Is it possible to analyse CPMG experiments with relax? -- April 30, 2013 - 18:40

Dear relax users.

I am looking into different NMR programs to fit

relaxation data for CPMG relaxation dispersion experiments and T1rho.

Essentially, I am looking for programs for which can fit functions, which for example nessy provide:

http://home.gna.org/nessy/reference.html

The Meiboom equation or Richard-Carver equation

Nessy is very buggy, and I am looking for a replacement.

I should be able to:

R2eff = -1.0/time_T2*log(Intensity/averageZero)

ncyc_arr=[28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24]

time_T2 = 0.06 second

nu = ncyc_arr[i]/time_T2

R2cpmg_slow:

tau_cpmg = 1.0/(4*nu)

R2eff = R2+ka*(1.0-sin(Domega*tau_cpmg)/(Domega*tau_cpmg))

I have followed the tutorial in the homepage manual:

Can relax analyse these kinds of experiments?

Should i provide the: relax_fit.relax_time(time to be equal tau_cpmg ?

I put in time_T2, even though its wrong. I just wanted to try the program. :-)

----------------------------------------------------------------

"""Script for relaxation curve fitting."""

# Create the 'rx' data pipe.

pipe.create('rx', 'relax_fit')

## Load the backbone amide 15N spins from a PDB file.

pdbfile=False

if pdbfile:

    structure.read_pdb(pdbfile)

    structure.load_spins(spin_id='@N')

else:

    molecule.create(mol_name='protein', mol_type='protein')

    residue.create(res_num=2, res_name='VAL')

    spin.create(res_num=2, spin_name='N')

    residue.create(res_num=3, res_name='PHE')

    spin.create(res_num=3, spin_name='N')

    residue.create(res_num=4, res_name='GLY')

    spin.create(res_num=4, spin_name='N')

    residue.create(res_num=5, res_name='ARG')

    spin.create(res_num=5, spin_name='N')

    residue.create(res_num=6, res_name='CYS')

    .... and so on

## Loop over the spectra intensities. Relaxation times should be in seconds.

readint=True

if readint:

    spectrum.read_intensities(dir='relax', file='proc_list.txt.0int', spectrum_id='0_0.0', int_method='point sum', heteronuc='N', proton='HN', int_col=3)

    relax_fit.relax_time(time=0.06, spectrum_id='0_0.0')

    spectrum.read_intensities(dir='relax', file='proc_list.txt.1int', spectrum_id='1_133.33', int_method='point sum', heteronuc='N', proton='HN', int_col=3)

    relax_fit.relax_time(time=0.06, spectrum_id='1_133.33')

    spectrum.read_intensities(dir='relax', file='proc_list.txt.2int', spectrum_id='2_166.67', int_method='point sum', heteronuc='N', proton='HN', int_col=3)

    relax_fit.relax_time(time=0.06, spectrum_id='2_166.67')

    spectrum.read_intensities(dir='relax', file='proc_list.txt.3int', spectrum_id='3_333.33', int_method='point sum', heteronuc='N', proton='HN', int_col=3)

    relax_fit.relax_time(time=0.06, spectrum_id='3_333.33')

    spectrum.read_intensities(dir='relax', file='proc_list.txt.4int', spectrum_id='4_33.33', int_method='point sum', heteronuc='N', proton='HN', int_col=3)

    relax_fit.relax_time(time=0.06, spectrum_id='4_33.33')

   ... and so on

# Specify the duplicated spectra.

spectrum.replicated(spectrum_ids=['0_0.0', '18_0.0'])

spectrum.error_analysis()

# Deselect unresolved spins.

#deselect.read(file='unresolved', mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)

# Set the relaxation curve type.

relax_fit.select_model('exp')

# Grid search.

grid_search(inc=11)

# Minimise.

minimise('simplex', scaling=False, constraints=False)

## Monte Carlo simulations.

monte_carlo.setup(number=10)

monte_carlo.create_data()

monte_carlo.initial_values()

minimise('simplex', scaling=False, constraints=False)

monte_carlo.error_analysis()

## Save the relaxation rates.

value.write(param='rx', file='rx.out', force=True)

## Save the results.

results.write(file='results', force=True)

# Save the program state.

state.save('rx.save', force=True)

Best

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