On Topological Descriptors and Curvilinear Regression Analysis of Antiviral Drugs Used in COVID-19 Treatment

Abstract

Topological indices are used to research the chemical, biological, clinical, and medicinal properties of drugs in the field of chemical and medical sciences. The COVID-19 pandemic is widely regarded as the most life-threatening problem that modern medicine has ever faced. Scientists have tested usable antiviral agents and found that they have a significant impact on recovery from viral diseases such as COVID-19. Arbidol, Chloroquine, Hydroxychloroquine, Lopinavir, Remdesivir, Ritonavir, Thalidomide, and Theaflavin are some of the antiviral agents used in the treatment of COVID-19. In this paper we propose reduced reverse degree-based topological descriptors such as reduced reverse Zagreb indices, reduced reverse forgotten index, reduced reverse atom bond connectivity index, reverse geometric arithmetic index and reduced reverse general Randić index for the antiviral drugs of COVID-19. We also analyze the Quantitative Structure-Property Relationship (QSPR) of the proposed topological indices. Curvilinear regression models are obtained and analyzed for the physico-chemical properties of the COVID-19 drugs, in terms of the proposed indices. Our models and findings could aid in the development of new drugs for the treatment of COVID-19.