Ts of depressionIngredients of CCHPdepressionNetwork construction herb-compound-target network of CCHP protein-protein
Ts of depressionIngredients of CCHPdepressionNetwork building 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 analysis GO enrichment analysis Target-Pathway network evaluation Target-Pathway network evaluation 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.five RMSD (nm) 0.four 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 free of charge energyRMSDFigure 1: Workflow for the network pharmacology-based study of CCHP in treating depression.ChemBio 3D Software program to export the 3D structures. AutoDockTools 1.5.6 Software was then employed to add charge values and export the structures in pdbqt format. Second, the 3D structures from the core targets had been acquired in the RCSB PDB database (rcsb/) [35] and deleted water and other ligands. AutoDockTools 1.5.six was employed to add Tyk2 Inhibitor manufacturer hydrogen and charges and convert the structures into pdbqt format. Lastly, AutoDock Vina 1.1.2 was utilized to execute molecular docking and analyze the results [36]. Docking benefits have been visualized and analyzed making use of PyMOL 1.7.2.1 and Ligplus two.2.4. e docking of core compounds and targets with reduced docking energies had stronger binding forces. two.10. Molecular Dynamics Simulations. Given that AKT1 (PDB ID: 6hhi) was the core target and quercetin was the core compound, the docking PKCĪ¶ Inhibitor Compound conformation of 6hhi andquercetin, which had low binding energy, was selected because the initial conformation for molecular dynamics (MD) simulations. G4N, the primitive ligand of 6hhi, was made use of as the optimistic control. MD simulations had been performed using the GROMACS 2018.4 plan [37] below continuous temperature and pressure and periodic boundary circumstances. Amber99 SB all-atom force field and TIP3P water model had been applied [38]. During MD simulations, all bonds involving hydrogen atoms have been constrained applying the LINear Constraint Solver (LINCS) algorithm [39] with an integration step of 2 fs. Electrostatic interactions have been calculated using the particle mesh Ewald (PME) approach [40]. e nonbonded interaction cutoff was set to ten A and updated just about every ten steps. e V-rescale temperature coupling strategy [41] was utilized to handle the simulation temperature at 300 K, and the Parrinello ahman system [42] was applied to control the pressure at 1 bar.4 1st, power minimization was performed inside the two systems employing 5000 measures of steepest descent algorithm using the convergence of energy minimization of 100 kJ/mol/nm to eliminate excessive interatomic make contact with. en, the systems were heated steadily from 0 to 300 K within the canonical ensemble (NVT) and equilibrated at 300 K for 1000 ps inside the continuous pressure-constant temperature ensemble (NPT). Finally, the systems had been subjected to MD simulations for 50 ns and the conformation was preserved just about every ten ps. e simulation final results have been visualized working with the GROMACS embedding plan and visual molecular dynamics (VMD). two.11. Calculation of Binding Free Power. e molecular mechanics Poisson oltzmann surface location (MMPBSA) approach [43] was utilized to calculate the binding power between substrate tiny molecules and proteins i.
