Hi,
we have embodied into the Relax program possibility to perform the
analysis with consideration of the asymmetric character of the CST and
also all dipole-dipole interactions arising from the spins in the
proximity to the studied S-I spin pair.
This should be taken into the account for the dynamic studies of the
fully labeled nucleic acid (Poster 118 at 23rd ICMBRS meeting in San
Diego) and we would like to add this feature to the public version of
the Relax program.
These changes can be done by the addition of new terms into the
equations for the relaxation rates. The description of the relaxation
due to the fully anisotropic CST can be written in concordance with the
article by Goldman M, J magn. Reson 60, 437-452 (1984). The CST tensor
is splitted into two axially symmetric subtensors which both contribute
to the relaxation. Such approach has advantage that the spectral density
function do not change the form used in Relax program. The calculation
is done in the same manner using only different input orientation. The
function for chi^2 calculation and minimalization procedure is not
affected.
Definition additional input information:
The orientation of the CS tensor is defined in the new input file
containing for each studied nucleus three Euler angles in separate
columns defining the orientation of the CS tensor with respect to the
PDB frame (these values are then stored in the variable called CSEA).
Separate file contains three columns with the eigenvalues of the
chemical shielding tensor (these values are then stored in the variable
called CST).
The choice of atom responsible for the significant dipole-dipole
interaction with the studied nuclei is done in the PDB file. Atoms,
which are to be considered in the calculations, should be marked in the
PDB file by adding the distance to the studied nuclei (in the 1e-10m
unit) after the z coordinate. Other atoms should have zero distance
instead. So far only atoms from the same residuum may be taken into the
account.
Suggested changes in the code:
generic_fns/nuclei.py added function for setting gyromagnetic ratios
for selected atoms Y (atoms dipole-dipole interaction should be
considered in the calculation) and ratio of gyromagnetic ratios of atoms
Y and X (nucleus which relaxation is studied)
generic_fns/pdb.py added function for calculating XY unit vector
from the structure
generic_fns/runs.py added 'mf_csa' model name
prompt/interpreter and other files in prompt directory added code
for accessing Csa_data and Model_free_csa functions
prompt/model_free_csa.py added csa extended model_free code
(according to model_free.py)
prompt/csa_data.py Class for manipulating CST and CSEA csa data.
specific_fns/model_free_csa.py added csa extended model_free code
(according to model_free.py)
specific_fns/csa_data.py Class for manipulating CST and CSEA csa data.
Instead of the only jw_mf.py file in the original version of the Relax
program we added files:
jw_mf_csa1.py (calculate the spectral density function for the first
CS subtensor)
jw_mf_csa2.py (calculate the spectral density function for the
second CS subtensor)
jw_mf_csacross.py (calculate the cross correlation spectral density
function between both CS subtensors)
jw_mf_dipY.py (calculate the vector of the spectral density
functions for the dipole-dipole interactions to all nuclei Y, i.e. each
component of vector correspond to the individual dipole-dipole interaction)
direction_cosine_csa.py (calculate direction cosines of the
principal axis of the two CS pseudo tensors and first and second
derivations of the directions cosines with respect to the angles
defining the orientation of the diffusion tensor)
direction_cosine_dipY.py (calculate direction cosines of the
principal axis of the dipole-dipole interactions to atoms Y and first
and second derivations of the directions cosines with respect to the
angles defining the orientation of the diffusion tensor, data are store
as a vector, in which each component correspond to the individual
dipole-dipole interaction)
weights_csa1.py (calculate the coefficient necessary to calculate
the spectral density function for the first CS subtensor)
weights_csa2.py (calculate the coefficient necessary to calculate
the spectral density function for the second CS subtensor)
weights_csaC.py (calculate the coefficient necessary to calculate
the cross correlation spectral density function of the first and second
CS subtensor ... the form of the equation is slightly different to previous)
weights_dipY.py (calculate the coefficient necessary to calculate
the spectral density function for the first CS subtensor)
mf_csa.py (analogy of mf.py, redirect the calculation according to
the setup and initialize all necessary parameter)
ri_comps_csa_dipY.py (analogy to ri_comps.py, prepare the linear
combination of the spectral density functions and the constants
corresponding to the each type of the relaxation mechanism
i.e. instead of only
data.dip_jw_comps_func[i] ("i" goes over residues)
data.csa_jw_comps_func[i] ("i" goes over residues)
is necessary to introduce:
data.dip_jw_comps_func[i] ("i" goes over residues)
data.dipY_jw_comps_func[j][i] ("i" goes over residues, "j" over
atoms Y interacting with atom X)
data.csa1_jw_comps_func[i] ("i" goes over residues)
data.csa2_jw_comps_func[i] ("i" goes over residues)
data.csaC_jw_comps_func[i] ("i" goes over residues)
and similarly for constants:
data.dip_const_func by function comp_dip_const_func
data.dipY_const_func[i] by function comp_dipY_const_func ("j" over
atoms Y interacting with atom X)
data.csa1_const_func[i] by function comp_csa1_const_func ("i" goes
over spectrometer frequencies)
data.csa2_const_func[i] by function comp_csa2_const_func ("i" goes
over spectrometer frequencies)
data.csaC_const_func[i] by function comp_csaC_const_func ("i" goes
over spectrometer frequencies)
similarly for gradients and Hessian. So far the fitting the distance to
the selected neighbouring nuclei and the fitting of parameters of CS
tensor is not included.
ri_prime_csa_dipY.py (analogy of ri_prime.py, but relaxation rates,
gradients and Hessians comprises all terms calculated by mf_csa.py )
ri_csa_dipY.py (analogy to ri.py, but again the number of variables
is enlarged by those introduced previously)
All comments or suggestions are welcomed.
Pavel Kaderavek, Petr Novak
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relax (http://nmr-relax.com)
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