RDCvis & KiNG

 This page is under construction as of November 1st, 2011.  

Draft Outline

Intro to RDCvis

Visualizing the RDC curves in their structural context, especially when combined with other structure quality visualizations allows users to easily identify and study areas of their models which need improvement.

Software for generating RDC visualizations, dubbed RDCvis and built into KiNG (Chen, 2009), requires a PDB format coordinate file and an NMR restraints file (in CNS format) with RDC data.  RDCvis outputs the RDC visualizations in kinemage format (Richardson, 1992), as a standalone file that is routinely appended onto an existing multi-model kinemage for viewing in KiNG. These curves plotted using the kinemage graphics format, take advantage of the powerful and extensive infrastructure that already exists for manipulating and viewing kinemages in Mage, KiNG, and KinImmerse (Richardson, 1992; Chen, 2009; Block, 2009).

RDCvis draws RDC curves by using singular value decomposition (SVD) (losonczi1999) to calculate a Saupe alignment matrix (saupe1968) from the RDCs.  The method is described in more detail in the Supporting Information.

RDCvis allows users to visualize and interact with the possible RDC curve shapes. 

IMAGE These varied curve shapes arise from the intersection of the surface representing the possible solutions for the RDC equation with the sphere representing the possible positions for a given internuclear bond vector.  IMAGE

Getting RDCvis to work in KiNG

Walk-through of loading RDCs

What you need -

a) MolProbity multimodel-multicrit kinemage

Multiple models visualized at once with the local geometric and steric validation criteria from the Richardson lab displayed at each residue.

b) .tbl file (note on acceptible formats

One note is that a significant barrier to using RDCvis is the lack of consistency in the deposited NMR restraints files.  A more strictly defined standard data-file format would make RDCvis more straightforward to use and thus routinely useful to a wider community. 

Co-centering tool

Translational overlap while maintaining orientation in order to investigate the match of the internuclear vector across all models in the ensemble to the target curves of the measured RDC

Using RDCvis to analyze RDCs in their local context

Analysis with one or multiple RDCs

Just like others have predicted, it is better with multiple RDCs

Even if the tensors are very similar, it can still give useful data to have two RDCs

Philosophically similar to crystallography in that it is looking at validation crteria mapped on a model while also looking at the experimental data (in this case RDCs, in xray it is the density)

Patterns to look for

Orientation Dependent Variability

Contribution from both the orientation of the local structure to the RDC visualized and the RDC visualized to the field.

Implications for flexibility of the internuclear vector

One Curve Rule

It can never be on both...

Searching for these systematic errors

Special case where target curves overlap

Error Model Issues

The error model is too tight

The error model is not representative of the error in measurement

At the poles it isn't particularly helpful

Using other helpful data

Talos+ restraints

Use of Talos+ restraints to assist in restraining the backbone appropriately

Order parameters

Helpful for understanding the potential variability actually observed at a residue (and perhaps making the argument for not using as many restraints or explaining why the behavior of the ensemble of models at that point is peculiar)

Sterics and geometry from MolProbity

Orthogonal criteria that can give the user an inditation of the local quality of the ensemble of models and identify areas where fixes may need to be made.