title: Proteome-wide analysis of human disease mutations in short linear motifs: neglected players in cancer?
abstract: Disease mutations are traditionally thought to impair protein functionality by disrupting the folded globular structure of proteins. However, 22% of human disease mutations occur in natively unstructured segments of proteins known as intrinsically disordered regions (IDRs). This therefore implicates defective IDR functionality in various human diseases including cancer. The functionality of IDRs is partly attributable to short linear motifs (SLiMs), but it remains an open question how much defects in SLiMs contribute to human diseases. A proteome-wide comparison of the distribution of missense mutations from disease and non-disease mutation datasets revealed that, in IDRs, disease mutations are more likely to occur within SLiMs than neutral missense mutations. Moreover, compared to neutral missense mutations, disease mutations more frequently impact functionally important residues of SLiMs, cause changes in the physicochemical properties of SLiMs, and disrupt more SLiM-mediated interactions. Analysis of these mutations resulted in a comprehensive list of experimentally validated or predicted SLiMs disrupted in disease. Furthermore, this in-depth analysis suggests that 'prostate cancer pathway' is particularly enriched for proteins with disease-related SLiMs. The contribution of mutations in SLiMs to disease may currently appear small when compared to mutations in globular domains. However, our analysis of mutations in predicted SLiMs suggests that this contribution might be more substantial. Therefore, when analysing the functional impact of mutations on proteins, SLiMs in proteins should not be neglected. Our results suggest that an increased focus on SLiMs in the coming decades will improve our understanding of human diseases and aid in the development of targeted treatments.
authors: Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany. bora.uyar@embl.de toby.gibson@embl.de.
authors: Bora
authors: B
authors: Uyar
authors: Robert J
authors: RJ
authors: Weatheritt
authors: Holger
authors: H
authors: Dinkel
authors: Norman E
authors: NE
authors: Davey
authors: Toby J
authors: TJ
authors: Gibson
mesh_terms: D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D019295:Computational Biology; D066264:Datasets as Topic; D019143:Evolution, Molecular; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009154:Mutation; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism*; D011487:Protein Conformation; D060066:Protein Interaction Maps; D020543:Proteome; D040901:Proteomics; D016415:Sequence Alignment; D015398:Signal Transduction
chemical_list: D020543:Proteome