QSPR Analysis of Some Important Drugs Used in Heart Attack Treatment via Degree-Based Topological Indices and Regression Models

Abstract

Degree-based topological indices are very useful tools to model and characterize the molecular structure of drugs in order to predict their physicochemical properties without going into laborious and time-consuming laboratory experiments. These indices are numerical descriptors derived for the molecular structures using the principles of graph theory. Degree-based topological indices play a vital role in the QSPR analysis of heart attack drugs by providing molecular descriptors to predict their properties. The main goal of this paper is to compute six degree-based topological indices and a regression model for seven heart attack drugs. These drugs are nitroglycerin, clopidogrel, beta-blockers (metoprolol), ACE inhibitors (lisinopril), statins (atorvastatin), (ARBs) losartan, and beta-adrenergic blockers (propranolol). Regression analysis and degree-based indices correlate with various physicochemical properties related to drug activities, such as molecular weight, complexity, melting point, and boiling point. Correlations provide insights into how the molecular structure influences these properties, helping design and optimize new drugs. In the results, various statistical parameters are used to analyze heart attack drugs.

Keywords:

• Chemical graph theory
• Degree-based topological indices
• Heart attack drugs
• QSPR analysis
• Regression model

Disclosure statement

No potential conflict of interest was reported by the authors.