QSPR analysis of heart attack medications, especially antiplatelet agents and dual antiplatelet therapy (DAPT), through graph labeling based topological indicators and regression models

Abstract

To model and characterize the molecular structure of pharmaceuticals and forecast their physicochemical properties without undergoing time-consuming and arduous laboratory procedures, labeled-based topological indices are highly helpful tools. Using the concepts of graph theory, these indices are numerical descriptors for the molecular structures. Labeled-based topological indices, which offer molecular descriptors to anticipate the features of pharmaceuticals, are essential for the QSPR analysis of heart attack medications, especially antiplatelet agents and dual antiplatelet therapy (DAPT). This research aims to calculate a linear regression model and eight labeled-based topological indices for five antiplatelet agents and dual antiplatelet therapy (DAPT) medications. These drugs are aspirin, clopidogrel, dipyridamole, prasugrel, and ticagrelor. Linear regression analysis and labeled-based topological indices correlate with various physicochemical properties related to drug activities, such as molar refractivity, polar surface, polarizability, molar volume, surface tension, log P, boiling point, and flash point. By shedding light on how the molecular structure affects these characteristics, correlations aid in the development and improvement of novel pharmaceuticals. In this paper, various statistical parameters are used to analyze antiplatelet agents and dual antiplatelet therapy (DAPT) in the case of a heart attack.