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Pydoc: module pasd.formatSTAR

pasd.formatSTAR

index

Functions

correctedSelection(resNum, resName, atomName): NMR-STAR formatted shift tables typically have three
types of atom name problems:

1.  Backbone amides are named H, rather than HN.

2.  methylenes are typically named H*2 and H*3 instead of
H*1 and H*2.  H*3 maps to H*2 and H*2 maps to H*1.

3.  Selections involving methyls usually only select one
of the three protons.

Returns an xplor selection with the atom name corrected/expanded
as necessary.

readSTAR(filename, addSaveSet=False): Read in the given NMR-STAR file and store the contents in the global
starData variable, which is returned.

If addSaveSet=True, wrap the contents of the file with the lines
save_dummy
  .
  .
  .
save_

starPeaks(fromProtonColumnName, toProtonColumnName, fromHeavyatomColumnName=None, toHeavyatomColumnName=None, saveSet=None, tclOutput=True): Read nmr-star table for 3d experiments.

Specify NMR-STAR saveSet where the experimental data is located,
and the identities of labels for the dimensions of the experiment.
These names correspond to NMR-STAR items Spectral_dim.Dimension_name.

starShifts(useAmbiguityCodes=False, saveSet=None, verbose=False, segmentName=None, residOffset=0, defaultErr=0, tclOutput=True): Read chemical shift data from the global starData cif.Cif
object, which must have been previously populated by calling readStar().

If useAmbiguityCodes is True, some effort is made to obey the
included ambiguity codes.

Use a non-zero residOffset if the residue numbering in the shift table
differs from that in your PSF.

If the error (Val_err field) is not present in the STAR file, the
defaultErr value is used for all chemical shifts.

The return value is a sequence of tuples: (shift_val,selection,err).
However, if tclOutput=True, a string is returned containing valid
a TCL list of { val {selection} } elements.

Data
		geminalAmbigTab = {'ALA': [], 'ARG': ['hb', 'hg', 'hd'], 'ASN': ['hb', 'hd2'], 'ASP': ['hb'], 'CYS': ['hb'], 'GLN': ['hb', 'hg', 'he2'], 'GLU': ['hb', 'hg'], 'GLY': ['ha'], 'HIS': ['hb'], 'ILE': ['hg1', 'cg1'], ...} mappings = [['', 'h', 'hn'], ['', 'co', 'c'], ['gly', 'ha3', 'ha2'], ['gly', 'ha2', 'ha1'], ['ile', 'hg13', 'hg12'], ['ile', 'hg12', 'hg11'], ['phe', 'hb3', 'hb2'], ['phe', 'hb2', 'hb1'], ['phe', 'cd', 'cd#'], ['phe', 'ce', 'ce#'], ['trp', 'hb3', 'hb2'], ['trp', 'hb2', 'hb1'], ['cys', 'hb3', 'hb2'], ['cys', 'hb2', 'hb1'], ['ser', 'hb3', 'hb2'], ['ser', 'hb2', 'hb1'], ['asn', 'hb3', 'hb2'], ['asn', 'hb2', 'hb1'], ['tyr', 'hb3', 'hb2'], ['tyr', 'hb2', 'hb1'], ...]