Crystal Structure Prediction A Decade of Blind Tests. Frank Leusen

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1 Crystal Structure Prediction A Decade of Blind Tests Frank Leusen

2 Outline Crystal structure prediction Blind tests in crystal structure prediction 1999, 2001 and 2004 editions The 2007 edition of the blind test Methodology and results Conclusions and outlook

3 Crystal structure prediction Find lowest lying minima on lattice energy hypersurface Function of Space group Lattice constants a, b, c, α, β, γ Contents of asymmetric unit?

4 Problems in CSP Mathematical problem Number of degrees of freedom Unit cell, molecular flexibility, molecular orientation, number of molecules in asymmetric unit Physical problem Accuracy of energy calculations Exotic elements, intra-molecular energy, polarisation, ionic systems

5 Lattice energy Basic thermodynamics G = U + pv TS Gibbs free energy G, enthalpy U, pressure p, volume V, temperature T and entropy S U is the most important contribution pv is very small at normal pressure and can be neglected TS is not negligible at room temperature but is difficult to calculate accurately External factors (solvent, impurities, crystal defects, diffusion, etc) are neglected

6 Cambridge Crystallographic Data Centre Blind Tests in Crystal Structure Prediction

7 Background Organised and hosted by Cambridge University / CCDC In 1999, 2001, 2004 and 2007 Each test: three or four molecules Experimentally observed crystal structures are kept hidden Invited participants to predict crystal structures Up to three predictions per molecule Time limit of six months

8 Williams Verwer & Leusen Schmidt Price Motherwell Mooij Lommerse Hofmann Gavezzotti &Schweizer van Eijck Ammon CSP participants 4 molecules I (polymorph A) I (polymorph B) II X X X 2 III 1 VII (propane) X X X 1 X X 24 March Lommerse 2009 et al., Acta Crystallographica B, 56: (2000)

9 Williams Verwer Schweizer Schmidt Scheraga Price Motherwell Mooij Lommerse Leusen Hofmann Gavezzotti Erk van Eijck Dzyabchenko Ammon CSP participants 3 molecules IV X 3 2 V X 3 VI X X X X X ACS SLC et al., Acta Crystallographica B, 58: (2002)

10 Verwer Schweizer Schmidt Scheraga Price Pantelides Motherwell Liang Leusen Hofmann Facelli Erk van Eijck Dzyabchenko Della Valle Day Boerrigter Ammon CSP participants 4 molecules VIII (not blind!) 1 X X 1 X IX 1 X X X X X X X XI Day et al., Acta Crystallographica B, 61: (2005)

11 Blind test participants 4 molecules :

12 Our approach Use AMS novel technology for crystal structure generation and lattice energy calculation Predictions in all 230 space groups Crystal structure generation by random search engine combined with lattice energy minimizer Molecular flexibility probed automatically during search The two components of the co-crystal (molecule XV) were treated independently

13 Methodology Previously, all successful methods used molecular mechanics approaches to generate structures and rank them by stability Variety of potentials, e.g., point charges vs multipoles Relatively fast, but inaccurate even with sophisticated potentials New approach uses tailor made force field to generate structures and solid state hybrid MM / DFT for stability ranking DFT calculations with VASP combined with molecular mechanics van der Waals correction Force field is fitted to hybrid MM / DFT results Relatively slow, but very accurate Requires significant expertise and significant CPU resources Hybrid MM / DFT method Neumann and Perrin, Journal of Physical Chemistry B, 109: (2005) Force field fitting Neumann, Journal of Physical Chemistry B, 112: (2008)

14 Computational strategy structure generation final energy ranking starting Hessian Tailor-made force field parameterization Hybrid method

15 Molecule XII Space group Rel latt energy (kcal/mol atom) Density (g/cm 3 ) a (Å) b (Å) c (Å) α ( ) β ( ) γ ( ) Exp Pbca Exp Pred 1 Pbca Pred 2 P21/c Pred 3 Pc

Molecule XII powder patterns Intensity 100 90 80 70 60

Simulated for predicted structure 10 0-10 0 10 20 30

16 Molecule XII powder patterns Intensity Simulated for experimental structure Simulated for predicted structure theta MolXII (Sim) nlk_xii_0 (Sim) Observed Reflections

17 Molecule XII Experimental Predicted

Molecule XIII powder patterns Intensity 100 90 80 70 60

Simulated for predicted structure 10 0-10 0 10 20 30 40

18 Molecule XIII powder patterns Intensity Simulated for experimental structure Simulated for predicted structure theta MolXIII (Sim) ms_xiii_1 (Sim) Observed Reflections

19 Molecule XIII Experimental Predicted

Molecule XIV powder patterns Intensity 100 90 80 70 60

20 Molecule XIV powder patterns Intensity Simulated for experimental structure Simulated for predicted structure theta MolXIV (Sim) ms_xiv_1 (Sim) Observed Reflections

21 Molecule XIV Experimental Predicted

Molecule XV powder patterns Intensity 100 90 80 70 60

22 Molecule XV powder patterns Intensity Simulated for experimental structure Simulated for predicted structure theta MolXV (Sim) ms_xv_1 (Sim) Observed Reflections

23 Molecule XV Experimental Predicted

24 Summary Four out of four structures correct All four structures were predicted as our top rank Results could not have been better! Sanderson, Nature, 450: 771 (2007) Neumann, Leusen and Kendrick, Angewandte Chemie International Edition, 47: (2008) Day et al, Acta Crystallographica B, 65: (2009)

25 Schweizer Schmidt Scheraga Price Neumann, Leusen & Kendrick Jose Hofmann Gavezzotti Facelli van Eijck Desiraju Della Valle Day Boerrigter Ammon CSP participants 4 molecules XII XIII cocrystal 2 1 X 1 2 XIV 1 1 X 1 1 XV X 1 X 1 1 X 3 X X 1 X

26 Conclusions Crystal structures of small organic molecules are predictable Use tailor made force field to generate limited set of possible structures Use solid state DFT with empirical van der Waals correction to calculate accurate lattice energies Requires significant compute power, time & expertise Accurate lattice energies are an appropriate selection criterion in crystal structure prediction Long way to go to make reliable CSP a standard tool But a big leap forward has been made

27 Further work Further developments required to predict polymorphic stability Consideration of zero point energies and entropic effects Run simulations on many more test systems to establish general accuracy and reliability Larger sample required for meaningful statistics Need to explore limitations Progress is slow due to CPU requirements Extend parameterisation of hybrid method Further improvements in force field accuracy required Focus on electrostatics

28 Challenges More than one molecule per asymmetric unit Solvates Salts Highly flexible compounds Very large molecules, e.g., polypeptides

Acknowledgements Marcus Neumann (Avant-garde Materials Simulation) John Kendrick and Aldi Asmadi (University of Bradford) Sanofi-Aventis and Astra Zeneca

Simulation) and Lionel Zaske (Sanofi-Aventis) for running some of the calculations Pascale Girard (Avant-garde Materials Simulation) and Marc-Antoine Perrin

29 Acknowledgements Marcus Neumann (Avant-garde Materials Simulation) John Kendrick and Aldi Asmadi (University of Bradford) Sanofi-Aventis and Astra Zeneca for funding the software development Victoria Pennington (University of Bradford) for keeping the hardware running Ralf Siebrecht (Avant-garde Materials Simulation) and Lionel Zaske (Sanofi-Aventis) for running some of the calculations Pascale Girard (Avant-garde Materials Simulation) and Marc-Antoine Perrin (Sanofi-Aventis) for general support Graeme Day (University of Cambridge) for organising and CCDC for hosting the blind test CCDC for supporting this presentation

research papers Crystal structure prediction of small organic molecules: a second blind test 1. Introduction 2. Approach and methodology

research papers Crystal structure prediction of small organic molecules: a second blind test 1. Introduction 2. Approach and methodology Acta Crystallographica Section B Structural Science ISSN 0108-7681 Crystal structure prediction of small organic molecules: a second blind test W. D. Sam Motherwell, a * Herman L. Ammon, b Jack D. Dunitz,