Hi,

I'm trying to follow the protocol described in White et al., Structural principles of SNARE complex recognition by the AAA+ protein NSF e-life 2018 

https://elifesciences.org/articles/38888

Here is the pertinent paragraph:

"To improve the Ramachandran statistics and geometry of the models, a two-parameter grid search of real space refinements was performed in which 3–5 macrocycles of global minimization and local grid search were performed in the presence of secondary structure restraints. First, a grid refinement search was performed for both target functions with around 1000 refinements each. For the emsley target function, rama_weight and scale_allowed were varied from 0.01 to 300; for the oldfield target function, a grid of refinements was performed over plot_cutoff values from 0.01 to 1.0 and weight_scale values from 0.1 to 300. Results were judged empirically and based primarily on a balance between CCmask and a minimal fraction of residues flagged by the program CaBLAM (Richardson et al., 2018) because focusing on the fraction of residues with favored CCmask and Ramachandran statistics alone often resulted in unrealistic models with serious problems (Figure 12, Table 2)."

There are no differences in the refined structures regardless of what parameters I change. Attached is the input file I use for phenix.real_space_refine (1.18.2​). Altering the oldfield weight_scale (0.1 to 300) and plot_cutoff (0.1 to 0.5) makes no difference. Any help is highly appreciated. 

Best wishes,
Reza