Computational approaches: atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted anti-tubercular agents

Tuberculosis (TB) has become the biggest threat to human society because of the rapid rise in resistance to the causative bacteria Mycobacterium tuberculosis (MTB) against the available anti-tubercular drugs. There is an urgent need to design new multi-targeted anti-tubercular agents to overcome the resistance species of MTB through computational design tools. With this aim in mind, we performed a combination of atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), six-point pharmacophore (AHHRRR), and molecular docking analysis on a series of fifty-eight anti-tubercular agents. The created QSAR model had a R<sup>2</sup> value of 0.9521, a Q<sup>2</sup> value of 0.8589, and a Pearson r-factor of 0.8988, all of which are statistically significant. This means that the model was effective at making predictions. We performed the molecular docking study for the data set of compounds with the two important anti-tubercular target proteins, Enoyl acyl carrier protein reductase (InhA) (PDBID: 2NSD) and Decaprenyl phosphoryl-β-D-Ribose 20-epimerase (DprE1) (PDBID: 4FDO). We used the similarity search principle to do virtual screening on 237 compounds from the PubChem database in order to find strong anti-tubercular agents that act against multiple targets. The screened compound, MK3, showed the highest docking score of -9.2 and -8.3 kJ/mol towards both the target proteins InhA and DprE1, which were picked for a 100 ns molecular-dynamic simulation study using GROMACS. The data showed that the compound MK3 was thermodynamically stable and effectively bound to both target proteins in their active binding pockets without much movement. The analysis of the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), and energy gap predicts the molecular reactivity and stability of the identified molecule. Based on the result of the above studies, the proposed compound MK3 can be successfully used for the development of a novel multi-targeted anti-tubercular agent with high binding affinity and favourable ADME-T properties.

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Publication Details

Journal
BMC Chemistry
Published
2025-02-13
DOI
https://doi.org/10.1186/s13065-024-01357-2
Citations
12
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
16.75
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article

Computational approaches: atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted anti-tubercular agents

Debadash Panigrahi, Susanta Kumar Sahu
12 citations
BMC Chemistry
Tuberculosis Research and Epidemiology
16.75
article

Computational approaches: atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted anti-tubercular agents

Debadash Panigrahi, Susanta Kumar Sahu
article en
12 citations

Abstract

Tuberculosis (TB) has become the biggest threat to human society because of the rapid rise in resistance to the causative bacteria Mycobacterium tuberculosis (MTB) against the available anti-tubercular drugs. There is an urgent need to design new multi-targeted anti-tubercular agents to overcome the resistance species of MTB through computational design tools. With this aim in mind, we performed a combination of atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), six-point pharmacophore (AHHRRR), and molecular docking analysis on a series of fifty-eight anti-tubercular agents. The created QSAR model had a R<sup>2</sup> value of 0.9521, a Q<sup>2</sup> value of 0.8589, and a Pearson r-factor of 0.8988, all of which are statistically significant. This means that the model was effective at making predictions. We performed the molecular docking study for the data set of compounds with the two important anti-tubercular target proteins, Enoyl acyl carrier protein reductase (InhA) (PDBID: 2NSD) and Decaprenyl phosphoryl-β-D-Ribose 20-epimerase (DprE1) (PDBID: 4FDO). We used the similarity search principle to do virtual screening on 237 compounds from the PubChem database in order to find strong anti-tubercular agents that act against multiple targets. The screened compound, MK3, showed the highest docking score of -9.2 and -8.3 kJ/mol towards both the target proteins InhA and DprE1, which were picked for a 100 ns molecular-dynamic simulation study using GROMACS. The data showed that the compound MK3 was thermodynamically stable and effectively bound to both target proteins in their active binding pockets without much movement. The analysis of the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), and energy gap predicts the molecular reactivity and stability of the identified molecule. Based on the result of the above studies, the proposed compound MK3 can be successfully used for the development of a novel multi-targeted anti-tubercular agent with high binding affinity and favourable ADME-T properties.

BMC ChemistryVol. 19(1)
Yahoo (United Kingdom) (GB), Utkal University (IN)
Openalex Percentile: Top 1%
Tuberculosis Research and Epidemiology
16.75
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