Abstract
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, Randić and atom bond connectivity indices were evaluated using linear regression models across six physic-ochemical 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.
| Original language | English |
|---|---|
| Article number | 171 |
| Journal | International Journal of Analysis and Applications |
| Volume | 23 |
| DOIs | |
| Publication status | Published - 2025 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- QSPR model
- cholera drug
- neigborhood degree-based
- physical properties
- topological indices
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