In silico Identification of Characteristics Spike Glycoprotein of SARS-CoV-2 in the Development Novel Candidates for COVID-19 Infectious Diseases

Background : The emergence of infectious diseases caused by SARS-CoV-2 has resulted in more than 90,000 infections and 3,000 deaths. The coronavirus spike glycoprotein encourages the entry of SARS-CoV-2 into cells and is the main target of antivirals. SARS-CoV-2 uses ACE2 to enter cells with an affinity similar to SARS-CoV, correlated with the efficient spread of SARS-CoV-2 among humans. Objective : In the research, identification, evaluation, and exploration of the structure of SARS-CoV and SARS-CoV-2 spike glycoprotein macromolecules and their effects on Angiotensin-Converting Enzyme 2 (ACE-2) using in silico studies. Methods : The spike glycoproteins of the two coronaviruses were prepared using the BIOVIA Discovery Studio 2020. Further identification of the three-dimensional structure and sequencing of the macromolecular spike glycoprotein structure using Chimera 1.14 and Notepad++. To ensure the affinity and molecular interactions between the SARS-CoV and SARS-CoV-2 spike glycoproteins against ACE-2 protein-protein docking simulations using PatchDock was accomplished. The results of the simulations were verified using the BIOVIA Discovery Studio 2020. Results : Based on the results of the identification of the macromolecular structure of the spike glycoprotein, it was found that there are some similarities in characteristics between SARS-CoV and SARS-CoV-2. Protein-protein docking simulations resulted that SARS-COV-2 spike glycoprotein has the strongest bond with ACE-2, with an ACE score of −1509.13 kJ/mol. Conclusion : Therefore, some information obtained from the results of this research can be used as a reference in the development of SARS-CoV-2 spike glycoprotein inhibitor candidates for the treatment of infectious diseases of COVID-19.