www.ccdc.cam.ac.u k Insight into Molecular Geometry and Interactions using Small Molecule Crystallographic Data John Liebeschuetz Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge, UK [email protected]
Www.ccdc.cam.ac.uk Insight into Molecular Geometry and Interactions using Small Molecule Crystallographic Data John Liebeschuetz Cambridge Crystallographic.
Dec 17, 2015
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www.ccdc.cam.ac.uk
Insight into Molecular Geometry and
Interactions using Small Molecule
Crystallographic Data
John LiebeschuetzCambridge Crystallographic Data Centre,
12 Union Road, Cambridge, UK
www.ccdc.cam.ac.uk
How much Data is Available?
CSD Growth 1970-2006
419,768 entries June 2007
0
100000
200000
300000
400000
500000
600000
2001 2003 2005 2007 2009
Growth of the Cambridge Structural Database over 40 years
Predicted Growthto 2010
>500,000 entries during 2009
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CSD Data Content
Literature Reference:
G. Bringmann, M. Ochse,
K. Wolf, J. Kraus, K. Peters,
E-M. Peters, M. Herderich,
L. Ake, F. Tayman
Phytochemistry 51,1999, 271
Other text:R-factor: .0506
Colour: pale yellow
Habit: acicular
Polymorph: Form IV
Source: Rothmannia longiflora
4-Oxonicotinamide-1-(1’-beta-D-2’,3’,5’-tri-O-acetyl-
ribofuranoside)
C17 H20 N2 O9
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Molecular Interactions as well as Geometry
HEPPEX
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Cambridge Structural Database System
CambridgeStructuralDatabase
PreQuestDatabase Production
VISTAStatisticalanalysis
MercuryGraphical display,packing analysis
ConQuestDatabase
Search
MogulLibrary of
Molecular Geometry
IsoStarLibrary of
Intermolecular Interactions
Knowledge Bases
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Using Structural Data in molecular modelling for pharmaceutical design
• Intramolecular – 3D geometry– Designing in the desired Conformer
– Validation that models have correct geometry
• Intermolecular – Interactions between molecules– Design of pharmacophores
– Validation of interactions found during modelling
– Identification of new ways to satisfy binding motifs
– Knowledge-based scoring functions for docking
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Designing in the right Conformation (1)
Brameld. K.A., Kuhn, B., Reuter, D.C. and Stahl, M. J. Chem. Inf. Mod, 48(1), 1-24 2008)
It is possible using Conquest to generate incidence histograms for any geometric feature , for any substructure, if sufficient high quality structures including that substructure, are present in the CSD
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Designing in the right Conformation (2)
Sulphonamide is common in drug molecules. Its conformational behaviour well captured by CSD
Ortho Substitution (Blue histogram) shifts the maximum
Pyramidalisation of the N of the sulphonamide can also be explored. This is a common effect in sulphonamides (and piperidines) but is poorly reproduced by modelling software
Brameld. K.A., Kuhn, B., Reuter, D.C. and Stahl, M. J. Chem. Inf. Mod, 48(1), 1-24 2008)
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Designing in the right Conformation (3) : Example 1:
CSD analysis indicates the bioactive conformation is stable only for most active structureBrameld. K.A., Kuhn, B., Reuter, D.C. and Stahl, M. J. Chem. Inf. Mod, 48(1), 1-24 2008)
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Rapid access of geometric information from the CSD
Incorporates pre-computed libraries of bond lengths, valence angles and torsion angles
>20 million individual geometrical parameters derived entirely from the CSD and updated annually
Sketch or import molecule, then click on feature of interest to view distribution, mean values and statistics
Validation of Model Geometry: Mogul
Bruno et al., J. Chem. Inf. Comput. Sci., 44, 2133-2144, 2004
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Select fragment
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Validation of PDB Ligand Geometry
PDB structures suffer from less well defined electron density
Protein X-Ray refinement force fields often are poorly parameterised to reproduce ligand geometries
Sometimes protein crystallographers start with a poor ligand model
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Validation of Ligand structures in the PDB via Protein/Ligand analysis tool Relibase+*
*www.ccdc.cam.ac.uk
Validation of ligand structures found in the PDB
Ligand from 1HAK, Two abnormal torsions indicated
Further examination reveals the piperidine to be Boat form
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• 15% of 100 recent PDB entries have ligand geometry that are almost certainly in significant error (in house analysis using Relibase+/Mogul)
• The good news - For structures deposited before 2000 the figure is 26%
evaluation of pdb ligand dataset from 1990's with Mogul and Relibase
correct34%
wrong26%
not unusual40% correct
wrong
not unusual
evaluation of most recent pdb ligand dataset with Mogul and Relibase
correct29%
wrong16%
not unusual55%
correct
wrong
notunusual
Pre 2000 2006
Validation of ligand structures found in the PDB using Mogul
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Designing in the right Conformation (3) : Large Rings
Brameld. K.A., Kuhn, B., Reuter, D.C. and Stahl, M. J. Chem. Inf. Mod, 48(1), 1-24 2008)
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Validation of ligand structures found in the PDB
Ligand from 1HAK, Two abnormal torsions indicated
Further examination reveals the piperidine to be Boat form
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Mogul 1.3: Ring Conformations
• Mogul currently holds data on bonds, angles and torsions.
• In the 2010 release of the Cambridge Structural Database System Mogul will also contain a comprehensive ring knowledge base
• Ring libraries from α-Mogul 1.3 have been introduced into Gold 4.1 to allow knowledge- based ring-flexing during docking
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A Knowledge Base of Intermolecular Interactions
Experimental data from:
Cambridge Structural Database
Protein Data Bank (protein-ligand complexes only)
Theoretical potential energy minima (DMA, IMPT)
Typical Uses:
Probability of an interaction occurring
Preferred geometries
Design Strategies
IsoStar
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central group: -CONH2
contact group: NH
IsoStar Methodology
Search CSD or PDB for structures containing contact
Superimpose hits and display distribution
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IsoStar Scatterplots vs. Density MapsN-H donors around amide C=O
Scatterplot Contour surface
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IsoStar –indole and isoxazole interactions with faces of phenyl rings
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Using Intermolecular information to build pharmacophores from proteins
Use intermolecular information (IsoStar) to map a protein binding site (e.g. using SuperStar, an extra module to the CSDS )
Create a pharmacophore from this information (possible in SuperStar) c.f. GRID/FLAP
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Motif searching
Certain signature interaction motifs might be key to identifying inhibitor substructures of interest. Can we identify such motifs in the CSD and thereby uncover new ideas?
Materials Mercury: A new tool for the drug development and crystal design community
Most tools are specific to small molecule crystals ....
However ….
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1. Comparison of crystal structures: polymorphs, solvates etc can identify significant ‘packing features’.
2. We can then search the CSD using ‘Packing Feature Search’
Packing Feature Search
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H-bonding Motif Search: Kinase Binding Motifs
CDK2 Complex – 1ke8 Set up a ‘Packing Feature Search’ around Hinge Region
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H-bonding Motif Search: Kinase Binding Motifs
MISTOX WUSQAC
Provides ideas for new motifs – Fragment based design
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• Protein/Ligand Docking relies on a scoring function to rank binding poses
– Scoring functions may be Molecular Mechanics based, Empirical or Knowledge Based
• A Knowledge Based score is calculated by the sum of atom-atom potentials derived from a crystallographic database
The atom-atom potential = - log
• Knowledge based scoring functions (PMF, Bleep, DrugScore, ASP) have been developed using protein-ligand data (PDB)
• The CSD contains better resolved structures and a much greater variety of chemical functionality than the PDB
– DrugScoreCSD has demonstrably improved performance over DrugScore (Velec, Gohlke & Klebe, J. Med. Chem., 48 (2005), 6296 )
observed interactions
Knowledge-based scoring using small molecule structural data
reference state
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Uses of Small Molecule Structural Data in Drug Design: Conclusions
• Use in Model Validation -
– Geometry of designed synthetic candidates
– Geometry of X-ray derived Ligand Structures
– Intermolecular interactions of a candidate structure with a model of binding site
• Design of Pharmacophores
• Search for fragments fitting a binding motif
• Creation of robust and versatile Knowledge-Based scoring functions for docking
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Acknowledgements
Thank you for your attention
Jana HennemanJames Chisholm
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