MMS DockBench CrossDocking - MMGBSA Method
ACEMD v3212M, AmberTools 2014, VMD 1.9.2
Molecular Dynamics (MD): timestep 4 fs, ForceField = AMBER14+GAFF, Temperature = 310, ionic concentration 0.1 M
MMGBSA calculations: igb=5
One pose for each ligand was selected as explained in PosePredictionProtocol; in particular complexes of FXR1 to FXR36 compounds were retrieved from the pool of newly unveiled crystallographic structures, while the others were obtained by docking simulations. The ligand-protein complexes were prepared for MD simulations by using AmberTool, assigning Gasteiger charges and GAFF parameters to the ligands and Amber14 partial charges and parameters to the proteins. The systems were solvated and Na+ Cl- ions were added to neutralize the charge and to reach a concentration of 0.1 M, by using VMD. The systems were subjected to 100 ps nve and 500 ps npt equilibration, applying harmonic positional constraints on protein and ligands heavy atoms. Three MD replicas of 2ns were performed for each complex, in which the MMGBSA was computed. The MMGBSA average value for each replica was obtained and finally the average value of the three replicas was used as ranking score for each ligand.
MMS DockBench CrossDocking - MMGBSA Method
Maestro 2016/OpenEye 1.9.2/DockBench 1.01 [1]/Autodock 4.2.5.1/Glide 6.5/GOLD 5.4.1/MOE 2015.1001/Plants 1.2/RDock 2013.1
Assumed pH 7.4
FXR1-FXR36 Ligands and relative proteins
Chains A were used among the co-crystal structures refined with tightened planarity restraints as provided by the organizators. The AA alternative was chosen for structures with double occupancy.
Ligands were protonated using obabel.
Proteins were prepared with the ProteinPreparation tool implemented in MOE, and protonated by the Protonate3D tool. Portions of the backbone that were not solved by the crystallographers were reconstructed by the Homology Modeling tool of MOE.
FXR37-FXR102 Ligands and relative proteins
Ligands were prepared using LigPrep Tool of Maestro, retaining specified chiralities and without tautomers generations. Strong acids were deprotonated and strong bases protonated using Wash tool of MOE. Ligands were minimized with MMFF94 force field.
Proteins were prepared by selecting chain A of crystallographic structures and by using Structure Preparation Tool of MOE. Protonation states were assigned with Protonate 3D tool of MOE.
DockBench Num_poses= 20
DockBench Radius= 20
DockBench proteins pdb (21 pdbs) = 3bej,3dct,3dcu,3fli,3fxv,3dg2,3hc5,3hc6,3oki,3olf,3omk,3omm,3oof,3ook,3p88,3p89,3rut,3ruu,3rvf,4qe6,4qe8
DockBench docking protocols= autodock-ga,autodock-lga,autodock-ls,glide-sp,gold-asp,gold-chemscore,gold-goldscore,gold-plp,moe-affinitydg,moe-gbviwsa,moe-londondg,plants-chemplp,plants-plp,plants-plp95,rdock-solv,rdock-std
Key parameters of the docking protocols are specified in DockBench manuscript [1].
CrossDocker [DockBench] = same as above
Crystallographic structures of FXR in complex with ligands FXR1 to FXR36 were used as provided by D3R Challenge organizators after Stage 1. For the remaining structures we applied the same protocol employed in Stage 1, as described below.
Crystallographic structures of FXR were retrived from the PDB and used for a docking benchmark. After protein superposition of the pdb complexes, the co-crystalized ligands of the pdb structures were grouped into clusters on the basis of their shape similarity. RDKit ShapeTanimotoDistance was computed among the ligands. The resulting distance matrix was analyzed with scikit-learn DBSCAN clustering algorithm, using a cutoff value of 0.45: 6 clusters were obtained (RESULTS-Clusters).
A cross docking benchmark was applied, in order to identify which was the "protein-docking protocol" couple that was able to better reproduce each co-crystalized conformation.
The evaluation of the docking protocols performances in reproducing the crystallographic ligand conformation was performed by computing the RMSD of the docking poses to the references. More in details, for each pdb structure, only the ligands that were members of the same cluster of the co-crystalized ligand were considered. Thus for each member of the cluster, the RMSD of the top five poses were computed, and their average was used as score.
In the cross docking approach the original ligand was excluded from the ligands subset considered in the calculation of the final RMSD. For this reason, for the ligands that were part of one member-only cluster, self-docking results were used.
In addition we computed another evaluation, defined here as "total-cross-docking", in which for the RMSD calculation, we considered all the ligands despite their cluster membership.
The best "protein-docking protocol" couple (winner) was identified as minimum RMSD average for each cluster (RESULTS-Clusters). Consequently ligands FXR37 to FXR102 were linked to each cluster on the basis of the ROCS TanimotoComboShapeSimilarity to the winner. A cutoff value of 0.8 for TanimotoComboShapeSimilarity was used to achieve the cluster population.
For each FXR ligand there were three possible results for the previous step:
1) ligand linked to a cluster
2) ligand linked to a one-member cluster
3) ligand orphan of a cluster
In case 1) the "protein-docking protocol" winner for the cluster was selected; in case 2) the self docking results were considered; in case 3) the best "protein-docking protocol" in "total-crossing-docking" was considered
For FXR37 to FX102 ligands the docking simulations were performed by using the "protein-docking protocol" suggested by our analysis (RESULTS-FX37to102). The top one pose for each ligand was selected for the submission.
RESULTS-Clusters
Cluster 1: 3RVF, 3DCT, 3HC6, 3RUU, 3RUT, 3FXV, 3GD2, 3HC5, 3P89, 3DCU, 3P88
Cluster 2: 4QE8
Cluster 3: 3FLI
Cluster 4: 4QE6
Cluster 5: 3BEJ
Cluster 6: 3OKI, 3OLF, 3OMK, 3OMM, 3OOF, 3OOK
RESULTS-Clusters
Protein Docking Protocol reference Result
Cluster 1: 3gd2 gold-plp (cross docking)
Cluster 2: 4qe8 plants-plp95 (self docking)
Cluster 3: 3fli rdock-solv (self docking)
Cluster 4: 4qe6 gold-goldscore (self docking)
Cluster 5: 3bej gold-asp (self docking)
Cluster 6: 3omk gold-plp (cross docking)
Outliers: 3gd2 gold-goldscore (total-cross-docking)
RESULTS-FX37to102
Ligand Protein Docking Protocol
FX37 3omk gold-plp
FX38 3gd2 gold-goldscore
FX39 3omk gold-plp
FX40 3omk gold-plp
FX41 3gd2 gold-goldscore
FX42 3omk gold-plp
FX43 3gd2 gold-goldscore
FX44 3gd2 gold-goldscore
FX45 3gd2 gold-goldscore
FX46 3omk gold-plp
FX47 3omk gold-plp
FX48 3omk gold-plp
FX49 3omk gold-plp
FX50 3omk gold-plp
FX51 3omk gold-plp
FX52 3omk gold-plp
FX53 3omk gold-plp
FX54 3omk gold-plp
FX55 3omk gold-plp
FX56 3omk gold-plp
FX57 3omk gold-plp
FX58 3omk gold-plp
FX59 3omk gold-plp
FX60 3omk gold-plp
FX61 3omk gold-plp
FX62 3omk gold-plp
FX63 3omk gold-plp
FX64 3omk gold-plp
FX65 3gd2 gold-plp
FX66 3omk gold-plp
FX67 3omk gold-plp
FX68 3omk gold-plp
FX69 3omk gold-plp
FX70 3omk gold-plp
FX71 3omk gold-plp
FX72 3omk gold-plp
FX73 3gd2 gold-goldscore
FX74 3gd2 gold-goldscore
FX75 3gd2 gold-goldscore
FX76 3gd2 gold-goldscore
FX77 3gd2 gold-goldscore
FX78 3gd2 gold-goldscore
FX79 3bej gold-asp
FX80 3gd2 gold-goldscore
FX81 3gd2 gold-goldscore
FX82 3gd2 gold-goldscore
FX83 3gd2 gold-goldscore
FX84 3gd2 gold-goldscore
FX85 3gd2 gold-goldscore
FX86 3gd2 gold-goldscore
FX87 3gd2 gold-goldscore
FX88 3gd2 gold-goldscore
FX89 3gd2 gold-goldscore
FX90 3gd2 gold-goldscore
FX91 3omk gold-plp
FX92 3bej gold-asp
FX93 3omk gold-plp
FX94 3bej gold-asp
FX95 3omk gold-plp
FX96 3omk gold-plp
FX97 3bej gold-asp
FX98 3omk gold-plp
FX99 3gd2 gold-goldscore
FX100 3omk gold-plp
FX101 4qe8 plants-plp95
FX102 3gd2 gold-goldscore
[1] Cuzzolin, A.; Sturlese, M.; Malvacio I.; Ciancetta, A.; Moro S. DockBench: An integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations. Molecules 2015, 20 (6), 9977-9993.