The study of regression model based on CoM-polynomial in blood cancer drug properties

Abstract

A topological index (TI) is a real number that determined the structure of a graph. Topological indices (TIs) serves mathematical descriptors that aid in predicting and understanding the physicochemical properties and structure-activity relationships of chemical compounds, thus facilitating drug design and discovery processes. TIs utilizes to forecast the effectiveness of cancer treatment by providing details on the molecules of the medications and their associated properties. In order to create safe and effective treatments, it is crucial to employ TIs to accurately predict the toxicity and side effects of medications. In this paper, we have considered the physical and biological properties of some blood cancer treatment medications through degree based Banhatti topological indices from the M-polynomial by using derivations. The drugs are Palbociclib, Ivosidenib, Glasdegib, Gilteritinib, and Daunorubicin and the TI's are given in Table 1. Subsequently, a linear regression technique is employed to establish a quantitative structure-property relationship (QSPR) model for predicting various parameters such as molecular weight, complexity, molar volume, boiling point (BP), and flash point (FP). Results indicate that topological indices have potential as a drug discovery and development tool in the fight against cancer.

Keywords

• Anti-cancer drugs
• Differential and integral based topological indices
• QSPR analysis
• Regression models