On topological co-index polynomials for predictive modeling of the physicochemical properties of antiviral drugs

Abstract

This study investigates the potential of topological co-indices and their polynomials as computational tools for predicting the physicochemical properties of antiviral compounds targeting the Ebola virus. For an in-depth Quantitative Structure-Property Relationship (QSPR) analysis, we develop and compute topological co-indices using CoM and CoNM polynomials derived from the molecular structures of antiviral drugs, including Galidesivir, Chloroquine, Favipiravir, Amodiaquine, Azithromycin, Brincidofovir, and Clomiphene. These indices were correlated with some important experimental physicochemical properties via linear and curvilinear regression techniques, and their predictive models were developed. The results reveal strong correlations between the topological indices and physicochemical properties, underscoring their utility in drug discovery and design. A comparative analysis of actual experimental values and those predicted by the topological indices shows their predictive accuracy. To sum up, this study highlights the potential of topological co-indices as innovative tools for speeding up the discovery and optimization of antiviral drugs, especially concerning Ebola virus disease. The findings contribute to the expanding research focused on using computational methods to tackle emerging infectious diseases.