Computational Biology Analysis of COVID-19 Receptor-Binding Domains: A Target Site for Indocyanine Green Through Antimicrobial Photodynamic Therapy

Introduction: the receptor-binding domain (rbd) in sars-cov-2 binds strongly to angiotensin- converting enzyme 2 (ace2) receptors and causes coronavirus disease 2019 (covid-19). 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-2 as a target site for apdt. methods: sars-cov-2-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-2-rbd has 223 amino acids with a molecular weight of 25098.40 da. rbd is most similar to 6w41 with an e-value of 4e-167, identity of 100%, and query cover of 100%. the aliphatic index of the rbd protein sequences was 71.61, 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 (69.51%). four ligands were modeled in this entry, including one n-acetyl-d-glucosamine (nag), one glycerol (gol), and two sulfate ions (so_4), to which icg desires to bind in the molecular docking analysis. conclusion: molecular modeling and simulation analysis showed that sars-cov-2-rbd could be a substrate for binding to icg during apdt to control the spread of covid-19.