Natural Substances in the Fight of SARS-CoV-2: A Critical Evaluation Resulting from the Cross-Fertilization of Molecular Modeling Data with the Pharmacological Aspects

The recent pandemic due to SARS-CoV-2, the last isolated human betacoronavirus, has revolutionized modern knowledge of the pathogenesis of viral pneumonia. The lack of specific antiviral drugs and the need to develop adequate research for new antiviral drugs capable of treating this new form of the disease undertook three different research paths quickly. The first one is aimed to test antiviral molecules already present in therapeutic use, with a mechanism of action directed towards viral proteins functional to replication or adsorption; the second one, it is the repositioning of molecules with known pharmacological activity for which various chemistry studies have been prepared in an attempt to find new and specific viral targets; the third, it is the search for molecules of natural origin for which to demonstrate a specific anti-coronavirus activity. Many databases of natural and synthetic substances have been used for the identification of potent inhibitors of various viral targets. The field of computer-aided drug design seems to be promising and useful for the identification of SARS-CoV-2 inhibitors; hence, different structure-and ligand-based computational approaches have been used for their identification. This review analyzes in-depth and critically the most recent publications in the field of applied computational chemistry to find out molecules of natural origin with potent antiviral activity. Furthermore, a critical and functional selection of some molecules with the best hypothetical anti-SARS-CoV-2 activity is made for further studies by biological tests.

Automated summary

The outbreak of the COVID-19 pandemic has led to a significant advancement in understanding the pathogenesis of viral pneumonia and the development of antiviral drugs, including testing existing drugs, repositioning molecules, and searching for natural compounds. Computational methods have shown promising results in identifying SARS-CoV-2 inhibitors, with potential for discovering natural compounds with antiviral activity.