# Name for the protocol
Name: Maestro/Gold/Tscore

# All software packages used and their versions:
Software: Maestro Schrodinger Suite_2015-2/CCDC Gold Suite 2016

# List of key parameters used for system preparation
System Preparation Parameters: (prepwizard) -propka_pH # Use PH values listed in Data_set_fxr_crystallization_conditions.csv
System Preparation Parameters: (prepwizard) -fillsidechains -s # fillsidechains for target protein
System Preparation Parameters: (ligprep) -adjust_itc -ph # pH given in Data_set_fxr_crystallization_conditions.csv

# Plain-text description of system preparation method
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.

# List any number of key computational parameters in the following lines:
# Parameters used in Gold configuration file
Pose Prediction Parameters: autoscale = 0.2
Pose Prediction Parameters: floodfill_center = cavity_from_ligand 8 atoms 
Pose Prediction Parameters: gold_fitfunc_path = goldscore # use goldscore as scoring function to generate poses
Pose Prediction Parameters: num_poses = 500 # generate 500 poses as pose_pool for each complex

# Provide free text description of your method below. Use as many lines as you need.
Pose Prediction Method:
Use Gold to dock the ligand and target protein to generate 500 poses. After getting the pose_pool, use in house machine learning based score to rescore the pose_pool and choose 5 poses with minimum pairwise RMSD of 1.5 \AA as the candidates.
