![Position [°2Theta]
5 10 15 20 25 30
XRPD from bulk
simulated from
known structure
crystallisation from nitromethane
XRPD seems to show pure form
Theophylline
Polymorph screening and characterisation
thermodynamically
stable polymorph
with
Mark Eddleston, Bill Jones
Cambridge](https://image.slidesharecdn.com/gmdayiucr2014kn23-140810170114-phpapp01/85/Insight-from-energy-surfaces-structure-prediction-by-lattice-energy-exploration-12-320.jpg)
![CN1[C@H]2CC[C@@H]1[C@H]([C@H](C2)OC(=O)C3=CC=CC=C3)C(=O)OC
ensemble of conformers & associated energies
Some technical details
Chemical diagram converted to a SMILE, from which an
unbiased 3D structure is generated
Conformer searches
“Low-mode” search for all conformers
Initially force field based (OPLS-AA-2005)
Resulting structures re-optimised: B3LYP/6-31G(d,p) + dispersion correction
(CRYSTAL09)
Chem. Sci. (2014), 5, 3173-3182](https://image.slidesharecdn.com/gmdayiucr2014kn23-140810170114-phpapp01/85/Insight-from-energy-surfaces-structure-prediction-by-lattice-energy-exploration-26-320.jpg)
Insight from energy surfaces: structure prediction by lattice energy exploration
- 1. Insight from energy surfaces: structure prediction by lattice energy exploration IUCr Congress, Montreal August 2014 Graeme M. Day Chemistry, University of Southampton, UK www.crystalstructureprediction.net
- 2. Structure prediction of molecular crystals lattice energy approach applications challenges 12 August (Tuesday) MS104 Crystal Structure Prediction and Materials Design MS112 New Approaches to Crystal Structure Prediction
- 3. Crystal structure prediction (CSP) objectives Why might CSP be useful? • Anticipation of polymorphs • Structure solution • Design of structure → properties • We want to be able to reliably predict what is possible for a given molecule (or combination of molecules, for multi-component systems). • This is not just about predicting one structure, but a landscape of the energetically feasible possibilities. • Providing tools to help anticipate, characterise and design structures.
- 4. So, we’re writing programs to solve puzzles? This is what I tell non-scientists that I do.
- 5. Poorly fitting pieces → many solutions
- 6. Chemical information C H O N F
- 7. Balance of interactions C H O N F The energetically optimal solution is a balance of contributions to intermolecular interactions: • Repulsion: U ~ + exp(-aR) • Dispersion: U ~ - R-6 • Electrostatics: U ~ ± R-1 sterics & close packing strong, specific interactions, & important to long distances
- 8. structural parameters energy structural parameters optimisationenergy 1) Sample the lattice energy surface Algorithms we use: • Monte Carlo • quasi- or pseudo-random • simulated annealing • basin hopping also in use: systematic searches; grid-based search; genetic algorithms; metadynamics … 2) Lattice energy minimise • Interatomic potentials • anisotropic atomic models • Electronic structure methods 3) Remove duplicates (which we should have) 4) Analyse and interpret An outline of global lattice energy exploration sampling
- 9. First attempts J. Struct. Chem. (1984), 25, 416-420 • Many solutions with similar energies • The approach seems to work! Lowest energy structure (global minimum) is the observed structure
- 10. Crowded energy landscapes Many distinct crystal structures. Very small energy differences.
- 11. Vox populi Cryst. Growth & Des. (2006), 6, 1985–1990 http://dx.doi.org/10.1021/cg060313r Crystal structure prediction → low energy possible crystal structures 5 of lowest energy structures (named A-E) presented to crystallographers at IUCr2005 (Florence) Allowed to visualise structures and asked to select the ‘true’ structure. a) b) observed observed We cannot distinguish the correct from the ‘false’ structures by visual analysis.
- 12. Position [°2Theta] 5 10 15 20 25 30 XRPD from bulk simulated from known structure crystallisation from nitromethane XRPD seems to show pure form Theophylline Polymorph screening and characterisation thermodynamically stable polymorph with Mark Eddleston, Bill Jones Cambridge
- 13. a different shape from the rest of sample 5 µm 2 µm thickness ~ 0.3 µm electron diffractionTEM image However, analysis by transmission electron microscopy (TEM) shows two different morphologies: Predominant form: triangular plate-like crystals These are the known form 10 µm Less than 1% of sample TEM analysis of theophylline These diffraction patterns are inconsistent with known forms of theophylline. Chem. Eur. J., (2013), 19, 7883–7888 http://dx.doi.org/10.1002/chem.201204369
- 14. Yet another form that we observe (based on TEM and external habit). ~ once in 20 crystallisations, < 1% of sample. M. D. Eddleston et al, submitted for publication TEM analysis of theophylline Chem. Eur. J., (2013), 19, 7883–7888 http://dx.doi.org/10.1002/chem.201204369
- 15. Applications in characterisation A) Role of crystal structure prediction in structure characterisation. • Jointly with diffraction data (powder XRD, TEM) • In combination with solid state NMR expt calc CSP chemical shift calculations (ss-DFT) J. Am. Chem. Soc. (2010), 132, 2564–2566 Phys.Chem.Chem.Phys. (2013), 15, 8069-8080. J. Am. Chem. Soc. (2013), 135, 17501-17507 with Lyndon Emsley Lyon
- 16. 0 5 10 15 20 25 0.25 0.35 0.45 0.55 0.65 0.75 relativeenergy(kJmol-1) b-hydroquinone packing coefficient Importance of the landscape of structures B) We are changing our interpretation of the many structures on calculated landscapes • It used to be common to treat all but one structure in predicted sets as “wrong”. • We should treat these as real possibilities: many of these structures might be observable under the right conditions, and with the right characterisation tools. “Why don't we find more polymorphs?” S. L. Price, Acta Cryst. (2013). B69, p. 313-328 • Also on the landscape: host frameworks. Chem. Eur. J., (2009), 15, 13033. hydroquinone : C60 complex See poster MS112.P05.B663 Jonas Nyman
- 17. Microporous molecular crystals prefabricated molecular “pores” 4 x 6 Å diameter windows 4 x arene faces axial chirality window-to-arene packing → closed voids → formally non-porous CSP agrees: no window-to-window alignment in low energy structures CC1 CC3 CC1 CC3 with Andy Cooper Liverpool
- 18. pure R racemate Microporous molecular crystals predictable packing Nature (2011), 474, p. 367-371. Chem. Sci. (2014), 5, 2235-2245.
- 19. Microporous molecular crystals predictable packing X-ray Prediction Nature (2011), 474, p. 367-371. Chem. Sci. (2014), 5, 2235-2245.
- 20. predictable co-crystallisation and predictable porosity + Microporous molecular crystals predictable co-crystal packing non-porous Nature (2011), 474, p. 367-371.
- 21. Moving towards computational screening likelihood of observation relativeenergy Confidence in computational screening will depend on: 1) Variability of the target property among the predicted structures. 2) Reliability of the prediction. Cryst. Growth & Design (2004), 4, 1327 Cryst. Growth & Design (2005), 5, 1023. See poster MS112.P01.B659 Josh Campbell
- 22. Progress… 2002 2005 2006 2007 composition & structure co-crystals structure only 2008 2010 2011 Chem. Eur. J. (2008), 14, 8830; Chem. Commun. (2010), 46, 2224 Chem. Sci. (2013), 4, 4417. PCCP (2010), 12, 8466 Int. J. Pharm. (2011), 418, 168 JACS (2006), 128, 14466 PCCP (2007), 9, 1693
- 23. molecular connectivity rigid (one conformer) QM calculation Challenges of flexibility: conformer selection Crystal structure generation flexible conformer search + QM calculations ensemble of conformers conformer selection Crystal structure generation x N Lattice energy minimisations Inexpensive Force field methods Lattice energy minimisations More difficult: inter-/intra- balance Hybrid force field / QM models
- 24. 27 conformers 3 conformers 196 conformers A conformational explosion . . . ??? conformers This will scale very badly with size. Do we need to consider them all? We lack good guidelines on which of these are relevant for the crystalline solid state.
- 25. A set of pharmaceutical-like molecules Non-polymorphicPacking polymorphs Conformational polymorphs
- 26. CN1[C@H]2CC[C@@H]1[C@H]([C@H](C2)OC(=O)C3=CC=CC=C3)C(=O)OC ensemble of conformers & associated energies Some technical details Chemical diagram converted to a SMILE, from which an unbiased 3D structure is generated Conformer searches “Low-mode” search for all conformers Initially force field based (OPLS-AA-2005) Resulting structures re-optimised: B3LYP/6-31G(d,p) + dispersion correction (CRYSTAL09) Chem. Sci. (2014), 5, 3173-3182
- 27. Some technical details Optimisation of the crystal structure: B3LYP/6-31G(d,p) with dispersion correction (CRYSTAL09) Crystal calculations A) Single molecule energy at this geometry (energy of molecule in crystalline geometry) then B) Local minimisation (energy of associated conformer) molecular strain Where on the conformational landscape? Chem. Sci. (2014), 5, 3173-3182
- 28. Total numbers of conformers 0 50 100 150 200 250 HIBGUV MABZNA SIKRIN FAHNOR ODNPDS COCAIN VEMTOW FIBKUW NEWNIG HAJYUN GALCAX SEVJAF DANQEP CELHIL DADNUR 2418 numberofconformers
- 29. Energy rank of the crystalline conformer crystalline conformer Where on the conformational landscapes do we find the crystalline conformers? predicted conformers increasing energy predicted conformers increasing energy crystalline conformer DEconf DEconf
- 30. Energy rank of the crystalline conformer 0 20 40 60 80 100 283 conformerrank * * * * * * • Most molecules do not adopt their lowest energy conformer in their crystal • only 6 of 15 studied here • 2 of these 6 show conformational polymorphism These are adopting high energy conformations… for some reason
- 31. Energetic distribution of all conformers (all 15 molecules)
- 32. Why adopt such a high energy conformer? Global minimum conformer Crystalline conformer +25.5 kJ/mol We see an extended conformation, rather than the lower energy options. This makes sense: greater intermolecular stabilisation. Needs quantification… try surface area.
- 33. Why adopt such a high energy conformer? Global minimum conformer Crystalline conformer +25.5 kJ/mol AConnolly = 387.7 Å2AConnolly = 321.7 Å2 +66 Å2 We see an extended conformation, rather than the lower energy options. This makes sense: greater intermolecular stabilisation. Needs quantification… try surface area. Connolly surface spherical probe
- 34. Why adopt such a high energy conformer? Global minimum conformer Crystalline conformer +25.5 kJ/mol AConnolly = 387.7 Å2AConnolly = 321.7 Å2 +66 Å2 We see an extended conformation, rather than the lower energy options. This makes sense: greater intermolecular stabilisation. Needs quantification… try surface area. Connolly surface spherical probe All conformers of this molecule observed conformer
- 35. Importance of accessible surface area observed conformers in red
- 36. Importance of accessible surface area All molecules, all conformers
- 37. Importance of accessible surface area All molecules, all conformers • There is clearly a balance of inter- and intra-molecular energies • High energy, compact conformations are not see in crystal structures. • We thought about conformer selection rules based on DE and DA. • Why not unify these? The bias towards extended conformations reflects intermolecular stabilisation.
- 38. Gradient = 0.75 kJ mol-1 Å-2 At least for non-polar surface area, we can relate increases in lattice energy to increased molecular surface area. Molecules with reasonably well determined sublimation enthalpies: Surface area → pseudo-energy function A relationship between molecular surface area and lattice energy has been observed. A. Gavezzotti, JACS (1985), 107, 962. Chem. Sci. (2014), 5, 3173-3182
- 39. Global minimum conformer Crystalline conformer DAConnolly = 66.0 Å2 DEconf = 25.5 kJ mol-1 The increase in potential lattice energy overcomes the intramolecular energy cost. Surface area → pseudo-energy function x 0.75 kJ mol-1 Å-2 → -49.5 kJ mol-1 Chem. Sci. (2014), 5, 3173-3182
- 40. 0.75 kJ mol-1 Å-2 High energy, compact conformations are not see in crystal structures All observed conformers fall below this line. Chem. Sci. (2014), 5, 3173-3182 observed conformers in red
- 41. What does this mean for CSP? More efficient selection of conformers DEconf,biased = DEconf + 0.75 DAConnolly An enrichment in observed conformers in the region of low “energy”. Observed conformations based on energy. Need to consider up to approx. 26 kJ/mol. This would be bad news for structure prediction (computational or otherwise). Chem. Sci. (2014), 5, 3173-3182
- 42. More efficient selection of conformers 0 100 200 300 400 500 600 700 3 5 7 9 11 conformersinobservedDEconf flexible degrees of freedom Previous limitation re-filtering of conformers extends what we can do
- 43. Take-home • Computational methods offer an approach to exploring the packing possibilities that are available to molecules. • applications in: characterisation, anticipation, screening (design?). • The applicability of these methods is moving forward: • larger, more flexible molecules • multi-component systems Challenges and limitations remain. Some structures will remain unpredictable for a long time.
- 44. current group Dr Peter Bygrave Dr David Case Dr Angeles Pulido Dr Julien LeJeune Dr Janliang Yang Mr Joshua Campbell Mr Jonas Nyman Mr Thomas Gee Mr Hugh Thompson Acknowledgements past group members Dr Tim Cooper Dr Aurora Cruz Cabeza Dr Katarzyna Hejczyk Dr Daniele Tomerini Mr Andreas Stegmüller Dr Edward Pyzer-Knapp Dr Eloisa Angeles All collaborators, past and present.