where k = (4K1+4K2) -1 . To ease this in practice, we have listed numerical k values with the most commonly used magnetic fields in Table . In addition, we provide numerical results where overestimation of τ eff values in linear approximation are corrected by fitting equation τ eff = mR • 2 + c to the MD simulation data, which improves the accuracy also with respect to the 1-timescale approximation (Fig. ). For 1-timescale approximation, we provide a simple python function, that takes R2 values and the magnetic field as input, and returns the effective rotational time by numerically solving the inverse function of Eq 5. To demonstrate the advantage of rapid analysis of molecular dynamics directly from experimental spin relaxation data, we used the 1-timescales approximation to calculate total effective correlation times from experimental R2 values available in the literature for partially disordered proteins containing 114-411 residues in Fig. . Total effective correlation times of folded regions vary between approximately 5 ns and 17 ns with a slight dependence on the size of the region. On the other hand, effective correlation times of disordered regions are approximately 1-2 ns, independently of the size of the protein or the disordered part. This suggests that dynamics of folded and disordered parts are generally uncoupled in partially disordered proteins, in line with previous results that draw similar conclusions for TonB protein using NMR experiments and MD simulations . Such analysis would not be possible with standard approaches used to interpret spin relaxation experiments because partially disordered proteins bear a complex Figure . Effective correlation times of partially disordered proteins calculated from experimental R 2 values from the literature (EN2 , Pf-SH3 , TDP-43 , TonB , δ-subunit , PDZlinker , and BRD4 ). The bottom right corner shows effective correlation times of folded and disordered regions as a function of their size.