structural analysis of anticancer drugs using reverse degree-based topological indices

One of the biggest global public health issues, cancer puts a heavy financial strain on the nation and raises healthcare costs. furthermore, the efficacy of the existing anticancer medications is significantly hampered by a variety of problems, including poor selectivity and extreme toxicity. an alternative and more cost-effective method of evaluating the biological activity or molecular features of drug molecules is usually needed for new drug design. chemical graph theory evaluates the physicochemical characteristics and biological activity of a drug's molecular graph using molecular descriptors known as topological indices. the present study uses the rem-polynomial to define various reverse degree-based topological indices (rdbtis) on anticancer medicines. to calculate rem-polynomials, the chemical makeup of hyaluronic acid is first examined, conjugated with curcumin, paclitaxel, and methotrexate, and then edge partitioning technique is employed. calculus is used to derive a number of traditional rdbtis for understudied medications. furthermore, to confirm the predictive ability of the rdbtis, twenty anticancer medications were analyzed and quantitative structure property relationships (qspr)  were used to compare the various rdbtis with the five physicochemical characteristics of these medications. the data suggested a meaningful association between the physicochemical features such as boiling  point,  enthalpy, and molar refraction of anticancer medicines and the rdbtis that are being studied.