Computational Approaches in Drug Design: Study Quantitative Structure-Property Relationship of Organotin(IV) Carboxylates

It has been observed that a significant correlation between bioactivity and mathematical descriptors of a molecule. Topological indices serve as vital predictive instruments for pharmaceutical compounds because they reveal structural patterns of organotin(IV) carboxylates and other bioactive substances. Consequently, TIs find extensive therapeutic applications in studying antiproliferative effects, fungicide resistance, antibiotic resistance, anti-inflammatory activity, antiparasitic activity and enzyme inhibition. Analysis of degree-based TIs provides essential insights into optimal treatment approaches, as well as toxicity and side effects related with organotin(IV) carboxylates drugs. This predictive capability facilitates the design of safer, more efficient medications. The discovery of new substances has benefited from TIs through the identification of critical structural-property relationships during drug synthesis. The current study employs graph-based topological indices and regression model to evaluates how these descriptors determine the physicochemical, as well as biological features of novel pharmaceutical compounds. These findings establish an investigation for new therapeutic agents by assessing their multi-functional biological potential.