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Войти в исследования Current computer-aided drug design · 2025
Molecular Dynamics Simulation of SARS-CoV-2 E Ion Channel: The Study of Lone Protein and its Conformational Changes in Complex with Potential Cage Inhibitors.
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Shiryaev Vadim Andreevich, Ivleva Elena Alexandrovna, Zaborskaya Maria Sergeevna, Tkachenko Ilya Michailovich, Osyanin Vitaly Alexandrovich, Klimochkin Yuri Nikolaevich
Аннотация
BACKGROUND: The coronavirus E ion channel has previously been studied as a potential target for antiviral therapy, with several compounds found to bind to the channel. Since, these compounds have low activity, searching for effective E ion channel inhibitors of great importance.
OBJECTIVE: This study aimed to develop a computational approach for designing ligands for the coronaviral E ion channel and identify potential inhibitors based on this approach.
METHODS: The structure of the E-ion channel was refined using molecular dynamics, and the pore responsible for binding cage compounds was selected as the inhibitor-binding site. Potential inhibitor structures were identified using molecular docking, and their binding was confirmed using molecular dynamics simulations.
RESULTS: A number of potential SARS E ion channel inhibitors have been identified, and the binding modes and possible mechanisms of action of these inhibitors have been clarified.
CONCLUSION: This study presents a computational approach that can be used to design ligands for E ion channels and identify potential inhibitors, providing valuable insights into the development of new antiviral therapies. The behavior of the E protein pentamer of SARS-CoV-2 in its native environment was investigated using Molecular Dynamics (MD), resulting in an equilibrated structure that could be used to develop new inhibitors through molecular docking. Simulation of the MD of E-channel complexes with amantadine analogues allowed for the identification of the main types of ligand-protein interactions that are responsible for the good binding of ligands within the channel's inner chamber.
OBJECTIVE: This study aimed to develop a computational approach for designing ligands for the coronaviral E ion channel and identify potential inhibitors based on this approach.
METHODS: The structure of the E-ion channel was refined using molecular dynamics, and the pore responsible for binding cage compounds was selected as the inhibitor-binding site. Potential inhibitor structures were identified using molecular docking, and their binding was confirmed using molecular dynamics simulations.
RESULTS: A number of potential SARS E ion channel inhibitors have been identified, and the binding modes and possible mechanisms of action of these inhibitors have been clarified.
CONCLUSION: This study presents a computational approach that can be used to design ligands for E ion channels and identify potential inhibitors, providing valuable insights into the development of new antiviral therapies. The behavior of the E protein pentamer of SARS-CoV-2 in its native environment was investigated using Molecular Dynamics (MD), resulting in an equilibrated structure that could be used to develop new inhibitors through molecular docking. Simulation of the MD of E-channel complexes with amantadine analogues allowed for the identification of the main types of ligand-protein interactions that are responsible for the good binding of ligands within the channel's inner chamber.