Ligand_shape_similarity_vina_docking
AutoDock Vina 1.1.2/RDKit 2018.03.1/Openbabel/Pymol/fkcombu/ACPYPE/Gromacs 5.1.5
Default parameters used for most programs.
3D structure of target compounds was generated using RDKit from smiles.
Hydrogen was added and conformation was generated with ETKDG method in RDKit.
Openbabel was used to assign charges and atomtypes to ligand as PDBQT files.
MGLTools was used to generate PDBQT files for receptor protein.
Vina docking generated 10 poses, with flexible residues within 5 angstrom of the ligand.
The ligand force field parameters for gromacs was generated by ACPYPE with bcc charge method.
Vina scoring funtion (empirical + knowledge-based function)
Publically available structures of Beta-secretase 1 from pdb database was obtained.
The ligands were extracted and compared with target compound using Maximum Common Substructure method in RKDit.
The most similar ligand and its corresponding protein structure A was used as template.
The 20 target compounds were flexibly aligned and superimposed by fkcombu software with the most similar ligand as template.
The target compound was docked into protein A using AutoDock Vina with flexible residues within 5 angstrom of the ligand.
At most 10 poses were generated. The best pose was manually picked.
The protein-ligand complex was energy-minimized using Gromacs.
Yes
Dock_MMPBSA
AutoDock Vina 1.1.2/RDKit 2018.03.1/Openbabel/Pymol/fkcombu/ACPYPE/Gromacs 5.1.5/g_mmpbsa
default for most programs
The target compounds for affinity ranking were docked into protein which has the most similar ligand, as described in pose prediction protocol.
Protein-ligand complex was energy minimized in Gromacs, followed by 50 ps of NVT and 100 ps of NPT simulations.
Then a 2 ns simulation was performed and 100 frames of complex structure between 1 ns to 2 ns were extracted and binding free energy was calculated using g_mmpbsa.
Yes
No