Literature DB >> 33450550

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

Malti Sanjay Kalbhor1, Shovonlal Bhowmick2, Amer M Alanazi3, Pritee Chunarkar Patil1, Md Ataul Islam4.   

Abstract

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.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  MM-GBSA / MM-PBSA; Molecular docking; Molecular dynamics; Nipah virus glycoprotein; Virtual screening

Year:  2020        PMID: 33450550     DOI: 10.1016/j.bpc.2020.106537

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


  3 in total

1.  Structure-based identification of galectin-1 selective modulators in dietary food polyphenols: a pharmacoinformatics approach.

Authors:  Shovonlal Bhowmick; Achintya Saha; Nora Abdullah AlFaris; Jozaa Zaidan ALTamimi; Zeid A ALOthman; Tahany Saleh Aldayel; Saikh Mohammad Wabaidur; Md Ataul Islam
Journal:  Mol Divers       Date:  2021-09-05       Impact factor: 3.364

2.  Identification of bio-active food compounds as potential SARS-CoV-2 PLpro inhibitors-modulators via negative image-based screening and computational simulations.

Authors:  Shovonlal Bhowmick; Nora Abdullah AlFaris; Jozaa Zaidan ALTamimi; Zeid A ALOthman; Pritee Chunarkar Patil; Tahany Saleh Aldayel; Saikh Mohammad Wabaidur; Achintya Saha
Journal:  Comput Biol Med       Date:  2022-04-01       Impact factor: 6.698

3.  Computational Identification of Potential Multitarget Inhibitors of Nipah Virus by Molecular Docking and Molecular Dynamics.

Authors:  Vinay Randhawa; Shivalika Pathania; Manoj Kumar
Journal:  Microorganisms       Date:  2022-06-09
  3 in total

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