Hello John--
>
> I'm looking to perform a refinement with a combination of PCSs and
> paramagnetic induced RDCs. Ideally, I would like to use a single tensor object
> to describe them (i.e. have the Xax, Xrh, Euler Angles shared between PCSs and
> RDCs)
>
> If I write something as shown below, the Da would be properly set for PCS
> refinement... but this would be much too large for the RDC restraints.
> The relationship between Xax and Da should be something as follows:
> Dax = ((Xax)/(30*u0*k*T))*(Bo**2*39.46)
*If* the alignment tensors are indeed the same aside from scaling, you
can set this factor using the gyroA member of RDCPot, either the one
corresponding to PCS data, or the one for RDC data, e.g.
for M in Metals:
Para_Pot = PotList('Para_{}'.format(M))
Restraint = '{0}_NH_PCSs'.format(M)
PCS_File = 'PCS_tbl_Files/{0}_NH_PCSs.tbl'.format(M)
pcs_restr = create_RDCPot(Restraint, PCS_File, Metal_Tensors[M])
pcs_restr.setUseDistance(True)
pcs_restr.setGyroA( FACTOR )
...
However, as my colleague Guillermo Bermejo points out:
I think it might be relevant to ask whether there's motion involved
in the paramagnet (e.g., flexible tag). If so, I believe the
effective tensor involved in the PCS and RDC data might be
different, because the two types of data average differently, so
forcing the same tensor on both datasets may not be the right way to
go.
It is also possible to set as the same the orientation and rhombicity
of two different tensors - allowing the Da only to vary. There's an
example of this approach in eginput/dna_refi/ensemble.py in the
Xplor-NIH distribution.
best regards--
Charles
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