title: Retro-MoRFs: identifying protein binding sites by normal and reverse alignment and intrinsic disorder prediction.
abstract: Many cell functions in all living organisms rely on protein-based molecular recognition involving disorder-to-order transitions upon binding by molecular recognition features (MoRFs). A well accepted computational tool for identifying likely protein-protein interactions is sequence alignment. In this paper, we propose the combination of sequence alignment and disorder prediction as a tool to improve the confidence of identifying MoRF-based protein-protein interactions. The method of reverse sequence alignment is also rationalized here as a novel approach for finding additional interaction regions, leading to the concept of a retro-MoRF, which has the reversed sequence of an identified MoRF. The set of retro-MoRF binding partners likely overlap the partner-sets of the originally identified MoRFs. The high abundance of MoRF-containing intrinsically disordered proteins in nature suggests the possibility that the number of retro-MoRFs could likewise be very high. This hypothesis provides new grounds for exploring the mysteries of protein-protein interaction networks at the genome level.
authors.affiliation: Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA; E-Mails: binxue@iupui.edu (B.X.); kedunker@iupui.edu (A.K.D.).
authors.forename: Bin
authors.initials: B
authors.lastname: Xue
authors.forename: A Keith
authors.initials: AK
authors.lastname: Dunker
authors.forename: Vladimir N
authors.initials: VN
authors.lastname: Uversky
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites; D064267:Intrinsically Disordered Proteins / Q000737:chemistry* / Q000378:metabolism; D008969:Molecular Sequence Data; D011485:Protein Binding; D016415:Sequence Alignment / Q000379:methods*
chemical_list: D064267:Intrinsically Disordered Proteins