Table 3.

Diffusion tensor analysis from R2 and R1 data at 600 MHz of NusA(353–416) and NusA(431–490)

Diffusion tensor statisticsa
	Isotropic		Axially symmetric (prolate)		Axially symmetric (oblate)		Anisotropic
	χ2(5%)	χ2exp	χ2(5%)	χ2exp	χ2(5%)	χ2exp	χ2(5%)	χ2exp
NusA(353–416)	44.2	207.6	40.0	48.5	39.7	48.5	37.0	19.0
NusA(431–490)	31.4	55.98	26.6	24.3	28.0	39.7	23.4	22.9

Diffusion tensor statisticsb
	Dzz(107s−1)	Dyy(107s−1)	Dxx(107s−1)	ζ	η	τc,eff[ns]
a χ2(5%) corresponds to the α= 0.05 confidence limit for the fit derived from 500 Monte Carlo simulations, χ2exp refers to the value of the target function used for the fit. Values of χ2(5%) and χ2exp for accepted models are shown in bold italic. An F-statistic was used to differentiate between the prolate (four parameters) and the fully asymmetric model (six parameters) for NusA(431–490). The critical values for the F-statistic with α= 0.1 amount to Fexp = 4.6 and F(10%) = 22.3, indicating that the improvement of the fit upon using the six-parameter model is not statistically relevant (Mandel et al. 1995; Dosset et al. 2000). NusA(431–490) is thus best described by a prolate axially symmetric diffusion model, NusA(353–416) by an anisotropic diffusion tensor.
b Diffusion tensor components from R2 and R1 data at 600 MHz [NusA(353–416): 33 N-HN vectors; NusA(431–490): 21 N-HN vectors] for accepted models of NusA(353–416) and NusA(431–490). For a prolate diffusion tensor (Dzz − Dyy ≥ Dyy − Dxx) the anisotropy and rhombicity are defined as ζ = 2Dzz/(Dxx+Dyy) and η = 3/2 · (Dyy − Dxx)/Dzz · ζ/(ζ − 1), respectively, and characterize the deviations from a spherical top (Fushman et al. 2004). The effective rotational correlation time is related to the diffusion tensor components via τc,eff = 1/(2Dxx+2Dyy+2Dzz). Parameter uncertainties of the diffusion parameters were taken from 500 Monte Carlo simulations.
NusA(353–416)	2.31 ± 0.05	1.73 ± 0.06	1.22 ± 0.05	1.6 ± 0.1	0.91 ± 0.19	9.5 ± 0.3
NusA(431–490)	3.11 ± 0.12	2.01 ± 0.07	2.01 ± 0.07	1.6 ± 0.1	0	7.0 ± 0.2