Literature DB >> 26587786

In silico prediction of ebolavirus RNA polymerase inhibition by specific combinations of approved nucleotide analogues.

Formijn J van Hemert1, Hans L Zaaijer2, Ben Berkhout3.   

Abstract

BACKGROUND AND
OBJECTIVE: The urgency of ebolavirus drug development is obvious in light of the current local epidemic in Western Africa with high morbidity and a risk of wider spread. We present an in silico study as a first step to identify inhibitors of ebolavirus polymerase activity based on approved antiviral nucleotide analogues. STUDY
DESIGN: Since a structure model of the ebolavirus polymerase is lacking, we performed combined homology and ab initio modeling and report a similarity to known polymerases of human enterovirus, bovine diarrhea virus and foot-and-mouth disease virus. This facilitated the localization of a nucleotide binding domain in the ebolavirus polymerase. We next performed molecular docking studies with nucleotides (ATP, CTP, GTP and UTP) and nucleotide analogues, including a variety of approved antiviral drugs. RESULTS AND
CONCLUSIONS: Specific combinations of nucleotide analogues significantly reduce the ligand-protein interaction energies of the ebolavirus polymerase for natural nucleotides. Any nucleotide analogue on its own did not reduce ligand-protein interaction energies. This prediction encourages specific drug testing efforts and guides future strategies to inhibit ebolavirus replication.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Binding affinity; Ebolavirus; Modeling; Nucleotide analogues; Polymerase

Mesh:

Substances:

Year:  2015        PMID: 26587786     DOI: 10.1016/j.jcv.2015.10.020

Source DB:  PubMed          Journal:  J Clin Virol        ISSN: 1386-6532            Impact factor:   3.168


  2 in total

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Authors:  Jason G Glanzer; Brendan M Byrne; Aaron M McCoy; Ben J James; Joshua D Frank; Greg G Oakley
Journal:  Bioorg Med Chem       Date:  2016-09-04       Impact factor: 3.641

Review 2.  Therapeutic Strategies against Ebola Virus Infection.

Authors:  Ching-Hsuan Liu; Yee-Tung Hu; Shu Hui Wong; Liang-Tzung Lin
Journal:  Viruses       Date:  2022-03-11       Impact factor: 5.048

  2 in total

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