Intrinsically disordered or unstructured regions in proteins are both common and biologically important, particularly in regulation, signaling, and modulating intermolecular recognition processes. From a practical point of view, however, such disordered regions often can pose significant challenges for crystallization. Disordered regions are also detrimental to NMR spectral quality, complicating the analysis of resonance assignments and three-dimensional protein structures by NMR methods. The DisMeta Server has been used by Northeastern Structural Genomics (NESG) consortium as a primary tool for construct design and optimization in preparing samples for both NMR and crystallization studies. It is a meta-server that generates a consensus analysis of eight different sequence-based disorder predictors to identify regions that are likely to be disordered. DisMeta also identifies predicted secretion signal peptides, transmembrane segments, and low-complexity regions. Identification of disordered regions, by either experimental or computational methods, is an important step in the NESG structure production pipeline, allowing the rational design of protein constructs that have improved expression and solubility, improved crystallization, and better quality NMR spectra.