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Internal links to DASHA.
* Modelfree4 (with or without the Fast-Modelfree GUI interface)
* Dasha[[DASHA]]
* Tensor2 and
* DYNAMICS
# Find an initial diffusion tensor estimate (you can do this in relax by only using model m0). This requires all non-mobile residues and side chain spins to be excluded, and this can be problematic. See the [d'Auvergne and Gooley, 2008b] paper for an example of the catastrophic failure that this initial estimate can result in. Or the bacteriorhodopsin fragment of [Orekhov et al., 1999] where this complete failure was earlier demonstrated.
# Optimise all of the model-free models from m0 to m9. This requires high precision optimisation, for a comparison of all the softwares see the [d'Auvergne and Gooley, 2008a] model-free optimisation paper. Only relax and Dasha [[DASHA]] implement the full range of model-free models, though the models m6, m7, and m8 cannot be used if only single field strength data is used (m6 is the original 2-time scale motion model of [Clore et al., 1990]).
# Eliminate failed models (this is only available in relax). See the [d'Auvergne and Gooley, 2006] model elimination paper.
# Select the best model-free model for each spin system. This again requires precision modern techniques, with the best being AIC model select (see the [d'Auvergne and Gooley, 2003] model-free model selection paper). If you are unaware that ANOVA statistics for model selection (hypothesis testing via chi-squared, F- and t-tests) was abandoned by the field of model selection over 100 years ago (a field which makes the NMR field look very, very small), then you should really look at that paper.
=== Recommendation ===
Finally, you will probably find it much easier to spend the 7-8 days collecting data at another field strength than to implement the [[#Protocol|protocol]] in a relax, Modelfree4, or Dasha [[DASHA]] script (or via multiple iterations of the GUI programs), as well as study all of the relevant literature to understand all of the types of failures than only occurs with single field strength data. With multiple field strength data you can perform [https://gna.org/users/semor Sebastien Morin's] consistency testing analysis in relax[Morin and Gagné, 2009] (see http://www.nmr-relax.com/manual/Consistency_testing.html). That way you can see if your per-experiment temperature calibration and
per-experiment temperature control techniques have works sufficiently well (http://www.nmr-relax.com/manual/Temperature_control_calibration.html) and if you have used long enough recycle delays. Collecting data at a second field would probably save you significant amounts of time, and has the additional benefit that it would guarantee that the dynamics you see at the end will be real. I cannot emphasize enough how important it is to collect data at multiple fields, most importantly the NOE and R<sub>2</sub> data.
