The novel coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS‐CoV‐2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (M pro ), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on M pro that can be evaluated as drug targets besides the active site. Then, Food and Drug Administration (FDA)‐approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. Fourteen best molecule hits for the active site of M pro are determined. Six of these also exhibit high docking scores for the potential allosteric regions. Full‐atom molecular dynamics simulations with MM‐GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆ G bind ) values. ∆ G bind values reach −52.06 kcal/mol for the active site, −51.08 kcal/mol for the potential allosteric site 1, and − 42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin, and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as M pro inhibitor candidates to be evaluated against SARS‐CoV‐2 infections.
The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS-CoV-2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (Mpro), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on Mpro that can be evaluated as drug targets besides the active site. Then, FDA-approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. 14 best molecule hits for the active site of Mpro are determined. 6 of these also exhibit high docking scores for the potential allosteric regions. Full-atom molecular dynamics simulations with MM-GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆Gbind) values. ∆Gbind values reach -52.06 kcal/mol for the active site, -51.08 kcal/mol for the potential allosteric site 1, and -42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as Mpro inhibitor candidates to be evaluated against SARS-CoV-2 infection
Peptidylarginine deiminase 2 (PAD2) is a Ca 2+ -dependent enzyme that catalyzes the conversion of protein arginine residues to citrulline. This kind of structural modification in histone molecules may affect gene regulation, leading to effects that may trigger several diseases, including breast cancer, which makes PAD2 an attractive target for anticancer drug development. To design new effective inhibitors to control activation of PAD2, improving our understanding of the molecular mechanisms of PAD2 using up-to-date computational techniques is essential. We have designed five different PAD2–substrate complex systems based on varying protonation states of the active site residues. To search the conformational space broadly, multiple independent molecular dynamics simulations of the complexes have been performed. In total, 50 replica simulations have been performed, each of 1 μs, yielding a total simulation time of 50 μs. Our findings identify that the protonation states of Cys647, Asp473, and His471 are critical for the binding and localization of the N -α-benzoyl- l -arginine ethyl ester substrate within the active site. A novel mechanism for enzyme activation is proposed according to near attack conformers. This represents an important step in understanding the mechanism of citrullination and developing PAD2-inhibiting drugs for the treatment of breast cancer.
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