Application of Eccentricity-Based Topological Indices to the Design and Optimization of Blood Cancer Drugs

In this study, we apply QSPR analysis to some potent drugs used in blood cancer treatment using eccentricity-based topological indices, which are structural descriptors capturing the shape and size of the molecules as well as their branching and symmetry. These index values are computed by partitioning the corresponding molecular graphs of the drugs for both vertex and edge sets based on their degrees and eccentricities. Then, cubic regression analysis is incorporated into the structural property relational models with these indices and their corresponding physical properties. This work also deals with the various statistical parameters that affect the goodness of the model, and their error analysis is discussed, thereby producing impactful regression models through the graphical depiction of their curve fits.