title: Molecular recognition features (MoRFs) in three domains of life.
abstract: Intrinsically disordered proteins and protein regions offer numerous advantages in the context of protein-protein interactions when compared to the structured proteins and domains. These advantages include ability to interact with multiple partners, to fold into different conformations when bound to different partners, and to undergo disorder-to-order transitions concomitant with their functional activity. Molecular recognition features (MoRFs) are widespread elements located in disordered regions that undergo disorder-to-order transition upon binding to their protein partners. We characterize abundance, composition, and functions of MoRFs and their association with the disordered regions across 868 species spread across Eukaryota, Bacteria and Archaea. We found that although disorder is substantially elevated in Eukaryota, MoRFs have similar abundance and amino acid composition across the three domains of life. The abundance of MoRFs is highly correlated with the amount of intrinsic disorder in Bacteria and Archaea but only modestly correlated in Eukaryota. Proteins with MoRFs have significantly more disorder and MoRFs are present in many disordered regions, with Eukaryota having more MoRF-free disordered regions. MoRF-containing proteins are enriched in the ribosome, nucleus, nucleolus and microtubule and are involved in translation, protein transport, protein folding, and interactions with DNAs. Our insights into the nature and function of MoRFs enhance our understanding of the mechanisms underlying the disorder-to-order transition and protein-protein recognition and interactions. The fMoRFpred method that we used to annotate MoRFs is available at http://biomine.ece.ualberta.ca/fMoRFpred/.
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6G 2V4, Canada.
authors.forename: Jing
authors.initials: J
authors.lastname: Yan
authors.affiliation: Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, 46202, USA and Indiana University School of Informatics, 410 W. 10th Street, Suite 5000, Indianapolis, IN 46202, USA. kedunker@iu.edu.
authors.forename: A Keith
authors.initials: AK
authors.lastname: Dunker
authors.affiliation: Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd. MDC07, Tampa, FL 33612, USA. vuversky@health.usf.edu and Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region 142292, Russian Federation and Biology Department, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah, 21589, Kingdom of Saudi Arabia.
authors.forename: Vladimir N
authors.initials: VN
authors.lastname: Uversky
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6G 2V4, Canada and Department of Computer Science, Virginia Commonwealth University, 401 West Main Street, Room E4225, Richmond, VA 23284, USA. lkurgan@vcu.edu; phone.
authors.forename: Lukasz
authors.initials: L
authors.lastname: Kurgan
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000032:analysis; D001105:Archaea / Q000378:metabolism*; D001419:Bacteria / Q000378:metabolism*; D056890:Eukaryota / Q000378:metabolism*; D063990:Gene Ontology; D064267:Intrinsically Disordered Proteins / Q000737:chemistry*; D008969:Molecular Sequence Data
chemical_list: D000596:Amino Acids; D064267:Intrinsically Disordered Proteins