Difference between revisions of "Matplotlib DPL94 R1rho R2eff"

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(Improved figure placement - they now stay in their section.)
(→‎Figures: Switched to parameter templates and cleaned up the maths.)
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Ref [2], Equation 27.
 
Ref [2], Equation 27.
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Here the calculated value is noted as: $R_{eff}$. : Equation 27: $ R_{eff} = R_{1\rho} / sin^2(\theta) - R_1 / tan^2(\theta) = R^{0}_2 + R_{ex} $. <br>
+
Here the calculated value is noted as: {{:Reff}} = {{:R1rho}} / sin<sup>2</sup>(θ) - {{:R1}} / tan<sup>2</sup>(θ) = {{:R2zero}} + {{:Rex}}, where {{:R2zero}} refers to {{:R1rhoprime}} as seen at [[DPL94]]
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Where $R^{0}_2$ refers to $R_{1\rho '}$ as seen at [[DPL94]]
 
  
 
Ref [3], Equation 20.
 
Ref [3], Equation 20.
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Here the calculated value is noted as: $R_2$: $R_2 = R_{1\rho} / sin^2(\theta) - R_1 / tan^2(\theta)$ <br>
+
Here the calculated value is noted as: {{:R2}} = {{:R1rho}} / sin<sup>2</sup>(θ) - {{:R1}} / tan<sup>2</sup>(θ).  Figure 11+16, would be the reference.
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Figure 11+16, would be the reference.
 
  
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Ref [4], Equation 43. $R_{eff} = R_{1\rho} / sin^2(\theta) - R_1 / tan^2(\theta)$
+
Ref [4], Equation 43. {{:Reff}} = {{:R1rho}} / sin<sup>2</sup>(θ) - {{:R1}} / tan<sup>2</sup>(θ).
  
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Ref [5], Material and Methods, page 740. Here the calculated value is noted as: $R_2: R_2 = R^{0}_2 + R_{ex}$. <br>
+
Ref [5], Material and Methods, page 740. Here the calculated value is noted as: {{:R2}}: {{:R2}} = {{:R2zero}} + {{:Rex}}. Figure 4 would be the wished graphs.
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Figure 4 would be the wished graphs.
 
  
  

Revision as of 14:26, 3 November 2015

About

The production to these figures relates to the Suppport Request:
sr #3124: Grace graphs production for R1rho analysis with R2_eff as function of Omega_eff

References

Refer to the manual for parameter explanation

  1. Evenäs, J., Malmendal, A. & Akke, M. (2001). Dynamics of the transition between open and closed conformations in a calmodulin C-terminal domain mutant. Structure 9, 185–195 DOI
  2. Kempf, J.G. & Loria, J.P. (2004). Measurement of intermediate exchange phenomena. Methods Mol. Biol. 278, 185–231 DOI
  3. Palmer, A.G. & Massi, F. (2006). Characterization of the dynamics of biomacromolecules using rotating-frame spin relaxation NMR spectroscopy. Chem. Rev. 106, 1700–1719 DOI
  4. Palmer, A.G., Kroenke, C.D. & Loria, J.P. (2001). Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Meth. Enzymol. 339 DOI
  5. Francesca Massi, Michael J. Grey, Arthur G. Palmer III* (2005) Microsecond timescale backbone conformational dynamics in ubiquitin studied with NMR R1ρ relaxation experiments, Protein science DOI

Figures

Ref [1], Figure 1.b. The bell-curves As function of angle calculation.

Ref [1], Figure 1.c. The wanted graph. No clear "name" for the calculated parameter.

Ref [2], Equation 27. Here the calculated value is noted as: Reff = R1ρ / sin2(θ) - R1 / tan2(θ) = R20 + Rex, where R20 refers to R1ρ' as seen at DPL94

Ref [3], Equation 20. Here the calculated value is noted as: R2 = R1ρ / sin2(θ) - R1 / tan2(θ). Figure 11+16, would be the reference.

Ref [4], Equation 43. Reff = R1ρ / sin2(θ) - R1 / tan2(θ).

Ref [5], Material and Methods, page 740. Here the calculated value is noted as: R2: R2 = R20 + Rex. Figure 4 would be the wished graphs.


A little table of conversion then gives 

Relax equation    |   Relax store    | Articles
---------------------------------------------------------------
R1rho'                spin.r2             R^{0}_2 or Bar{R}_2
Fitted pars           Not stored          R_ex
R1rho                 spin.r2eff          R1rho
R_1                   spin.ri_data['R1']  R_1 or Bar{R}_1

The parameter is called R_2 or R_eff in the articles. Since reff is not used in relax, this could be used?

A description could be:

  • The effective rate
  • The effective transverse relaxation rate constant
  • The effective relaxation rate constant.

Make graphs

The outcome

Figure 1
Figure 2
Figure 3

To run

relax -p r1rhor2eff.py

Code

Code: r1rhor2eff.py Python script

Bugs ?

Do you get an error with matplotlib about dateutil? Then see Matplotlib_dateutil_bug

See also

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