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Pydoc: module diffPotTools

diffPotTools

index

tools to create a potential term restraining the shape of protein using components of rotation diffusion tensor. Together with facilities to fit NMR relaxation data.

Classes

builtins.object

FitResults
realx_datum
v_e

class FitResults(builtins.object)

Methods defined here:

__init__(self): Initialize self. See help(type(self)) for accurate signature.

Data descriptors defined here:

__dict__: dictionary for instance variables (if defined)

__weakref__: list of weak references to the object (if defined)

class realx_datum(builtins.object)

Methods defined here:

__init__(self): Initialize self. See help(type(self)) for accurate signature.

Data descriptors defined here:

__dict__: dictionary for instance variables (if defined)

__weakref__: list of weak references to the object (if defined)

class v_e(builtins.object)

Methods defined here:

__init__(self): Initialize self. See help(type(self)) for accurate signature.

Data descriptors defined here:

__dict__: dictionary for instance variables (if defined)

__weakref__: list of weak references to the object (if defined)

Functions

Target_relax_function(in_param, ifp): target function for fitting

addTmPAtoms(tpOatom=None, tpXatom=None, tpYatom=None, resid=None, segid=None, pot=None, mass=1000): create psf and initial coordinates for pseudo atoms used for optimizing
correlation times tau_c, tau_t and tau_i

analyze(potList): perform analysis of DiffPot terms and return nicely formatted summary

calcR2R1ratio(Freq=None, Ing=None, Rsel='resid 1:1000'): Subrutine which simulates NMR relaxation data
INPUT:
Freq is spectrometer frequency in GHz
Ing is a vector of diffusion tensor parameters which will be used
    for relaxation rates calculation
    Ing=[Dx, Dy, Dz, alpha, betha, gamma]
    for axial mode Ing=[Dxy, Dz, betha, alpha]
    for iso mode   Ing=[Dxyz]
    Dx, Dy, Dz are in inverse nanoseconds, alpha, betha, and
    gamma are in degrees
    Ing is in the same format as results.Fit_vector
res_sel is selection of residues in a format 'resid N:M' where
    integers N and M specify the range of residues used to
    simulate relaxation data
RETURN:
    out_dat list in format [resNum, R2/R1]

calc_relax_data(Fr=None, InG=None, res_sel=None): # Subrutine which simulates NMR relaxation data
# INPUT:
# Fr is spectrometer frequency in GHz
# InG is a vector of diffusion tensor parameters which will be used
#     for relaxation rates calculation
#     InG=[Dx, Dy, Dz, alpha, betha, gamma]
#     for axial mode InG=[Dxy, Dz, betha, alpha]
#     for iso mode   InG=[Dxyz]
#     Dx, Dy, Dz are in inverse nanoseconds, alpha, betha, and gamma are in degrees
#     InG is in the same format as results.Fit_vector
# res_sel is selection of residues in a format 'resid N:M' where integers N and M
#     specify the range of residues used to simulate relaxation data
# RETURN:
#     simulated_data list of realx_datum() structures containing R1, R2, and R2/R1
#     for details see declaration of FitResults() class below.

create_DiffPot(name, sel='known and (not PSEUDO)', temperature=293, addAtoms=False, mass=1000, link_to=None): create an instance of an diffPot.DiffPot object

Arguments:
name        - is an instance name of a diffPot object.
sel         - is selection of atoms which will be used to create
              protein surface tessellation by surfTessellation object
              This parameter is used only if the created relaxRatioPot
              instance is not using a surfTessellation
              borrowed from another potential, i.e. link_to=None, in
              which case sel argument is omitted.
temperature - the nominal experimental temperature in Kelvins
addAtoms    - flag wich specifies whether the pseudo atoms for
              temperature optimization are created or not. Default
              setting does not assume temperature optimization. The
              state addAtoms=True creates pseudo atoms
mass        - value for the mass of the pseudo atoms
link_to     - used to link the potential to surfTessellation created
              by another potential or to a standing alone
              surfTessellation object. The default setting that
              external surfTessellation is not given, and, therefore,
              creates a new surfTessellation using sel atom selection.

returns a diffPot object

diffValuesEuler(dT_e): given a diffusion tensor (in 100*[inverse ns]) return the
eigenvalues and Euler angles corresponding to the rotation matrix
formed from the eigenvectors
in a list:

[ a,b,c, gamma, beta, alpha ]

The eigenvalues are scaled by a factor of 0.1 such that they have
units of (10 * [inverse ns]).

estimate_Dxyz(in_data, omega_1): Estimates eigenvalue of diffusion tensor for given set of initial data
using assumption of isotropic tumbling model

fill_in_relax_datum(datum, datum_line, pattern): # service subroutine which distributes
# the list of given data into given
# rerealx_datum structure according given pattern

fill_in_results(results, in_Fit_res_list, mode, dlina, dT_e)

fitRelaxData(data_in=None, Fr=None, InG=None, mode='full', inc_sel='known', Err_calc=1): Function which fits NMR NH relaxation data using Nelder-Mead downhill
(amoeba) simplex method

Arguments:
data_in  - list of relax_datum structures which is generated by
           readInRelaxData
Fr       - is the spectrometer frequency in MHz
mode     - specifies the model for relaxation data fitting
             the available options for mode are:
             full  - is fully anisotropic tensor
             axial - is axially symmetric tensor
             iso   - is spherically symmetric tensor
InG      - optional list of initial guess parameters for fitting
           routine which should be compatiable with mode settings:
    for full mode  InG=[Dx, Dy, Dz, alpha, betha, gamma]
    for axial mode InG=[Dxy, Dz, betha, alpha]
    for iso mode   InG-[Dxyz]
    Dx, Dy, Dz are in inverse nanoseconds, alpha, betha, and gamma are
      in degrees
    if InG is not given then it is estimated for the loaded protein
    coordinates  using facilities in diffPot

inc_sel  - specifies the residues which will which will be included
           into the fit when relaxation data are available in data_in.
           Could be either a text string or an atom selection object.
Err_calc - number of bootstrap cycles for error calculations
    default settings Err_calc=1 which means that only the original data
    is used: no synthetic data sets prepared and no confidence
    intervals calculated. Bootstrap error estimations is lengthy. For
    robust estimation of confidence intervals the number of bootstrap
    cycles, Err_calc, should be equal to the number of R2/R1 relaxation
    data points in the data set used for fitting, len(in_relax).
    However to get an estimate of the order of magnitude for confidence
    intervals one may use about 20% of this number.

Returns:
    list_results[0], a python structure containing results of fitting
    for the original data set of relaxation data
    for details see declaration of FitResults() class below.

make_ratio(datum): For given realx_datum structure constructs a ratio of relaxation
rates R2/R1.

meanTemperature(term): term can be a single potential term, or a list of terms

merge2values(value1, err1, value2, err2)

mergeRelaxData(data_merged): # subroutine with analyzes give list of realx_datum structures,
# sorts the list according to the residue number,
# finds items with the same residue numbers,
# and merges them in a single relaxa_datum.

readInRST(restraints=None): # routine like above which starts from reading restraints
# for use in test file

readInRelaxData(file, pattern=['resid', 'ratio', 'ratio_err'], verbose=False): # pattern specifies the way the data given in the file
# possible keys for pattern are :
# resid         - residue number
# ratio         - ratio of relaxation rates
# ratio_err     - errors in ration of relaxation rates
# R1            - longitudinal relaxation rate
# R1_err        - error in longitudinal relaxation rate
# R2            - transverse relaxation rate
# R2_err        - error in transverse relaxation rate
# skip       - skip entry
# T1            - longitudinal relaxation time
# T1_err        - error in longitudinal relaxation time
# T2            - transverse relaxation time
# T2_err        - error in transverse relaxation time
# NOE           - heteronuclear NOE
# NOE_err       - error in heteronuclear NOE

registerTerm(term): add the given DiffPot object to a list associated with its Simulation.
These objects will be automatically processed by topologySetup and
massSetup.

remove_position_from_list(l_st, p_sn)

reset_DiffPot_temp(pot=None, temperature=None)

rms_relax_function(in_param, ifp)

showFitResults(results)

show_relax_datum(datum): debugging subroutine printing out the content of realx_datum structure

sqrt(x, /): Return the square root of x.

str2num(line=None)

tensParams(Dx, Dy, Dz): Given eigenvalues of a diffusion tensor, return a tuple
containing (tau, anisotropy , rhombicity), where tau is the
correlation time in ns.

topologySetup(ivm, list=[]): configure the given ivm.IVM object's topology setup using the
freedom string for each DiffPot in list.
This function should be called prior to
ivm.IVM.autoTorsion() or protocol.torsionTopology()

Data
		default_resid = 2700 default_segid = '' psfTmPTemplate = '\nstructure\nPSF\n\n 1 !NTITLE\n REMARKS preP... 1 0 !NGRP\n 0 0 0\n\nend\n' radiusMap = {'C': 1.85, 'H': 1.0, 'N': 1.75, 'O': 1.6, 'P': 2.05, 'S': 2.0} registeredTerms = {}