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Optimally-designed, adaptive sampling of NMR experiments (implemented for Bruker spectrometers)

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Protocol: optimal sampling of relaxation

Setup

Python installation

Required libraries:

  • numpy
  • scipy
  • matplotlib
  • numba
  • json

Setting up python scripts

Ensure #! in analyse_results.py and final_results.py points to the correct python interpreter.

Set field strength in response_surface.py.

Setting up bruker bits

Copy files from bruker-bits into python script directory:

cp run_adaptive_methyl_ccr.py /opt/topspin/exp/stan/nmr/py/user/
cp -r simplejson /opt/topspin/exp/stan/nmr/py/user/

Edit run_adaptive_methyl_ccr.py to set appropriate experiment names and directories (at top of script file)

Setup pulse sequence

Use sequence adaptive_hsqcphpr.cw:

acquisition parameters:

  • o1p = 0.7 ppm
  • cnst21 = (bf hz) for off-resonance pre-sat
  • d0 = 13C evolution time (compensating for 13C 90 pulses) > 20 us
  • phcor7 = detection phase
  • o2p = 11 ppm
  • aq = 100 ms, td = 4k
  • d1 = 1 s

processing parameters:

  • WDW = EM
  • LB = 5 Hz
  • COROFFS = cnst21 - o1 (i.e. put solvent suppression on-resonance with water)
  • BCmod = qfil
  • SI = 16k
  • set phase correction based on run with d0=20us and phcor7=0

Chemical shifts

Measure using HMQC:

Peak: 1H shift: -0.2573 0.1958 0.4057 0.65367 0.7437 13C shift: 10.4281 11.3917 10.9918 10.784 11.8283

Optional debugging flags

od/optimal_design.py: PLOT = True

Running

run_adaptive_methyl_ccr

  • monitor output directory for result files
  • don't let anyone use the computer during acquisition!

To interrupt acquisition:

  • create a file named 'STOP' in the main experiment directory: touch STOP

Analysing results

Use script final_results.py:

  • Pass the experiment directory (containing adapt_ccr_* files) as a command line argument
  • Set the number of seed points at the top of the script file (for plotting)

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