Exploring the properties of antituberculosis drugs through QSPR graph models and domination-based topological descriptors

Tuberculosis (TB) is a global health concern caused by the bacterium Mycobacterium tuberculosis. This infectious disease primarily affects the lungs but can also impact other organs. Effective TB control involves early diagnosis, appropriate treatment with a combination of antibiotics, and public health measures to prevent transmission. However, ongoing challenges include drug-resistant strains and socioeconomic factors influencing its prevalence. Drugs such as isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are approved for the treatment of drug-susceptible tuberculosis. The properties and other activities of the drug, can be analyzed by modelling its chemical structure in terms of a molecular graph [Formula: see text], by considering the atoms as the vertex set [Formula: see text] and the bonds between the two atoms as the edge set [Formula: see text]. A molecular descriptor or topological index of [Formula: see text] represents the corresponding chemical molecule as a numerical value. Domination is one of the key concepts in the molecular structure used to analyze the properties of atoms. In this article, the domination distance-based topological indices of the drugs isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are computed to conduct QSPR (Quantitative Structure-Property Relationship) analysis, exploring their physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. Quadratic regression is then used in the QSPR analysis to examine the physicochemical and ADMET properties of these drugs. The results of this analysis indicate that the domination Schultz index and domination SM index are the indices most strongly correlated with the majority of the physicochemical and ADMET properties. The QSPR analysis can also be extended to analogs of these drugs and to other treatment drugs, such as rifampin and rifapentine, to further explore their properties.

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Journal
Scientific Reports
Published
2024-10-17
DOI
https://doi.org/10.1038/s41598-024-73918-3
Citations
10
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.61

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article

Exploring the properties of antituberculosis drugs through QSPR graph models and domination-based topological descriptors

Thilsath Parveen S, Muhammad Kamran Siddiqui, Balamurugan Bommahalli Jayaraman
10 citations
Scientific Reports
Computational Drug Discovery Methods
3.61
article

Exploring the properties of antituberculosis drugs through QSPR graph models and domination-based topological descriptors

Thilsath Parveen S, Muhammad Kamran Siddiqui, Balamurugan Bommahalli Jayaraman
article en
10 citations

Abstract

Tuberculosis (TB) is a global health concern caused by the bacterium Mycobacterium tuberculosis. This infectious disease primarily affects the lungs but can also impact other organs. Effective TB control involves early diagnosis, appropriate treatment with a combination of antibiotics, and public health measures to prevent transmission. However, ongoing challenges include drug-resistant strains and socioeconomic factors influencing its prevalence. Drugs such as isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are approved for the treatment of drug-susceptible tuberculosis. The properties and other activities of the drug, can be analyzed by modelling its chemical structure in terms of a molecular graph [Formula: see text], by considering the atoms as the vertex set [Formula: see text] and the bonds between the two atoms as the edge set [Formula: see text]. A molecular descriptor or topological index of [Formula: see text] represents the corresponding chemical molecule as a numerical value. Domination is one of the key concepts in the molecular structure used to analyze the properties of atoms. In this article, the domination distance-based topological indices of the drugs isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are computed to conduct QSPR (Quantitative Structure-Property Relationship) analysis, exploring their physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. Quadratic regression is then used in the QSPR analysis to examine the physicochemical and ADMET properties of these drugs. The results of this analysis indicate that the domination Schultz index and domination SM index are the indices most strongly correlated with the majority of the physicochemical and ADMET properties. The QSPR analysis can also be extended to analogs of these drugs and to other treatment drugs, such as rifampin and rifapentine, to further explore their properties.

Scientific ReportsVol. 14(1)
COMSATS University Islamabad (PK), Vellore Institute of Technology University (IN)
Vellore Institute of Technology, Chennai, VIT University
Good health and well-being
Openalex Percentile: Top 6%
Computational Drug Discovery Methods
3.61
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