Identification of natural FtsZ inhibitors through computational approaches to combat drug-resistant tuberculosis

The Mycobacterial cell division protein FtsZ is a promising target for addressing multidrug-resistant tuberculosis (MDR-TB). We employed computational strategies to screen a large library of natural compounds for FtsZ inhibitors. Our virtual screening process involved high-throughput docking simulations, standard precision and extra precision docking, and in silico ADME analysis to evaluate the drug-likeness of selected compounds. Four promising ligands were identified, with two emerging as potential FtsZ ligands: CID_5487121 (Capuramycin) and CID_71452248 (Deacetylkirschsteinin). These molecules exhibited high docking affinities and consistent behavior throughout molecular dynamics simulations. Our findings demonstrate the potential of these compounds as leads for further experimental validation and development of novel therapeutics against MDR-TB. Additionally, the molecular dynamics simulations provided insights into the stability and interaction patterns of these compounds with the FtsZ protein, highlighting their potential as strong inhibitors. The comprehensive ADME analysis ensured that these compounds possess favorable drug-like properties, making them viable candidates for further development.

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Publication Details

Journal
Results in Chemistry
Published
2025-05-14
DOI
https://doi.org/10.1016/j.rechem.2025.102354
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Identification of natural FtsZ inhibitors through computational approaches to combat drug-resistant tuberculosis

Achyut Raj Pandey, Ram Suresh Bharti, Shruti Mishra
1 citations
Results in Chemistry
Computational Drug Discovery Methods
1.50
article

Identification of natural FtsZ inhibitors through computational approaches to combat drug-resistant tuberculosis

Achyut Raj Pandey, Ram Suresh Bharti, Shruti Mishra
article en
1 citations

Abstract

The Mycobacterial cell division protein FtsZ is a promising target for addressing multidrug-resistant tuberculosis (MDR-TB). We employed computational strategies to screen a large library of natural compounds for FtsZ inhibitors. Our virtual screening process involved high-throughput docking simulations, standard precision and extra precision docking, and in silico ADME analysis to evaluate the drug-likeness of selected compounds. Four promising ligands were identified, with two emerging as potential FtsZ ligands: CID_5487121 (Capuramycin) and CID_71452248 (Deacetylkirschsteinin). These molecules exhibited high docking affinities and consistent behavior throughout molecular dynamics simulations. Our findings demonstrate the potential of these compounds as leads for further experimental validation and development of novel therapeutics against MDR-TB. Additionally, the molecular dynamics simulations provided insights into the stability and interaction patterns of these compounds with the FtsZ protein, highlighting their potential as strong inhibitors. The comprehensive ADME analysis ensured that these compounds possess favorable drug-like properties, making them viable candidates for further development.

Results in ChemistryVol. 16
Jawaharlal Nehru University (IN), Galgotias University (IN), Gautam Buddha University (IN)
Good health and well-being
Openalex Percentile: Top 17%
Computational Drug Discovery Methods
1.50
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