Computational Biology Analysis of COVID-۱۹ Receptor-Binding Domains: A Target Site for Indocyanine Green Through Antimicrobial Photodynamic Therapy

Abstract Introduction: The receptor-binding domain (RBD) in SARS-CoV-۲ binds strongly to angiotensin-converting enzyme ۲ (ACE۲) receptors and causes coronavirus disease ۲۰۱۹ (COVID-۱۹). Antimicrobial photodynamic therapy (aPDT) is a well-established treatment option for the treatment of several viral infections. This in silico study was conducted to target the RBD of SARS-CoV-۲ as a target site for aPDT.Methods: SARS-CoV-۲-RBD was selected as a novel target for indocyanine green (ICG) as a photosensitizer during aPDT to exploit its molecular modeling, hierarchical nature of protein structure, and physico-chemical properties using several bioinformatic tools. The binding mode of the RBD to ICG was assessed via protein-ligand docking.Results: The results of a computational biology analysis revealed that SARS-CoV-۲-RBD has ۲۲۳ amino acids with a molecular weight of ۲۵۰۹۸.۴۰ Da. RBD is most similar to ۶W۴۱ with an E-value of ۴e-۱۶۷, an identity of ۱۰۰%, and a query cover of ۱۰۰%. The aliphatic index of the RBD protein sequences was ۷۱.۶۱, suggesting that the protein is stable in a broad spectrum of temperatures. The predicted structure of RBD showed that it is a protein with a positive charge and a random coil structure (۶۹.۵۱%). Four ligands were modeled in this entry, including one N-acetyl-D-glucosamine (NAG), one glycerol (GOL), and two sulfate ions (SO۴), to which ICG desires to bind in the molecular docking analysis.Conclusion: Molecular modeling and simulation analysis showed that SARS-CoV-۲-RBD could be a substrate for binding to ICG during aPDT to control the spread of COVID-۱۹. Keywords: Antimicrobial photodynamic therapy Bioinformatics tools Indocyanine green In silico SARS-CoV-۲