mark mackey, cresset, 'meet molecular architect, a new product for understanding sar and...
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Meet Molecular Architect
Dr Mark MackeyChief Scientifc Officer
Outline
> Fields, Field points and the good things you can do with them
> The alignment problem
> 3D-QSAR using Fields
> Examples> SARS PLpro – small data set, known xtal structure
> NK3 – large data set, unknown xtal structure
NN
Br
F FF
SH2NO
O
Field Points
Condensed representation of electrostatic, hydrophobic and shape properties (“protein’s view”)
> Molecular Field Extrema (“Field Points”)
3D Molecular Electrostatic
Potential (MEP)
Field Points= Positive = Negative= Shape= Hydrophobic
2D
Field Points have lots of applications
> Virtual screening
> Alignment
> Pharmacophore elucidation
> Bioisosteres
> etc
Field Points have lots of applications
> Virtual screening
> Alignment
> Pharmacophore elucidation
> Bioisosteres
> etc
> What about 3D QSAR?
The Alignment Problem
> Historically very difficult
> Early approaches template-based> Issues with side chain orientations
> Some success with docked data sets
> Easy to fool yourself> Correlation/causation
Alignment issues
> Ligand-centric view vs protein-centric
Cramer, JCAMD, 2010, DOI 10.1007/s10822-010-9403-z
NN
Br
F FF
SH2NO
O
NN
Br
F FF
SH2NO
O
Which is better?
> “The superior statistical qualities of 3D-QSAR models based on poses that superimpose presumably critical ligand features, rather than docked conformations.” Clark R., JCAMD 2007, p587
Doweyko, J. Comp-Aided Mol. Des., 2004, p 587
Free alignment adds signal, but also noise. Worse statistics, better predictability?
N-methyl acetamideImidazole
Field Alignment
H3N
N
OO
HN
O
NH
NH2H2N
O
NH
NH
HN
SOO
N-methyl acetamideImidazole
Field Scoring
Cheeseright et al, J. Chem Inf. Mod., 2006, 665
To score a particular alignment, we use the field points of molecule 1 to sample the actual field of molecule 2
Field Scoring
N-methyl acetamideImidazole
Cheeseright et al, J. Chem Inf. Mod., 2006, 665
To score a particular alignment, we use the field points of molecule 1 to sample the actual field of molecule 2 and vice-versa
Field Sampling
Field-point based QSAR descriptors
Field Sampling
Field-point based QSAR descriptors
Advantages
> Many fewer sample points than grid-based methods
> E.g. Vegfr2 data set
Field Sampling Grid Sampling Filtered Grid Sampling
q2 0.62 0.42 (0.48) 0.40
Number of descriptors
466 3940 1243
Du et al., J Mol Graph Model. 27 (2009) 642-652
Advantages
> Many fewer sample points than grid-based methods
> Sample points physically rather than statistically chosen
> Gauge invariant
> Consistent framework for alignment and QSAR
Initial validation
> Tested against literature CoMFA datasets> 15 datasets with alignments available
> CoMFA average cross-validated RMSE is 0.72
> Field QSAR using CoMFA alignments is 0.74
> Simple model (volume indicator variable) is 0.83
> Data sets re-aligned using field alignment> RMSE 1.00
Interpretability
Electrostatic Steric Variance
SARS PLpro
The target
> PLpro (Papain-like protease) is a DUB target which is critical for the replication of the coronavirus responsible for SARS
> Crystal structures available with bound ligands from 2 series of compounds: structurally related (PDB entries 3E9S and 3MJ5)
> Small number of analogues – challenge to see if we can use 3D-QSAR for small data sets
Alignment
Sampling points
Model
3.50 4.00 4.50 5.00 5.50 6.00 6.50 7.003.50
4.00
4.50
5.00
5.50
6.00
6.50
7.00
R² = 0.838410392100944
R² = 0.987121600034644Training SetLinear (Training Set)Test SetLinear (Test Set)
PLS Components = 5 RMSE = 0.09 RMSEP = 0.38
Summary
> Able to build a predictive 3D-QSAR model based on small number of analogues
> Guided (by volume of Xtal structure) alignment worked best. Free alignment was OK, but noisier.
NK3 antagonists
NK3 example
> GPCR target (Tachykinin receptor 3) – selectively binds Neurokinin B – target for treatment of neurological disorders such as schizophrenia
> Three series of inhibitors from Euroscreen> Scaffold-1 – 81 compounds with pIC50 (radioligand
binding) in range 4.6-8.7
> Scaffold-2 – 80 compounds with pIC50 in range 4.8-7.7
> Errors in radioligand binding data c. ± 0.4
NK3 binding mode
> For a 3D method you need a 3D alignment
> FieldAlign can align to a reference
> FieldTemplater generates the reference
O
N+
NH
N
HO
O
O
OHO
H
N
N+
N
O
N
N
O
H
F
F F
F
F
O
HN N+
H
H
N N
NH
FieldTemplater
NK3 binding mode prediction
> FieldTemplater> Selection of 3 highly active scaffold-1 compounds
plus 2 structurally dissimilar literature NK3 actives (Talnetant and SB-218795).
> Generated Templates filtered and candidate selected
> Conformation of most active scaff-1 structure then used as alignment target for other structures
3D-QSAR details
> Alignment> Free alignment to template conformation
> Field selection> Generated Field points for both steric and electrostatic
fields, with both sets at independent locations.
> 80/20 training/test split > Most active and least active training set
> 2nd most active, 2nd least active test set
> Random distribution of remaining compounds
Initial models problematic
> When all else fails, talk to the chemists
> “Are you using the right tautomer?”
N N
N
N
H
N N
N
N
NK3 Series 1
RMSE 0.19, RMSEpred 0.64
4.5 5 5.5 6 6.5 7 7.5 8 8.5 94.5
5
5.5
6
6.5
7
7.5
8
8.5
9
Training Set
Test Set
NK3 Series 1
Electrostatics Sterics
Extend to scaff-2?
4 5 6 7 8 9 10 114
5
6
7
8
9
10
11
Actual vs Predicted - scaff2 compounds on scaff1 model
> Complete lack of predictivity
> Visual analysis suggests a shift in binding mode for scaff-2
> Cross-series QSAR difficult
> Requires consistent binding modes!
NK1 Scaffold 2
4 4.5 5 5.5 6 6.5 7 7.5 8 8.54
4.5
5
5.5
6
6.5
7
7.5
8
8.5
TrainingTest
Activity
Pred
icted
Acti
vity
RMSEpred 0.60
Summary
> Able to generate models based on alignment to predicted active conformation by templating
> Independent models within each of two series show reasonable predictivity and can be used to guide further work
> Cross-series analysis suggests different binding modes for the two series
Molecular Architect
Molecular Architect
> Initially FieldAlign + QSAR
> Align your molecules
> Build models
> Test models
> Fit new compounds to models
> Interactive feedback
> Add additional alignment options
Molecular Architect
> One tool for molecule designers> Align
> QSAR
> Pharmacophore elucidation
> Bioisosteres
> What do I make next?
> Beta Q4 2011
Acknowledgements
> Cresset> Andy Vinter
> Tim Cheeseright
> James Melville
> Chris Earnshaw
> Euroscreen> Hamid Hoveyda
> Julien Parcq
