A Global Ramachandran Score Identifies Protein Structures with Unlikely Stereochemistry

Ramachandran plots report the distribution of the (ϕ, ψ) torsion angles of the protein backbone and are one of the best quality metrics of experimental structure models. Typically, validation software reports the number of residues belonging to “outlier,” “allowed,” and “favored” regions. While “zero unexplained outliers” can be considered the current “gold standard,” this can be misleading if deviations from expected distributions are not considered. We revisited the Ramachandran Z score (Rama-Z), a quality metric introduced more than two decades ago but underutilized. We describe a reimplementation of the Rama-Z score in the Computational Crystallography Toolbox along with an algorithm to estimate its uncertainty for individual models; final implementations are available in Phenix and PDB-REDO. We discuss the interpretation of the Rama-Z score and advocate including it in the validation reports provided by the Protein Data Bank. We also advocate reporting it alongside the outlier/allowed/favored counts in structural publications. [Display omitted] •Current standard of “zero unexplained Ramachandran outliers” can be misleading•We revisited Ramachandran Z score (Rama-Z) as a validation tool•We enhanced Rama-Z and developed an algorithm to estimate its uncertainty•We advocate reporting Rama-Z in structural publications and validation reports Counting the number of Ramachandran outliers is not sufficient for protein backbone validation. Sobolev et al. revisited the underutilized Ramachandran Z score. The authors describe its reimplementation in Phenix and PDB-REDO and showcase its utility. They advocate including it in the validation reports provided by the Protein Data Bank.