QSPR and QSTR analysis to explore pharmacokinetic and toxicity properties of antifungal drugs through topological descriptors.

COVID-19 patients often develop serious fungal infections like Aspergillosis, Candidiasis, and Mucormycosis, which are treated with antifungal drugs like Amphotericin B, Posaconazole, and Isavuconazole. However, these treatments are often insufficient, leading researchers to explore drug combinations and analogs. In theoretical chemistry, a chemical molecule is converted into an isomorphic molecular graph, represented as G (V, E) by considering atom set V as vertices and bond set E as edges. Quantitative structure-activity/property/toxicity relationships (QSAR, QSPR, QSTR) modelling is a widely recognized discipline that correlates physicochemical and molecular descriptors with a drug's bioactivity to predict its standard pharmacological properties. In this article, the aforementioned drugs, as well as some Amphotericin B analogs, with their properties, are considered for QSPR/QSTR analysis. The QSPR/QSTR analysis is carried out using linear regression between the computed topological indices (based on degree and neighbourhood degree sum) and pharmacokinetic (ADMET) and toxicity properties (LD50) of these drugs. The analysis reveals a strong correlation between the topological indices and the pharmacokinetic and toxicity properties of the drugs and their analogs. These insights are crucial for advancing more effective antifungal treatments, especially for COVID-19-related infections.