Ts of depressionIngredients of CCHPdepressionNetwork construction herb-compound-target network of CCHP protein-protein
Ts of depressionIngredients of CCHPdepressionNetwork construction herb-compound-target network of CCHP protein-protein interaction network of CCHP in treating depression herb-compound-target network Network evaluation GO and KEGG enrichment evaluation KEGG enrichment evaluation GO enrichment analysis Target-Pathway network analysis Target-Pathway network analysis Molecular docking protein-protein interaction network Intersection of targets of depression and CCHPcore compoundsMolecular docking of core compounds and core targets Docking models of core compounds and core targetscore targets Molecular dynamics simulations0.6 0.5 RMSD (nm) 0.4 0.3 0.two 0.1 0 10 0.228.027 20 30 Time (ns) 40 50 0.194.Molecular dynamics simulationsMolecular Mechanics-Poisson Boltzmann Surface Area6hhi_G4N 6hhi_QuercetinBinding totally free energyRMSDFigure 1: Workflow for the network pharmacology-based study of CCHP in treating depression.ChemBio 3D Software to export the 3D structures. AutoDockTools 1.five.6 Computer software was then employed to add charge values and export the structures in pdbqt format. Second, the 3D structures with the core targets were acquired in the RCSB PDB database (rcsb/) [35] and deleted water and other ligands. AutoDockTools 1.five.6 was utilised to add hydrogen and β adrenergic receptor Inhibitor Gene ID charges and convert the structures into pdbqt format. Finally, AutoDock Vina 1.1.2 was utilized to perform molecular docking and analyze the results [36]. Docking outcomes have been visualized and analyzed utilizing PyMOL 1.7.two.1 and Ligplus two.two.four. e docking of core compounds and targets with lower docking energies had stronger binding forces. 2.ten. Molecular Dynamics Simulations. Considering that AKT1 (PDB ID: 6hhi) was the core target and quercetin was the core compound, the docking conformation of 6hhi andquercetin, which had low binding power, was selected as the initial conformation for molecular dynamics (MD) simulations. G4N, the primitive ligand of 6hhi, was utilised because the good handle. MD simulations have been performed applying the GROMACS 2018.four plan [37] below continuous temperature and pressure and periodic boundary circumstances. Amber99 SB all-atom force field and TIP3P water model were applied [38]. During MD simulations, all bonds involving hydrogen atoms were constrained applying the LINear Constraint Solver (LINCS) algorithm [39] with an integration step of 2 fs. Electrostatic NF-κB Inhibitor review interactions were calculated making use of the particle mesh Ewald (PME) strategy [40]. e nonbonded interaction cutoff was set to ten A and updated each ten steps. e V-rescale temperature coupling method [41] was applied to manage the simulation temperature at 300 K, as well as the Parrinello ahman system [42] was employed to manage the stress at 1 bar.four Initial, power minimization was performed in the two systems using 5000 measures of steepest descent algorithm together with the convergence of energy minimization of one hundred kJ/mol/nm to do away with excessive interatomic make contact with. en, the systems have been heated gradually from 0 to 300 K inside the canonical ensemble (NVT) and equilibrated at 300 K for 1000 ps in the continuous pressure-constant temperature ensemble (NPT). Lastly, the systems have been subjected to MD simulations for 50 ns as well as the conformation was preserved just about every ten ps. e simulation benefits have been visualized working with the GROMACS embedding program and visual molecular dynamics (VMD). 2.11. Calculation of Binding Cost-free Power. e molecular mechanics Poisson oltzmann surface location (MMPBSA) method [43] was employed to calculate the binding energy involving substrate compact molecules and proteins i.
