Molecular modeling of natural and synthesized inhibitors against SARS-CoV-2 spike glycoprotein

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Abstract

Purpose: Viral diseases increasingly endanger the world public health because of the transient efficacy of antiviral therapies. The novel coronavirus disease 2019 (COVID-19) has been recently identified as caused by a new type of coronaviruses. This type of coronavirus binds to the human receptor through the Spike glycoprotein (S) Receptor Binding Domain (RBD). The spike protein is found in inaccessible (closed) or accessible (open) conformations in which the accessible conformation causes severe infection. Thus, this receptor is a significant target for antiviral drug design. Methods: An attempt was made to recognize 111 natural and synthesized compounds in order to utilize them against SARS-CoV-2 spike glycoprotein to inhibit Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using simulation methods, such as molecular docking. The FAF-Drugs3, Pan-Assay Interference Compounds (PAINS), ADME (absorption, distribution, metabolism, excretion) databases along with Lipinski’s rules were used to evaluate the drug-like properties of the identified ligands. In order to analyze and identify the residues critical in the docking process of the spike glycoprotein, the interactions of proposed ligands with both conformations of the spike glycoprotein was simulated. Results: The results showed that among the available ligands, seven ligands had significant interactions with the binding site of the spike glycoprotein, in which angiotensin-converting enzyme 2 (ACE2) is bounded. Out of seven candidate molecules, six ligands exhibited drug-like characteristics. The results also demonstrated that fluorophenyl and propane groups of ligands had optimal interactions with the binding site of the spike glycoprotein. Conclusion: According to the results, our findings indicated the ability of six ligands to prevent the binding of the SARS-CoV-2 spike glycoprotein to its cognate receptor, providing novel compounds for the treatment of COVID-19.

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Jomhori, M., & Mosaddeghi, H. (2022). Molecular modeling of natural and synthesized inhibitors against SARS-CoV-2 spike glycoprotein. Research on Biomedical Engineering, 38(1), 71–86. https://doi.org/10.1007/s42600-020-00122-3

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