Abstract
In this study, we investigate the efficacy of neighborhood-degree-based topological indices in the modeling of drug properties pertinent to HIV/AIDS. By representing molecular structures as graphs, we delve deep into atom-level environments, uncovering intricate relationships between local topological attributes and theoretical characteristics. Through meticulous quantitative structure–property relationship analysis, we establish robust correlations between these indices and drug properties. This breakthrough augurs predictive insights in the realm of pharmaceutical research, reducing the need for exhaustive experimentation. Our research underscores the pivotal role played by neighborhood-degree-based topological indices in advancing drug discovery, offering a powerful tool that resonates with chemists and industry professionals. It marks a transformative step in the trajectory of pharmaceutical development, promising to redefine and enhance the future of drug design and innovation.
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