Computational analysis of molecular descriptors for anti-tuberculosis drugs used in tuberculosis treatment through quantitative structure-property relationships

Abstract

Tuberculosis poses a major public health challenge due to its widespread prevalence and severe health impact, necessitating the development of effective therapeutic agents. This study analyzes the structural and physicochemical characteristics of 13 anti-tuberculosis drugs, including Isoniazid, Levofloxacin, and Bedaquiline, using distance-based topological descriptors, particularly the Mostar index. A computational approach involving the Mostar index and Quantitative Structure-Property Relationship (QSPR) analysis was employed to predict critical drug properties like melting point and molar mass. The findings revealed strong correlations (melting point R > 0.990, molar mass R > 0.970), demonstrating the predictive potential of the Edge Mostar index. These results offer valuable insights into the structural properties of anti-tuberculosis drugs, supporting the development of novel agents by leveraging the Mostar index for improved drug design.