The emergence of structure-determination initiatives that employ high-throughput protein crystallography emphasizes the need to establish quality-control methods for screening the resulting models prior to deposition with the public data banks. An in-house database of 26 new protein structures, associated diffraction data and high-quality experimentally determined electron-density maps have been used to develop (i) a set of minimal global quality criteria that a structure must meet before the refinement may be considered completed and (ii) a reliable set of indicators for detecting local errors in protein structures. These criteria have been applied to detecting local errors to a set of structures recently deposited in the Protein Data Bank and it is estimated that about 3% of amino acids are incorrectly modeled.