HIFI NMR : part1 automated backbone assignments using 3D->2D

Transcription

1 HIFI NMR : part automated backbone assignments using 3D->2D Marco Tonelli National Magnetic Resonance Facility At Madison NMRFAM

2 Recording multidimensional experiments is time costly In conventional multidimensional experiments, all the individual frequency domains are incremented (sampled) independently t D t FID 30 sec. t 2 Increasing number of indirect dimensions in conventional multidimensional: collection time increases exponentially t : 28 FIDs 64 min. need 2D to reduce number of increments 3D to keep collection time reasonable: low resolution not very practical above 3 dimensions t t 3 t x t 2 : 28x28=6,384 FIDs 5 days 6 hrs. t2 impossible above 4 dimensions 4D t x t 2 x t 3 : 32x32x32=32,768 FIDs days 9 hrs.

3 Fast methods Reduced Dimensionality Reduced Sampling Hadamard spectroscopy single-scan NMR so-fast NMR

4 Reduced Dimensionality Techniques two or more indirect dimensions are evolved simultaneously preparation t mix/prep t t 3 2 mixing Conventional 3D spectrum RD spectrum t /t 2 t t 2 t 3 t and t 2 are incremented simultaneously point by point t 3 t and t 2 are incremented independently

5 Reduced Dimensionality Techniques Φ Φ 2 t preparation mix/prep t t 3 2 mixing Φ = x,y Φ 2 = x Φ = x,y Φ 2 = y Φ = x,y t /t 2 RD spectrum sinωt x cosωt 2 t /t 2 RD spectrum sinωt x sinωt 2 t 2D spectrum sinωt cosωt t 3 cosωt x cosωt 2 FT t 3 cosωt x sinωt 2 FT t 3 FT ω /ω 2 δ δ 2 ω /ω 2 δ δ 2 δ + δ 2 δ + δ 2 ω δ ω 3 ω 3 ω 3 δ δ 2 ω /ω 2 δ + δ 2 ω 3 ω 3

6 Reduced Dimensionality Techniques The peaks in RD experiments can either be separated into different spectra (GFT - Syperzky) or into different regions of the same spectrum (TPPI - Gronenborn) GFT TPPI Method 2D + δ 2 δ + δ 2 δ + δ 2 ω ω δ /ω 2 TPPI offset - δ 2 δ - δ 2 δ - δ 2 ω 3 ω 3

7 2D RD planes of 3D spectra 2D projections of 3D spectra tilted planes 0 H- 3 C plane of CBCA(CO)NH 3 C 0 plane 5 N H H 3 C 90 H- 5 N plane of CBCA(CO)NH 5 N 90 plane 5 N H H 3 C 45 θ H- 3 C/ 5 N plane of CBCA(CO)NH 3 C/ 5 N tilted plane 5 N H H 3 C

8 Reduced Dimensionality Techniques By changing the ratio between the two simultaneously evolving dimensions we can change the projection angle of the tilted plane t 3 C t 5 N θ θ 5 N H 3 C

9 Reduced Dimensionality Techniques Projection Reconstruction Simple 3D objects can be reconstructed from 2D projections collected at different angles 3D object 3D reconstruction reconstructed object θ D reconstrucion In principle, it is feasible to reconstruct a 3D spectrum from a number of 2D tilted planes collected at different angles. 5 N H 3 C

10 Reduced Dimensionality Techniques GFT / TPPI method n-dimensional experiments are run as two-dimensional RD spectra split peaks can be separated into different spectra (GFT) or different regions of the same spectrum (TPPI) Projection-Reconstruction multiple tilted planes are collected at different angles n-dimensional spectra are reconstructed from several tilted planes indirect frequencies are extracted from analysis of split patterns High-resolution Iterative Frequency Identification HIFI simultaneously evolving indirect frequencies are extracted from twodimensional RD spectra multiple tilted planes are used angle of tilted planes is chosen adaptively in real time

11 Reduced Dimensionality Techniques GFT / TPPI method Projection-Reconstruction it relies on combining multiple indirect dimension to resolve overlapped peaks with each added indirect dimension: S/N is reduced by 2 collection time is doubled analysis can be very complicated HIFI multidimensional frequency information can only be extracted after spectra reconstruction reconstructing spectra can be very complicated or impossible with overlapped peaks and/or low S/N difficult to automate difficult to automate by changing the tilt angle, HIFI has greater potential of resolving overlapped peaks than GFT/TPPI methods since only frequency information is extracted from tilted planes, HIFI does not need to resolve the problem of reconstructing nd volumes easier to analyze easier to automate by adaptively choosing the next tilt angle, HIFI optimizes information gain while minimizing time collection

12 HIFI flowchart orthogonal planes mortho0 macro hifi.sh generate_peaklist.sh predict next best tilted angle does tilted plane add new information??? NO YES tilted plane this process can be automated in vnmr peak list

13 HIFI algorithm for predicting best tilted angle orthogonal planes predicted chemical shift distribution 0 90 assign a probability of a peak being in a given voxel, p find a tilt angle that maximizes a dispersion function f θ (p) dispersion function, f θ (p), measures the dispersion of the putative peaks on the selected tilted plane collect tilted plane does X YES tilted plane add NO new information??? peak list Eghbalnia et al JACS 27 (36), , 2005

14 putative peaks from C-H/N-H planes add 45 tilted plane add additional tilted planes HIFI on CBCA(CO)NH Combined peaks from HIFI planes are in magenta Hand picked peaks from 3D spectrum in green

15 Using HIFI for backbone assignments Modified BioPack experiments for backbone assignments HNCO HN(CO)CA HNCA CBCA(CO)NH HN(CA)CB HNCACB NH sensitivity enhanced TROSY option standard sequences are robust and offer the best S/N for backbone assignments we rely on HIFI ability to adaptively select tilted planes to resolve overlapped peaks added HIFI option for collecting tilted planes 3 C and 5 N indirect dimensions are evolved simultaneously added semi-constant time 5 N evolution to allow collecting tilted planes with more indirect points for higher resolution optimized for cryogenic probes Needs AUTOMATION!!!

16 preparation - orthogonal planes outline of vnmr macro for automated HIFI data collection run othogonal planes for all experiments all experiments list: collect plane adjust 3 C s.w. save orthogonal planes process orthogonal planes optimize processing parameters H- 5 N HSQC : use as plane adjust 5 N s.w. input list of experiments number of residues = XX HNCO HN(CO)CA HNCA CBCA(CO)NH HNCACB HN(CA)CB hnco_tilt_0 hncoca_tilt_0 hnca_tilt_0 cbcaconh_tilt_0 hncacb_tilt_0 hncb_tilt_0 hnco_hsqc hnco_hsqc hnco_hsqc hnco_hsqc hnco_hsqc hnco_hsqc experiment # in list run HIFI macro - tilted planes run tilt angle predicting program process tilted plane next experiment in list read predicted tilt angle tilt=0 run program to extract 3D frequencies tilt>0 save tilted plane run experiment to collect tilted plane at suggested angle 3D peak list NO all experiments in list completed?? YES run probabilistic backbone assignments

17 HNCO HN(CO)CA HNCA CBCA(CO)NH HN(CA)CB HNCACB 47º 62º 2 52º 69º 2 5º 7º 29º 38º 4 49º 63º 44º 32º 4 42º 59º 3º 28º 4 39º 45º 3º 8º 5º 5 4º 38º 34º 3 5º 69º 44º 3 56º 67º 22º º 57º 4 3º 4 53º 62º 4º º º 37º 26º 8º 57º 6 brazzein - 53 a.a. ubiquitin 76 a.a. flavodoxin 76 a.a. 7º 42º 5º 2 63º 4 26º 7 34º 53º 4 46º 59º 8º 39º 34º 52º 7 46º 6 8º 35º 26º 53º º 35º 8º 4º º 33º 3º 39º 29º 9 53º 7 28º 4º 4º 6 35º 7 43º 64º 2 45º 77º 2 4º 63º 27º 33º 4 65º 77º 54º 42º 4 3º 42º 24º 2º 5º 5 ~9hrs ~2hrs ~4hrs ~48hrs wild-type RI mutant

18 HIFI backbone assignments - recap we have developed HIFI for extracting 3D peaks using 2D tilted planes by adaptively predicting the best tilt angles, we guarantee that all available 3D data is extracted using the minimum number of tilted planes we have adapted the most robust 3D experiments for backbone assignments to be recorded using HIFI-NMR we have successfully automated HIFI backbone data collection for proteins of small/medium size automated HIFI is robust and allows to extract 3D peaks lists with: least amount of spectrometer time minimum human intervention

19 where is HIFI going size deuteration selective labeling T2 relaxation peak overlap protein sample TROSY 4 3 resolve overlap longer time _ higher S/N complicated conventional NMR experiments resolve overlap complicated lower S/N 3 2 longer time _ higher S/N HIFI Improving algorithm for peak detection Improving algorithm for tilt angle prediction Combine information from different experiments Acquired # dim Total # dim Acquired # dim

20 The BIG picture NMR data collection chemical shift assignments structure calculation

21 HIFI NMR : part2 conclusions and other applications Marco Tonelli National Magnetic Resonance Facility At Madison NMRFAM

22 HIFI: application to chemical shift assignments TODAY: HIFI adaptive robust : collect all the information needed efficient : collect only the minimum amount information needed to answer the question HNCO HN(CO)CA HNCA CBCA(CO)NH HNCACB HN(CA)CB orthogonal plane HIFI predict best angle collect tilted plane peak list BACKBONE ASSIGNMENTS

23 HIFI: application to chemical shift assignments HIFI TOMORROW: adaptive robust : collect all the information needed efficient : collect only the minimum amount information needed to answer the question HNCO HN(CO)CA HNCA CBCA(CO)NH HNCACB HN(CA)CB peak list orthogonal plane predict best angle collect tilted plane HIFI BACKBONE ASSIGNMENTS

24 HIFI: application to chemical shift assignments HIFI adaptive THE DAY AFTER TOMORROW: robust : collect all the information needed efficient : collect the only the minimum amount information needed to answer the question collect preliminary data HIFI pool of experiments select experiment predict best tilt collect tilted plane BACKBONE ASSIGNMENTS

25 HIFI: other applications any application that makes use of information extracted from a 3D experiment can be speeded up by recording a tilted plane instead Conventional 3D spectrum tilted plane t /t 2 t t 2 t 3 t 3 HIFI can then be used to ensure that maximum information is recovered by predicting the best angle to use for recording the tilted plane

26 HIFI: other applications +θ 3 C + 5 N 5 N H H 3 C θ 3 C - 5 N H two tilted planes are obtained for each experiment run: plus and minus different peak distribution bigger potential of resolving overlapped peaks different noise distribution can provide measure of confidence of data obtained by analyzing spectra

27 HIFI: extraction of RDC Example: extraction of RDC C N using a modified HNCO pulse sequence (Bax) Conventional method: record two 3D C -N-H experiments:. reference spectrum 2. attenuated spectrum - intensity of peaks is modulated by coupling: J C N + D C N reference attenuated 5 N 5 N H 3 C H 3 C extract J C N + D C N coupling from the ratio between intensity of corresponding peaks in the reference and attenuated spectra repeat for isotropic and aligned samples

28 HIFI: extraction of RDC HIFI method: record two tilted C -N-H planes at the optimal tilt angle:. reference spectrum 2. attenuated spectrum - intensity of peaks is modulated by coupling: J C N + D C N reference +θ attenuated +θ reference θ attenuated θ 3 C + 5 N 3 C - 5 N H H H H extract J C N + D C N coupling from the ratio between intensity of corresponding peaks in the reference and attenuated spectra analyze plus and minus planes independently compare the results from the two plenes to get measure of data confidence combine the results from the two planes repeat for isotropic and aligned samples

29 Who did the work? pulse sequences vnmr automation RDC extraction Marco Tonelli Klaas Hallenga Gabriel Cornilescu tilt prediction and peak extraction algorithms Arash Barhami Hamid Eghbalnia sample preparation Fariba Assadi-Porter Shanteri Shingh Rob Tyler Anna Fuzery Nick Reiter Claudia Cornilescu John Markley Milo Westler