Chemical Invariant Analysis of Drug Structures Using Multi-Criteria Decision-Making Approaches: TOPSIS and SAW

Abstract

Extensive research in recent years has shown the strong relationship between many physicochemical and biological features, including medication toxicity, melting and boiling points, and topological descriptors of chemical structures. For describing molecular graphs and forecasting these crucial characteristics, topological indices (TIs) have become extremely effective mathematical tools. Chain oxides, chain silicate networks, sheet oxide networks, and sheet silicates are among the molecular drug frameworks whose structural properties are examined in this work using a comprehensive topological analysis.. We measure the molecular complexity and connectivity of these structures using a variety of topological indices, such as the Randić Index, Augmented Zagreb Index, and Forgotten Topological Index (FTI). In addition, we rank and evaluate the molecular designs based on their topological signatures using Multi-Criteria Decision-Making (MCDM) methods, specifically the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Simple Additive Weighting (SAW) technique.. The results provide light on the relative effectiveness of different indices and frameworks for making decisions when evaluating the pharmacological and chemical properties of possible therapeutic options.