbreak of NiV infection has reported high mortality rates in Southeast Asian countries including Bangladesh, East Timor, Malaysia, Papua New Guinea, Vietnam, Cambodia, Indonesia, Madagascar, Philippines, Thailand and India. Considering the high risk for an epidemic outbreak, the World Health Organization (WHO) declared NiV as an emerging priority pathogen. However, there are no effective therapeutics or any FDA approved drugs available for the treatment of this infection. Among the known nine proteins of NiV, glycoprotein plays an important role in initiating the entry of viruses and attaching to the host cell receptors. Herein, three antiviral databases consisting of 79,892 chemical entities have been computationally screened against NiV glycoprotein (NiV-G). Particularly, multi-step molecular docking followed by extensive molecular binding interactions analyses, binding free energy estimation, in silico pharmacokinetics, synthetic accessibility and toxicity profile evaluations have been carried out for initial identification of potential NiV-G inhibitors. Further, molecular dynamics (MD) simulation has been performed to understand the dynamic properties of NiV-G protein-bound with proposed five inhibitors (G1-G5) and their interactions behavior, and any conformational changes in NiV-G protein during simulations. Moreover, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) based binding free energies (∆G) has been calculated from all MD simulation trajectories to understand the energy contribution of each proposed compound in maintaining and stabilizing the complex binding interactions with NiV-G protein. Proposed compounds showed high negative ∆G values ranging from −166.246 to −226.652 kJ/mol indicating a strong affinity towards the NiV-G protein. [Display omitted] •Nipah Virus (NiV) is highly lethal, emerging, and count among various medically important bat-borne viruses.•A set of 79,892 compounds were screened against NiV protein through a multi-step molecular docking study.•Based on Glide_XP score, binding free energy and pharmacokinetics assessment, 5 molecules found as potential NiV protein inhibitors.•Binding interaction and molecular dynamics simulations suggested the potentiality of the selected molecules for NiV inhibition.•Binding energy calculated using MM-PBSA approach indicates strong binding affinity of the molecules towards NiV pro