title: Landscape of Pleiotropic Proteins Causing Human Disease: Structural and System Biology Insights.
abstract: Pleiotropy is the phenomenon by which the same gene can result in multiple phenotypes. Pleiotropic proteins are emerging as important contributors to rare and common disorders. Nevertheless, little is known on the mechanisms underlying pleiotropy and the characteristic of pleiotropic proteins. We analyzed disease-causing proteins reported in UniProt and observed that 12% are pleiotropic (variants in the same protein cause more than one disease). Pleiotropic proteins were enriched in deleterious and rare variants, but not in common variants. Pleiotropic proteins were more likely to be involved in the pathogenesis of neoplasms, neurological, and circulatory diseases and congenital malformations, whereas non-pleiotropic proteins in endocrine and metabolic disorders. Pleiotropic proteins were more essential and had a higher number of interacting partners compared with non-pleiotropic proteins. Significantly more pleiotropic than non-pleiotropic proteins contained at least one intrinsically long disordered region (P < 0.001). Deleterious variants occurring in structurally disordered regions were more commonly found in pleiotropic, rather than non-pleiotropic proteins. In conclusion, pleiotropic proteins are an important contributor to human disease. They represent a biologically different class of proteins compared with non-pleiotropic proteins and a better understanding of their characteristics and genetic variants can greatly aid in the interpretation of genetic studies and drug design.
authors.affiliation: Structural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
authors.forename: Sirawit
authors.initials: S
authors.lastname: Ittisoponpisan
authors.affiliation: Structural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
authors.forename: Eman
authors.initials: E
authors.lastname: Alhuzimi
authors.affiliation: Structural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
authors.forename: Michael J E
authors.initials: MJ
authors.lastname: Sternberg
authors.affiliation: Structural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
authors.forename: Alessia
authors.initials: A
authors.lastname: David
mesh_terms: D019295:Computational Biology; D030541:Databases, Genetic; D056726:Genetic Association Studies; D058685:Genetic Pleiotropy; D020022:Genetic Predisposition to Disease; D018398:Homeodomain Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D006801:Humans; D064267:Intrinsically Disordered Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D008958:Models, Molecular; D016017:Odds Ratio; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D015398:Signal Transduction; D013329:Structure-Activity Relationship; D049490:Systems Biology / Q000379:methods; D016596:Vinculin / Q000737:chemistry / Q000235:genetics / Q000378:metabolism
chemical_list: D018398:Homeodomain Proteins; D064267:Intrinsically Disordered Proteins; D011506:Proteins; D016596:Vinculin
keywords: disordered protein region; genetic variants; human disease; pleiotropy