Name

TML-BP/RI-Score/GOLD/AUTODOCK-VINA

Software

PQB2PQR, Javaplex, R-TDA, Scikit-learn

Parameters

NA

Method

Machine learning based method using the selected top poses.

Answer 1

No

Name

GOLD/AutoDock Vina/Schrodinger

Software

GOLD/AutoDock Vina/Schrodinger

System Preparation Parameters

(prepwizard) -propka_pH 7.5
(prepwizard) -fillsidechains -s # fillsidechains for target protein
(ligprep) -adjust_itc -ph

System Preparation Method

Maestro's prepwizard was used to optimize the protein with pH value and fillsidechains option.
Maestro's ligprep was used to generate optimized 3d structure of ligands from 2d structure. Sample ligand was manually filled into the binding pocket as the reference ligand. Position of the reference ligand was set as binding site.

Pose Prediction Parameters

autoscale = 1.5
floodfill_center = cavity_from_ligand 10 atoms
gold_fitfunc_path = plp # use plp as scoring function to generate poses
num_poses = 200 # generate 200 poses as pose_pool for each complex

Pose Prediction Method

Target ligands were docked to all CatS proteins available in RCSB and two protein structures provided by organizer.
Use consensus scores between plp scores (GOLD) and Vina scores (Autodock Vina) to select the best poses.

Answer 1

No

Answer 2

Yes