title: Intrinsic disorder in cell-signaling and cancer-associated proteins.
abstract: The number of intrinsically disordered proteins known to be involved in cell-signaling and regulation is growing rapidly. To test for a generalized involvement of intrinsic disorder in signaling and cancer, we applied a neural network predictor of natural disordered regions (PONDR VL-XT) to four protein datasets: human cancer-associated proteins (HCAP), signaling proteins (AfCS), eukaryotic proteins from SWISS-PROT (EU_SW) and non-homologous protein segments with well-defined (ordered) 3D structure (O_PDB_S25). PONDR VL-XT predicts >or=30 consecutive disordered residues for 79(+/-5)%, 66(+/-6)%, 47(+/-4)% and 13(+/-4)% of the proteins from HCAP, AfCS, EU_SW, and O_PDB_S25, respectively, indicating significantly more intrinsic disorder in cancer-associated and signaling proteins as compared to the two control sets. The disorder analysis was extended to 11 additional functionally diverse categories of human proteins from SWISS-PROT. The proteins involved in metabolism, biosynthesis, and degradation together with kinases, inhibitors, transport, G-protein coupled receptors, and membrane proteins are predicted to have at least twofold less disorder than regulatory, cancer-associated and cytoskeletal proteins. In contrast to 44.5% of the proteins from representative non-membrane categories, just 17.3% of the cancer-associated proteins had sequence alignments with structures in the Protein Data Bank covering at least 75% of their lengths. This relative lack of structural information correlated with the greater amount of predicted disorder in the HCAP dataset. A comparison of disorder predictions with the experimental structural data for a subset of the HCAP proteins indicated good agreement between prediction and observation. Our data suggest that intrinsically unstructured proteins play key roles in cell-signaling, regulation and cancer, where coupled folding and binding is a common mechanism.
authors.affiliation: Department of Biochemistry and Biophysics, School of Molecular Biosciences, Washington State University, Pullman, WA 99164-4660, USA.
authors.forename: Lilia M
authors.initials: LM
authors.lastname: Iakoucheva
authors.forename: Celeste J
authors.initials: CJ
authors.lastname: Brown
authors.forename: J David
authors.initials: JD
authors.lastname: Lawson
authors.forename: Zoran
authors.initials: Z
authors.lastname: Obradović
authors.forename: A Keith
authors.initials: AK
authors.lastname: Dunker
mesh_terms: D000595:Amino Acid Sequence; D030562:Databases, Protein; D015195:Drug Design; D006801:Humans; D008969:Molecular Sequence Data; D009363:Neoplasm Proteins / Q000737:chemistry* / Q000235:genetics; D009369:Neoplasms / Q000378:metabolism*; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D016415:Sequence Alignment; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D009363:Neoplasm Proteins; D011506:Proteins