title: Constructing Structure Ensembles of Intrinsically Disordered Proteins from Chemical Shift Data.
abstract: Modeling the structural ensemble of intrinsically disordered proteins (IDPs), which lack fixed structures, is essential in understanding their cellular functions and revealing their regulation mechanisms in signaling pathways of related diseases (e.g., cancers and neurodegenerative disorders). Though the ensemble concept has been widely believed to be the most accurate way to depict 3D structures of IDPs, few of the traditional ensemble-based approaches effectively address the degeneracy problem that occurs when multiple solutions are consistent with experimental data and is the main challenge in the IDP ensemble construction task. In this article, based on a predefined conformational library, we formalize the structure ensemble construction problem into a least squares framework, which provides the optimal solution when the data constraints outnumber unknown variables. To deal with the degeneracy problem, we further propose a regularized regression approach based on the elastic net technique with the assumption that the weights to be estimated for individual structures in the ensemble are sparse. We have validated our methods through a reference ensemble approach as well as by testing the real biological data of three proteins, including alpha-synuclein, the translocation domain of Colocin N, and the K18 domain of Tau protein.
authors.affiliation: 1 Institute for Interdisciplinary Information Sciences, Tsinghua University , Beijing, China .
authors.forename: Huichao
authors.initials: H
authors.lastname: Gong
authors.affiliation: 1 Institute for Interdisciplinary Information Sciences, Tsinghua University , Beijing, China .
authors.forename: Sai
authors.initials: S
authors.lastname: Zhang
authors.affiliation: 2 Biostatistics and Research Decision Sciences-Asia Pacific, Merck Research Laboratory , Beijing, China .
authors.forename: Jiangdian
authors.initials: J
authors.lastname: Wang
authors.affiliation: 3 School of Life Sciences, Tsinghua University , Beijing, China .|4 MOE Key Laboratory of Bioinformatics, Tsinghua University , Beijing, China .
authors.forename: Haipeng
authors.initials: H
authors.lastname: Gong
authors.affiliation: 1 Institute for Interdisciplinary Information Sciences, Tsinghua University , Beijing, China .|4 MOE Key Laboratory of Bioinformatics, Tsinghua University , Beijing, China .
authors.forename: Jianyang
authors.initials: J
authors.lastname: Zeng
mesh_terms: D019295:Computational Biology / Q000379:methods*; D006801:Humans; D064267:Intrinsically Disordered Proteins / Q000737:chemistry*; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular; D011487:Protein Conformation
chemical_list: D064267:Intrinsically Disordered Proteins
keywords: chemical shift; elastic net; intrinsically disordered proteins; least squares