High-Throughput in Chemical Crystallography from an industrial point of view

Transcription

1 High-Throughput in Chemical Crystallography from an industrial point of view Ina Dix Novartis Institutes for Biomedical Research, Basel

2 Analytics at Novartis (Basel) staff # spectra NMR structure determinations IR all completely interpreted MS completely interpreted A MS M-H+ = 444 IR O NMR N N O sample (purified) with HPLC molecular mass functional groups structure

3 Analytics at Novartis (Basel) staff # spectra NMR structure determinations IR all completely interpreted MS completely interpreted X-ray # samples XP XX structures 2010* * first 8 month

4 Number of samples at Novartis (Basel) no. samples expected accepted year

5 Number of samples at Novartis (Basel) incoming processed 1 (0.3 %) 199 (68.3 %) 92 (31.6 %) 119 (41.0 %) 89 (30.6 %) 79 (27.1 %) 3 (1.0 %) blue: red: crystalline not crystalline blue: crystalline yellow: grown crystals red: not crystalline

6 Crystal morphologies at Novartis (Basel) needles plates others 26 % 63 % 11 %

7 Crystal sizes at Novartis (Basel) % 63 % 11 % other

8 Instruments used for measurements ImS RA SLS 10 µm

9 Categories of compounds with HA w/o HA chiral non chiral

10 Number of independent molecules

11 Some more statistics 2.4 % 79.8 % 17.8 % 65.4 % 19.7 % 11.6 % structures: finished refinement: normal ongoing disorder not solved twinned modulated 71 % of measured crystals are solvates! 3.3 %

12 Statistics 2010: quality criteria 166 structures (8 month) wr R 1 (all) 0

13 Reasons for x-ray structures stereochemistry proof of constitution bond length and angles 3-dimensional models d absolute structure determination unknown compounds?

14 Customised approach Proof of constitution (routine case) N H N H N H 1. Structure solution as fast as possible N H N H compound o.k.? symmetry structure o.k.? publicity HO HO H O 2. Completion of data set based on requirements HO OH Absolute structure determination

15 Time problems with Cu radiation partial data set (proof of constitution) full data set (ACTA C standards) to obtain structure as quick as possible: 2θ 2θ nλ = 2d sin(θ) move in detector to catch as many reflections as possible with only one detector position limiting factor: overlap for long cell edges at 4 cm up to 50 Å Mo Cu radiation (small (large 2θ range): 21 detector settings

16 Experimenatal parameter: increments of rotation x-ray x-ray each scan: overall 180º in ω outer sphere: 3 x 180, doubled exposure time ω # frames data RA+OH total :40 h 1:40 h 3:20 h :25 h 0:25 h 0:50 h :15 h 0:13 h 0:28 h * Exposure time: 5 s

17 Limiting factors: axis length, exposure time, software 5º image of an 47 Å axis x x 0.3º 2.1º Indexing and intergration: center of gravity? good compromise: ω frames data readout total :25 0:25 0:50

18 Scaling of Cu-data (SADABS) typ. YLID acceptance measurement at d=5(!) cm after 10 h redundancy: 5.4 (3.3) h Red. d/p 2: (2.8) 5.9 (97%) 4: (5.5) 6.8 (99%) 7: (8.3) 7.1

19 Completion of data set x-ray scan-ratio 1:3 x-ray completeness > 95 % resolution 0.84 Å redundancy > 3 I/σ(I) > all w/o P 1 P 1 P 21/c P 2 1

20 What means based on requirements? R1 HO H Q1: 0.25 Q2: 0.20 Q3: 0.19 Q1: 0.48 Q2: 0.20 R2 R1 = , wr2 = , Flack x = 0.03(1)!! H N 5 % impurity not assignable with NMR >8Å N O N O N inversion of 6-ring causes line broadening ratio 60:40

21 example 1: good scatterer, low symmetry (P-1) after 2 scans 180º (50 min): 52 % compl. data to 0.84 Å data processing online preparation of input files 1 min solution after altogether 55 min!

22 example 2: twin, monoclinic after 150 frames (25 min): 77 % compl. data set to 1.10 Å Structure solution after 30 min after 2 seconds: 54 % of atoms (refinement: + 46%)

23 example 2: twin, monoclinic single crystal R1 all (R1 [I>2σ]) 3.07 (3.12) wr2 all 7.93 R1* 3.14 GooF Weight / Flack x (0.0617) twin (HKLF4) 2.64 (2.67) / (0.0490) twin (HKLF5) [ratio 83/17] 2.82 (2.85) / (0.0510) * reflections after merging for Fourier

24 example 3: multiple twin, monoclinic

25 example 3: multiple twin, monoclinic after 150 frames (50 min): 73 % compl. data to 1.10 Å structure solution after 60 sec 41 atoms (32 OK, cycle1 +14, cycle 2 +2) R (3.50) wr Flack x 0.023(10)

26 example 4: weak scatterer, monoclinic after 75 frames (90 min): 44 % compl. data to 1.09 Å structure solution after 75 sec after 2 min: 43 atoms (one cycle: remaining 15 atoms found)

27 example 4: weak scatterer, monoclinic 6 scans 8 scans 12 scans 15 scans best 10 scans Compl Redund (1.38) 5.66 (1.63) 8.49 (2.37) (2.98) 6.76 (1.61) R(int) R(σ) R1(2σ) R1 all wr2 (2σ) wr2 all GooF

28 Absolute structure determination f = f o + f + if f and f atom type and wavelength dependent Ag-Kα = Å Mo-Kα = Å Cu-Kα = Å Cr-Kα = Å AgKα MoKα CuKα CrKα f f f f f f f f B C N O F P S Cl Br I

29 Absolute structure determination S-compound, O-compound, Cu-Kα: Cu-Kα: I 732 = I ; = 513.1; I I = = F c (4 3 5) = F c ( ) = > I(-) > I(+)!! I (-) = = 0.4 I (+) C: 66.7 %, H: 6.7%, O:26.6 % I (+) I (-) refl. (5356 unique, 5280 > 2 σ) R int = R 1 = (0.0236) wr 2 = (0.0594) GoF = (1.047, 17) res. el. dens / e/å 3 Flack x = 0.00(9)

30 example 5: absolute configuration, monoclinic C: 78%, H: 9%, N: 6 %, O: 7% runs # refl Red. R(int) R(sigma) x(u) (2.1) (29) (3.7) (27) (5.4) (27) (7.5) (26) (9.5) (26) (11.4) (26) (14.4) (26)

31 Q-value method (Simon Parsons) Most reflections in a data set are rather insensitive to the absolute structure. For the sensitive reflections a quotient D can be defined: D obs (h) = I(h) I(h) I( h) + I( h) = (1 F(h) 2x) F(h) F( h) F( h) 2 2 I(h) and I(-h) have been measured in a way that the quotient is free from systematic errors such as absorption and extinction These quantities can be applied as restraints (in CRYSTALS). Since the restraints are linear in x convergence is fast (one cycle). The method is also implemented in XPREP.

32 Q-value method Implementation in XPREP pre-requisites:.res file (w/o riding H!) and.hkl file

33 Q-value method runs # refl Red. R(int) R(sigma) x(u) (2.1) (12) (3.7) (9) (5.4) (7) (7.5) (6) (9.5) (5) (11.4) (5) (14.4) (5)

34 Bayesian Approach Provides relative probabilities for different models of the chiral compound. It is possible with prior knowledge of enantiopurity to calculate the probability of each enantiomer. p2(true) and p2(false) It is also possible to determine with no prior knowledge if the structure is either enatiomerically pure or indeed a racemic mixture. p3(true), p3(false) or p3(rac-twin)

35 Bayesian Approach Using the method

36 Bayesian Approach Using the method

37 example 5: absolute configuration, monoclinic standard deviations are significantly lowered (factor 2-3)

38 example 6: being fast, but not too fast C: 82%, H: 6%, N: 8 %, O: 4% 4 scans 5034 (96 %) (34) i 0.37(28) 6 scans 7370 (98 %) (25) i 0.27(25) 16 scans (100 %) (19) i 0.11(19) 0.65(20) 0.34(20) 0.86(18) 0.14(18) 1.02(10) 0.03(10) 0.6(2) 0.4(2) 0.74(19) 0.26(19) 0.91(10) 0.09(10)

39 Going to the limits C: 83 %, H: 7 %, N: 10 %

40 Flack x parameter Parsons Flack x: (0.13) (0.15) (0.16)

41 Thanks to: Philippe Piechon, Lukas Oberer, Trixie Wagner (Novartis) George Sheldrick (Uni Göttingen) Bruker AXS