ICM/APF 3D QSAR + MMGBSA
Molsoft ICM 3.8-5
default
3D QSAR model was trained on the available FXR activity data in ChEMBL database. Training set was assembled using only ligands within 0.2 Tanimoto distance from any of the 102 query compounds. Resulting training set consisted of 115 ligands. Training set ligands were docked to a set of FXR pockets as desribed in PosePredictionProtocol.txt. Atomic Property Fields (APF) approach was used to create the 3D QSAR model based on the docked poses and activities of the training set ligands and perform prediction using poses of 102 query compounds generated as desribed in PosePredictionProtocol.txt
Independently, MM/GBSA type score was trained on the same ChEMBL-derived data by PLS regression on three terms: van der Waals interaction, buried hydrophobic surface and generalized Born solvation electrostatics. Predictions were performed for 102 query compounds on the same poses as for 3D QSAR.
Final predicted pKd was calculated as the highest of the two models (i.e. model predicting stronger binding was chosen for each compound as a final predictor).
ICM Dock
Molsoft ICM 3.8-5
default
Standard ICM conversion procedure was used to add hydrogens, assign atom types and charges
All the waters were removed.
Monte Carlo search 'effort' parameter was set to 10.
Docking runs were executed with the above specified parameters while default values
were applied for the rest of the variables. Each ligand was docked to a set of receptor conformations from X-ray structures in PDB and structures released by D3R after Stage 1.
Only poses with APF (Atomic Property Fields) similarity >0.4 to the cognate ligand of the corresponding receptor conformation were retained.
The top 5 poses according to ICM VLS score were further analysed: poses were re-ranked according to composite ICM-VLS/APF score (the product of physics-based ICM VLS Score and APF similarity to the cognate ligand of the respective receptor conformation). Poses were also clustered across the compound set to identify consensus poses for each chemotype (when applicable). In a few cases where best-scoring pose disagreed with the chemotype consensus, the pose in agreement with the chemotype was selected instead.