Statistical analysis of Revan topological indices for drug compounds used in treatment of tuberculosis

Abstract One of the most infectious diseases, tuberculosis (TB) has a higher death rate than HIV/AIDS, and as a result of the COVID-19 pandemic, there is concern that the number of TB cases may increase. With the aid of QSPR models, the pharmaceutical industry is continuously searching for methods to enhance medication design procedures to stop the spread of infections and treat recently discovered syndromes or genetically based dysfunctions. QSPR models are mathematical tools that utilize structural properties to establish relationships between a molecular structure and its physicochemical attributes. One way to generate attributes from the molecular graph without the need for experimental measurements is to use topological indices. The goal of this work is to create a QSPR model for tuberculosis drugs and their many physicochemical characteristics using degree-based topological indices.