No. Disorder Atlas is a tool, based on population statistics, that facilitates the interpretation of intrinsic disorder predictions from two reputable algorithms - IUPred and DisEMBL. Disorder Atlas allows users to interpret significance of their results with respect to disorder predicted in the proteome to which the protein of interest belongs. Additionally, Disorder Atlas is also equipped to facilitate exploratory searches for finding one or more proteins containing a disorder feature of interest.
If your protein of interest belongs to one of the ten eukaryotic proteins supported by Disorder Atlas, but cannot be found via a protein query, this is likely due to one of the following reasons: (1) The protein was excluded due to the presence of ambiguous, undetermined/unknown, and/or unique amino acid residues (B, J, O, U, X, Z), or (2) The protein was not present in the UniProt reference proteome file at the time of sequence collection.
Yes, your protein of interest may be added as long as it belongs to one of the supported proteomes (see "Supported proteomes" for a complete list). Please contact either Michael Vincent (vincemp@umich.edu) or Santiago Schnell (schnells@umich.edu) with your request. However, please keep in mind that you may also simply run your protein sequence instead of querying by the UniProt ID.
Currently, Disorder Atlas is for academic use only. For commercial inquiries, please contact either Michael Vincent (vincemp@umich.edu) or Santiago Schnell (schnells@umich.edu). Please refer to the Disorder Atlas user agreements and policies for detailed information regarding the permitted usage of the DisorderAtlas software and service.
Importantly, users must also understand that in addition to abiding by the DisorderAtlas use policies, they must also abide by the policies of the IUPred (Dosztanyi et al., 2005) and DisEMBL (Linding et al., 2003) disorder prediction algorithms (for details, please refer to the official documentation of IUPred and DisEMBL).
As defined by Vincent et al., 2016, a PLT is a "protein length threshold" that is specific to BOTH a proteome AND a disorder prediction algorithm. The PLT is important to consider when assessing whether you should interpret the statistical significance of a CD region using the CDL (the raw length of the longest CD region) or the LCPL (the percentage of the protein's length accounted for by the CDL). The PLT was determined by calculating the protein length at which the CDL expected value begins to fall below the 25th percentile cutoff for the LCPL.
Why is this important? While the length of an intrinsically disordered region offers little insight into the purpose, function, or importance of that intrinsically disordered region, it has nevertheless become common practice to examine CD region length when using computational methods to identify, and/or assess the prevalence of, significantly long intrinsically disordered regions. However, when deeming a CD region to be significant on the basis of length alone, utilizing a fixed threshold length becomes less reliable as the primary sequence length increases. Thus, Vincent et al., 2016 determined PLTs to flag proteins having exceptionally long primary sequence lengths where the LCPL should be used instead of the CDL.