Abstract Cancer is a hideous disease caused due to the excessive increase in infected cells in the body, millions of people every year are affected due to this disease and its mortality rate is much higher than any other disease. Medicines and therapies used for this precarious disease are also dangerous for the healthy cells, to improve their efficacy and effectiveness, many optimum methods are used. Physicochemical properties and biological activities of medicines are directly related to their performance, researchers paid special attention to maximizing the efficiency by studying these physicochemical properties using different methods. One of the optimum methods to investigate physicochemical properties is the topological descriptor. The topological descriptor is an invariant, which relates some of the physicochemical properties with a numerical value and helps to understand the insights of the molecular structure of some drugs (medicines). In this paper, we use the anticancer drugs encompassing vorinostat, tucidinostat, triciferol, and CUDC-907 to investigate the insights, distance-based topological descriptors including Trinajstic descriptor, Mostar descriptor, Padmakar-Ivan descriptor, and Szeged descriptor are used to explore the physicochemical properties including density, molecular refraction, LogP, polar surface area, polarizability, standard temperature, and molar volume. Moreover, a regression model and graphical representation is given to batter understanding of the insights of aforesaid drugs.
Abid et al. (Wed,) studied this question.