Modeling the Physical Properties of Cholera Treatment Drugs via Neighborhood Sum Degree-Based Topological Indices

Cholera remains a global health challenge, which requires the optimization of treatment strategies, including the design of effective drugs. This study explores the utility of neighborhood sum degree-based topological indices (TIs) in predicting the physical properties of cholera treatment drugs through quantitative structure-property relationship (QSPR) modeling. Eight TIs, neighborhood first Zagreb, second Zagreb, hyper Zagreb, geometric-arithmetic, forgotten, harmonic, Randi´c and atom bond connectivity indices were evaluated using linear regression models across six physicochemical properties: boiling point, flash point, enthalpy of vaporization, molar refraction, polarization, and molar volume. Among all indices, neighborhood harmonic, sum connectivity, and atom bond connectivity indices stand out for their high R2 values and low standard errors in modeling molar refraction and polarization. For boiling point and flash point, the neighborhood first and second Zagreb indices, and randic index provide moderate predictive power. Some indices such as neighborhood hyper, second Zagreb and forgotten indices showed moderate performance for all physical properties.