PMC:7784834 / 13054-17959 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"209","span":{"begin":96,"end":101},"obj":"Gene"},{"id":"210","span":{"begin":650,"end":655},"obj":"Gene"},{"id":"211","span":{"begin":1253,"end":1258},"obj":"Gene"},{"id":"212","span":{"begin":740,"end":758},"obj":"Gene"},{"id":"213","span":{"begin":85,"end":95},"obj":"Species"},{"id":"214","span":{"begin":349,"end":354},"obj":"Chemical"},{"id":"215","span":{"begin":593,"end":598},"obj":"Chemical"},{"id":"216","span":{"begin":851,"end":856},"obj":"Chemical"},{"id":"217","span":{"begin":1310,"end":1315},"obj":"Chemical"},{"id":"221","span":{"begin":2014,"end":2015},"obj":"Gene"},{"id":"222","span":{"begin":2056,"end":2057},"obj":"Gene"},{"id":"223","span":{"begin":2271,"end":2279},"obj":"Chemical"},{"id":"226","span":{"begin":3871,"end":3876},"obj":"Gene"},{"id":"227","span":{"begin":3673,"end":3681},"obj":"Chemical"},{"id":"230","span":{"begin":4166,"end":4171},"obj":"Gene"},{"id":"231","span":{"begin":4834,"end":4837},"obj":"Disease"}],"attributes":[{"id":"A209","pred":"tao:has_database_id","subj":"209","obj":"Gene:43740568"},{"id":"A210","pred":"tao:has_database_id","subj":"210","obj":"Gene:43740568"},{"id":"A211","pred":"tao:has_database_id","subj":"211","obj":"Gene:43740568"},{"id":"A213","pred":"tao:has_database_id","subj":"213","obj":"Tax:2697049"},{"id":"A214","pred":"tao:has_database_id","subj":"214","obj":"MESH:D014867"},{"id":"A215","pred":"tao:has_database_id","subj":"215","obj":"MESH:D014867"},{"id":"A216","pred":"tao:has_database_id","subj":"216","obj":"MESH:D014867"},{"id":"A217","pred":"tao:has_database_id","subj":"217","obj":"MESH:D012431"},{"id":"A221","pred":"tao:has_database_id","subj":"221","obj":"Gene:4137"},{"id":"A222","pred":"tao:has_database_id","subj":"222","obj":"Gene:4137"},{"id":"A223","pred":"tao:has_database_id","subj":"223","obj":"MESH:D006859"},{"id":"A226","pred":"tao:has_database_id","subj":"226","obj":"Gene:43740568"},{"id":"A227","pred":"tao:has_database_id","subj":"227","obj":"MESH:D006859"},{"id":"A230","pred":"tao:has_database_id","subj":"230","obj":"Gene:43740568"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"2.4. Molecular dynamics trajectory analysis of protein and their docked complex\nThe SARS-CoV-2 spike protein and main protease were used separately for molecular dynamics (MD) simulations alone and in complex with the repurposed drug, rutin. All the four MD simulations were executed through GROMACS v5.0 under the force field GROMOS96 54a7 having water model SPC216 along with the time step of 1 fs for 100 ns (Abraham et al., 2015; Darden et al., 1993). Varied sizes of the simulation box were created for each MD simulation event, which were further loaded with about respective amount of water molecules using the SPC model. The total charge on spike protein, main protease and the two in complex with rutin were neutralized by adding –6, –4, –6, and –4 charges, respectively, and were incorporated into the simulation system by compensating the water molecules in the arbitrary locations inside the simulation box. The NPT ensembles, along with periodic boundary conditions, were utilized to carry out MD simulations. A cut-off of about 12 Å was used in order to manage the Vander Waals forces. The Particle Mesh Ewald model manifesting a cut-off of 14 Å was further utilized to calculate the electrostatic interactions (Darden et al., 1993). The spike protein, main protease and the two in complex with rutin were solvated through a slab of about 10 Å in every direction. The neighbor list was updated to a frequency of 10 ps.\nThe MD simulations were achieved for each system employing the four major steps. The first step deals with the energy minimization of the entire system utilizing the integrator of steepest descent in continuation with second integrator of conjugate gradients algorithms. The second step involves the minimization and molecular dynamics of NVT and NPT ensembles for 500 ps and 1000 ps, respectively allowing the solvents and ions to evolve by keeping the same starting configuration for the structures. In the third step the systems were heated using a lower temperature coupling (τ = 0.1 ps) along with pressure coupling (τ = 0.5 ps) to attain equilibrium at 300 K and 1 atm of temperature and pressure. In the equilibration phase, the thermostat and barostat were evaluated through the Berendsen algorithm (Berendsen et al., 1984). The hydrogen-containing bond lengths were constrained with the help of the LINCS algorithm (Hess et al., 1997). Finally, the last step also called as the production step was carried out, where the MD simulation for 100 ns at 300 K temperature with 2 fs of time step were performed for both systems, and the last final structures were achieved. The Maxwell Boltzmann distribution was utilized in order to reassign the velocities at every step. The Nose Hoover thermostat and Parrinello Rahman barostat were the respective thermostat and barostat for the final MD or production run (Berendsen et al., 1984).\nVarious analyses were performed with the help of inbuilt analysis commands of GROMACS. The root mean square deviation (RMSD) is a magnitude of the dimensional disparity among the two stagnant structures, and RMSD calculation is achieved depending upon the native structure and each consecutive trajectory frames in the simulation. In addition, root mean square fluctuation (RMSF) profile measures the affability of every protein residue depending on the fluctuation about an average location within all MD simulations (Knapp et al., 2011). Therefore, RMSD and RMSF of each simulation system were determined to examine the stability and residual fluctuations. Further, the radius of gyration (Rg) analysis was performed to evaluate the compactness of both the simulation systems separately. Also, the hydrogen bond analysis was performed to check the neighboring interactions with both simulation systems separately, including the hydrophobic interactions with the help of the LigPlot tool for both spike protein and main protease complexes with rutin before and after simulation.\nAdditionally, the solvent accessibility surface area (SASA) was also computed to examine the solvent attributable areas of all simulation system. The cluster analysis having a cut-off value of 0.25 and 0.2 nm for spike protein and main protease respectively, depending upon the RMSD profile were utilized to demonstrate the conformations found utmost intermittently throughout the trajectory. Here, all the structures having RMSD values of below 0.25 nm for all components within a cluster are incorporated to the initial cluster. It is rare that a molecule having a higher value for RMSD than 0.25 nm from other cluster supposedly would be treated as a structure. The secondary structure analysis was also performed using the DSSP program (Martin et al., 2005). The visualization of protein nature during the entire simulation was accomplished by using Visual Molecular Dynamics (VMD) (Humphrey et al., 1996) and UCSF Chimera (Pettersen et al., 2004)."}

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Molecular dynamics trajectory analysis of protein and their docked complex\nThe SARS-CoV-2 spike protein and main protease were used separately for molecular dynamics (MD) simulations alone and in complex with the repurposed drug, rutin. All the four MD simulations were executed through GROMACS v5.0 under the force field GROMOS96 54a7 having water model SPC216 along with the time step of 1 fs for 100 ns (Abraham et al., 2015; Darden et al., 1993). Varied sizes of the simulation box were created for each MD simulation event, which were further loaded with about respective amount of water molecules using the SPC model. The total charge on spike protein, main protease and the two in complex with rutin were neutralized by adding –6, –4, –6, and –4 charges, respectively, and were incorporated into the simulation system by compensating the water molecules in the arbitrary locations inside the simulation box. The NPT ensembles, along with periodic boundary conditions, were utilized to carry out MD simulations. A cut-off of about 12 Å was used in order to manage the Vander Waals forces. The Particle Mesh Ewald model manifesting a cut-off of 14 Å was further utilized to calculate the electrostatic interactions (Darden et al., 1993). The spike protein, main protease and the two in complex with rutin were solvated through a slab of about 10 Å in every direction. The neighbor list was updated to a frequency of 10 ps.\nThe MD simulations were achieved for each system employing the four major steps. The first step deals with the energy minimization of the entire system utilizing the integrator of steepest descent in continuation with second integrator of conjugate gradients algorithms. The second step involves the minimization and molecular dynamics of NVT and NPT ensembles for 500 ps and 1000 ps, respectively allowing the solvents and ions to evolve by keeping the same starting configuration for the structures. In the third step the systems were heated using a lower temperature coupling (τ = 0.1 ps) along with pressure coupling (τ = 0.5 ps) to attain equilibrium at 300 K and 1 atm of temperature and pressure. In the equilibration phase, the thermostat and barostat were evaluated through the Berendsen algorithm (Berendsen et al., 1984). The hydrogen-containing bond lengths were constrained with the help of the LINCS algorithm (Hess et al., 1997). Finally, the last step also called as the production step was carried out, where the MD simulation for 100 ns at 300 K temperature with 2 fs of time step were performed for both systems, and the last final structures were achieved. The Maxwell Boltzmann distribution was utilized in order to reassign the velocities at every step. The Nose Hoover thermostat and Parrinello Rahman barostat were the respective thermostat and barostat for the final MD or production run (Berendsen et al., 1984).\nVarious analyses were performed with the help of inbuilt analysis commands of GROMACS. The root mean square deviation (RMSD) is a magnitude of the dimensional disparity among the two stagnant structures, and RMSD calculation is achieved depending upon the native structure and each consecutive trajectory frames in the simulation. In addition, root mean square fluctuation (RMSF) profile measures the affability of every protein residue depending on the fluctuation about an average location within all MD simulations (Knapp et al., 2011). Therefore, RMSD and RMSF of each simulation system were determined to examine the stability and residual fluctuations. Further, the radius of gyration (Rg) analysis was performed to evaluate the compactness of both the simulation systems separately. Also, the hydrogen bond analysis was performed to check the neighboring interactions with both simulation systems separately, including the hydrophobic interactions with the help of the LigPlot tool for both spike protein and main protease complexes with rutin before and after simulation.\nAdditionally, the solvent accessibility surface area (SASA) was also computed to examine the solvent attributable areas of all simulation system. The cluster analysis having a cut-off value of 0.25 and 0.2 nm for spike protein and main protease respectively, depending upon the RMSD profile were utilized to demonstrate the conformations found utmost intermittently throughout the trajectory. Here, all the structures having RMSD values of below 0.25 nm for all components within a cluster are incorporated to the initial cluster. It is rare that a molecule having a higher value for RMSD than 0.25 nm from other cluster supposedly would be treated as a structure. The secondary structure analysis was also performed using the DSSP program (Martin et al., 2005). The visualization of protein nature during the entire simulation was accomplished by using Visual Molecular Dynamics (VMD) (Humphrey et al., 1996) and UCSF Chimera (Pettersen et al., 2004)."}