Predicting optimal drugs for fin rot by reverse topological QSPR analysis.

Abstract

Fin rot is a prevalent bacterial disease affecting aquarium fish, often resulting from poor environmental conditions. Effective treatment relies on selecting suitable drugs with desirable chemical and therapeutic properties. In this study, we employ quantitative structure property relationship (QSPR) analysis to investigate the relationship between molecular structures of drugs and their therapeutic efficacy in treating fin rot. Specifically, we focus on selected set of reverse degree-based topological indices in mathematical chemistry that reflect the structural attributes of molecules. Several drugs commonly used for fin rot treatment were analyzed, and their topological indices were calculated to establish correlations with key drug properties, such as Molar Weight, Complexity, Polarizability, and Exact Mass. The QSPR models developed in this study demonstrate the predictive potential of topological indices in evaluating drug properties. These findings provide a foundation for optimizing drug selection and design, contributing to efficient treatment strategies for fin rot and potentially other bacterial diseases.