Study of drug structures using topological descriptors and multi-criteria decision making

It has been observed that there is a strong correlation between topological descriptors of chemical structures and their physical properties in a number of tests every year. There are several of these characteristics, including molecular mass, density, melting and boiling points, flash points, and others. Topological indices are numerical numbers associated with the molecular graph and are used in quantitative structure property relationship studies to predict their physical and chemical properties. In this work, we have calculated the reverse degree based topological descriptors of five molecular structures namely, hyaluronic acid-paclitaxel conjugates (G(n)), anticancer drug (SPn), polyomino chain of n-cycle (Z(n)), triangular benzenoid (T-n), and circumcoronene benzenoid series (H-k,k >= 1). The values of topological indices are used in entropy method to calculate the weights. Then, using multiple criteria decision-making techniques like COPRAS and PROMETHEE, we rank these molecular structures.