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Research Articles

Computational studies of the properties and activities of selected trisubstituted benzimidazoles as potential antitubercular drugs inhibiting MTB-FtsZ polymerization

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Pages 1558-1570 | Received 20 Jul 2020, Accepted 24 Sep 2020, Published online: 06 Oct 2020
 

Abstract

Trisubstituted benzimidazoles (trisbenz) are significantly active against nonreplicating Mycobacterium tuberculosis (MTB) by inhibiting the polymerization of Filamentous Temperature Sensitive Mutant Z (FtsZ), an essential bacteria cell division protein. In-depth in-silico study of 5 of the most active trisubstituted benzimidazoles; trisbenz 1, 2, 3, 4 and 5, giving insight into their properties, such as stability, bioavailability, interactions with residues at the binding site of MTB-FtsZ and their influence on structural dynamics of the protein have been conducted. This was achieved through the application of in-silico methods including density functional theory (DFT) calculations, ADME properties calculations, molecular docking and molecular dynamics simulations. A DFT approach was applied to predict reactivity properties of potent FtsZ inhibitors, and the results reveal the relative reactivity of these inhibitors as bioactive moieties. The estimated ADME properties predicted all 5 compounds to be bioavailable and suitable for oral administration. Molecular docking, binding free energy, RMSD, RMSF, and hydrogen bond analysis confirmed these 5 compounds as potent MTB-FtsZ inhibitors. Although analyses proved these compounds to be bioactive and potent MTB-FtsZ inhibitors, however, trisbenz 1 appeared to be the most active against this protein while trisbenz 5 was the least active. This study further confirms the experimental study while also giving insight on the compounds mechanism of action and presents their bioavailability properties.

GRAPHICAL ABSTRACT

In silico study of trisubstituted benzimidazoles as potential antitubercular drugs

Communicated by Ramaswamy H. Sarma

Disclosure statement

Authors declare no financial and intellectual conflict of interests.

Additional information

Funding

The authors acknowledge the College of Health Sciences, University of KwaZulu-Natal and Centre for High-Performance Computing (www.chpc.ac.za) all in South Africa, for financial and technical support, respectively.

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