d3r grand challenge 2 · 2017. 3. 30. · desaphy et al., encoding protein-ligand interaction...
TRANSCRIPT
Docking Pose Selection by Interaction Pattern Similarity
D3R Grand Challenge 2
Dr. Didier RognanStructural Chemogenomics – Laboratory of Therapeutic InnovationFaculty of Pharmacy - University of Strasbourg - Francehttp://bioinfo-pharma.u-strasbg.fr
Dr. Priscila FigueiredoPost-doc , CAPES Biocomputational – University of Rio de Janeiro - Brazil
OUTLINE
Structure selection
Protein & ligands preparation1
Docking and re-scoring protocol
Pose Prediction accuracy
Failures
2
3
4What have we learned from the challenge?
Advantages of the method
2
System setup
Templateselection
• 26 FXR x-ray structures (ligand-bound) available and extracted from the PDB;
Proteinpreparation
• Hydrogens added using PROTOSS v2.0 (Bietz et al. J. Cheminform. 2014, 6, 12);• Protonation of the active site residues verified;• Ligand and loosely-bound water ( < 2 intermolecular H-bonds) removed;
FXR ligands preparation
• 3D coordinates generated using CORINA (MOLECULAR NETWORKS GMBH);
• Protonation state assigned using FILTER (OPENEYE) and verified.
3
1OSH 1OSV 1OT7(A) 1OT7(B) 3BEJ 4QE6
3DCT 3DCU 3FLI 3FXV 3GD2
3HC5 3HC6 3L1B 3OKH 3OKI
3OLF 3OMK 3OMM 3OOF 3OOK
3P88 3P89 3RUT 3RUU 3RVF
Docking protocol
FXR_1
FXR_102
…
102 FXR ligands
Surflex-Dock
102 x 26 x 20 = 53 040 poses
• Residue-based protomol• 6.5 Å around bound ligands
• pgeom option
• 20 poses/ligand
x 26 x-ray templates
Jain, J. Med. Chem., 2003, 46, 499-511.
4
Scoring: Interaction pattern matching (GRIM)
Protein-Ligand Complex Interactions pseudoatoms (IPAs)
Graph-based alignment of IPAs
Alignment quantification by GRIMscore
GRIMscore = K + a*NLig + b*NCenter + c*NProt
+ d*SumCl –e*RMSD – g*DiffI
NLig: number of matched ligand-based IPAs
Ncent: number of matched centered IPAs
NProt: number of matched protein-based IPAs
SumCl:σ pair weights in clique
σ all possible pair weights
RMSD: root-mean square deviation of the matched clique
DiffI: absolute value of the difference in the number of IPAs between reference and query.3ert vs. 2r6y (GRIMScore = 0.804)
Desaphy et al. J. Chem. Inf. Model, 2013, 53, 623-633.
5
GRIM Pairwise comparisons
(~53000 * 26)
Pose rescoring using GRIM
53 040 poses
26 FXR-ligand templates (PDB)
FINAL POSES
FXR-1-1
…
FXR_36-5
Surflex score > 2 (-logKd)
5 best GRIMscoresfor each ligand
1OSH
. . .
4QE6
6
Pose prediction accuracy (35 ligands, FXR_1:FXR_36)
FXR_33 omitted
3.67 3.11 4.04 1.57
GRIM-1 GRIM-best Surflex-1 Best
Ave
rage
RM
SD(Å
)
No real docking problemAverage best pose: 1.57 Å
Real scoring problemGRIMscore > Surflex score
Highest GRIMscore Best of top5 GRIMscores Highest Surflex-Dock score Absolute Best rmsd7
Pose prediction accuracy (35 ligands, FXR_1:FXR_36)
FXR_33 omitted
0
2
4
6
8
10
12
14FX
R_1
FXR
_2FX
R_3
FXR
_4FX
R_5
FXR
_6_
AA
FXR
_6_
AB
FXR
_7_A
AFX
R_7
_A
BFX
R_8
FXR
_9FX
R_1
0FX
R_1
1FX
R_1
2_A
AFX
R_1
2_A
BFX
R_1
3FX
R_1
4_A
AFX
R_1
4_A
BFX
R_1
5FX
R_1
6FX
R_1
7FX
R_1
8FX
R_1
9FX
R_2
0FX
R_2
1FX
R_2
2FX
R_2
3FX
R_2
4FX
R_2
5FX
R_2
6FX
R_2
7FX
R_2
8FX
R_2
9FX
R_3
0FX
R_3
1FX
R_3
2FX
R_3
4FX
R_3
5FX
R_3
6
RM
SD (
Å)
GRIM-1 GRIM-best Surflex-1 Best
Correctly posed (< 2 Å): n=20 (benzimidazoles)Incorrectly posed (> 2 Å): n=15
8
0
2
4
6
8
10
0.7 0.8 0.9 1.0 1.1 1.2
RM
SD (
Å)
GRIMscore
Pose prediction accuracy (35 ligands, FXR_1:FXR_36)
FXR_33 omitted
0
2
4
6
8
10
0.2 0.4 0.6 0.8 1.0
RM
SD (
Å)
Chemical Similarity to Reference Ligand
GRIM-1 poses
Good pose when the reference ligand ischemically similar to the ligand to dock
Tc (MACCS keys)
Very high GRIMscores correspond to good posesNo strict correlation between GRIMscore and rmsd
9
Pose prediction accuracy (35 ligands, FXR_1:FXR_36)
0
2
4
6
8
10
0 5 10 15
RM
SD (
Å)
Npolar
Npolar: number of matched polar interactions(H-bonds, ionic bonds)
Repeated failures when onlyapolar interactions are matched(High GRIMscore, Npolar = 0 or 1)
Good poses when the matched interaction pattern becomes more polar(High GRIMscore, Npolar ≥3)
FXR_33 omitted
10
Reasons for failure
➢ Lack of polar interactions (high GRIMscore, Npol=0) FXR_4,8,10,12,15,16,18
➢ Low chemical similarity to any known co-crystallized FXR ligand (Tc <0.5): FXR_4,10,16,34
➢ Docking problem (rmsd >3Å): FXR_1,FXR_3
➢ Different binding mode: FXR_2
X-rayrefGRIMPredicted
rmsd: 5.15 ÅGRIMscore: 0.99Tc: 0.76
rmsd: 6.97ÅGRIMscore: 0.78Tc: 0.6
FXR_2
FXR_8
11
0
2
4
6
8
10
12
RM
SD (
Å)
receiptID
Mean RMSD of Top Scoring Poses
GRIM rescoring vs other contributions
Incomplete predictions
GRIM
GRIM rescoring: 14th/46 complete predictions
12
Ranking the ligands by affinity using HYDEStage-1
Sample slides available at: https://www.biosolveit.de/SeeSAR/science.html
13
Results: ranking of the 102 FXR ligands
0.44
Best GRIMscore poseHYDE ranking
3rd/57 predictions
14
What have we learned?
Pose predictionGRIM helps to rescue badly scored poses
GRIM rescoring relies on the availability of good templates (known binding modes)
Importance of polar interactions to generate a correct alignment
Structure-based scoringPose selection by GRIM and affinity ranking by HYDE is an efficient strategy
Protocol is fast enough (seconds) to be applicable at a higher throughput (VS hit list)
15
Advantages of using GRIM
Can be coupled to any docking algorithm to post-process poses;
Take advantage of ligands with similar binding mode, not necessarily similar chemical
structures;
Can be applied in a target family-biased docking strategy
Module of the IChem toolkit (http://bioinfo-pharma.u-strasbg.fr/labwebsite/download.html)
Desaphy et al., Encoding protein-ligand interaction patterns in fingerprints and graphs. J. Chem. Inf. Model, (2013), 53:623-637
Slynko et al., Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015. J Comput
Aided Mol Des (2016), 30:669-683 16
Acknowledgments
Dr. Didier Rognan
Contact: [email protected]
Guillaume Bret Dr. Franck da Silva
[email protected]. Priscila Figueiredo