Hi Evette,
(1) best practices in refining against lower resolution data (~4 angstrom) > to achieve the best model, > obtain a model that fits data best under requirement that it has zero geometry violations (Ramachandran, Cbeta deviations, rotamers, CABLAM, etc..). Note, a geometry outlier (Ramachandran plot outlier, for instance) does not necessarily mean wrong. Example of a valid outlier: page 21 here: http://phenix-online.org/presentations/latest/pavel_validation.pdf However, low-resolution data is unlikely to justify outliers, that's why zero is the goal (unless there is no other strong reasons to support the outlier). > One might encounter a hypothetical situation where standard refinement > approaches gave a model with poor Ramachandran statistics. Imposing > Ramachandran restraints gave a model with improved Ramachandran statistics > but at the expense of higher Rfree. > This is likely a software issue or incorrect use by the user. Contact refinement software developers to resolve the issue. Pavel
