1146-1-cbd4c-PosePredictionProtocol.txt

Name

Omega/HYBRID/MM-GBSA

Software

Omega 3.0.8/HYBRID 3.2.0.2/MM-GBSA/amber16

System Preparation Parameters

Assumed pH 7.4
Tautomers considered only for BACE_5
AM1-BCC charges
0.1 M NaCl solution for MD simulations
Amberff99sb, TIP3P and Gaff for MD simulations

System Preparation Method

Ligand conformations for shape similarity search were generated using Omega in Openeye Toolkits. A maximum number of 100 conformations per ligand was gerenated. Ligand protonation state was generated at pH 4.5 using pKa Plugin from ChemAxon. Pdbfixer was used to remove the ligand and the water molecules and to add the missing heavy atoms to the pdb structures of the receptors. Then, PDB2PQR server (http://nbcr-222.ucsd.edu/pdb2pqr_2.0.0/) was used to correct the protonation states at pH 4.5 and to fix the residue/atom names following AMBER naming scheme. Parmed was used to convert the resulting pqr file to a pdb file. OpenEye toolkits were used to check bond-order and connectivities. For MM-GBSA calculations, the protein and ligand was solvated in TIP3P water with Amberff99sb force field and solvate in a cubic box wth 10 Angstrom padding.

Pose Prediction Parameters

50 docker poses in Hybrid
OESearchResolution_High 1.0
For tleap, set default PBRadii mbondi3
Amber parameter, dt=0.002,ntc=2,ntf=2,cut=8.0, ntb=2, ntp=1, taup=2.0, ntt=3, gamma_ln=2.0, temp0=300.0
For mmgbsa calculations using MMPBSA.py, igb=8, saltcon=0.100

Pose Prediction Method

RCSB database was searched for similar ligands and target protein structures were selected accordingly to dock the ligand. 50 poses per ligand were generated with a high docking resolution using HYBRID, followed by optimization. Then, the docked poses were visually inspected based on the similar/reference ligand from the pdb database and similar poses were selected for the next step. The selected poses were minimized and simulated for 15 ns using explicit solvent MD simulations in NPT ensemble and the MM-GBSA calculations were performed on the last 10 ns to estimated the binding free energy. Ligands were then selected based on their stability in the binding pocket and also the calculated binding energy.

Answer 1

Yes

Answer 2

Yes

1146-2-xb3zz-LigandScoringProtocol.txt

Name

Chimera/Omega/HYBRID/MM-PBSA

Software

Chimera, Omega 3.0.8/HYBRID 3.2.0.2/MM-PBSA/amber16

Parameters

50 docker poses in Hybrid
OESearchResolution_High 1.0

Method

We chose a reference ligand based on the closest structure from the 20 molecules for the pose prediction challenge and also macrocycles in the pdb database. We assumed that the copmounds are going to bind in a similar way to the reference ligand, and made the neccessary changes to the transform the reference ligand into the ligands in the scoring challenge using Chimera. If the changes were difficult like breaking macrocycle or non-aromatic rings, we uses combination of Omega/Hybrid and visual inspection to pick poses as we did in the pose prediction challenge. The protein-ligand structure was then minimized and simulated for 15 ns using explicit solvent MD simulations in NPT ensemble. In the final step, MM-PBSA calculations were performed on the last 10 ns to estimated the binding free energy. We are expecting this MM-PBSA scoring to do poorly.

Answer 1

Yes

Answer 2

No