Article

NMR structure determination for larger proteins using backbone-only data.

Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Science (Impact Factor: 31.48). 02/2010; 327(5968):1014-8. DOI: 10.1126/science.1183649
Source: PubMed

ABSTRACT Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.

0 Bookmarks
 · 
126 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Three vignettes exemplify the potential of combining EM and X-ray crystallographic data with molecular dynamics (MD) simulation to explore the architecture, dynamics and functional properties of multicomponent, macromolecular complexes. The first two describe how EM and X-ray crystallography were used to solve structures of the ribosome and the Arp2/3-actin complex, which enabled MD simulations that elucidated functional dynamics. The third describes how EM, X-ray crystallography, and microsecond MD simulations of a GPCR:G protein complex were used to explore transmembrane signaling by the β-adrenergic receptor. Recent technical advancements in EM, X-ray crystallography and computational simulation create unprecedented synergies for integrative structural biology to reveal new insights into heretofore intractable biological systems.
    Current Opinion in Structural Biology 09/2014; 27C:138-148. · 8.75 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: For the first time, this research assesses monetary policy shock effects on GCC members over the last 17 years using a structural vector autoregressive (SVAR) model baseline. While GCC states peg their currency to the US dollar, the contemporaneous coefficient in the structural model indicates that for GCC countries a monetary policy instrument responds positively to unexpected increases in M2, while a monetary aggregate reacts negatively to interest rate shocks. However, our findings indicate that these countries' interest rate channel is weak. Furthermore, oil price innovation contributes to most output fluctuations in the short horizon, and M2 and Federal Fund Rates shocks are responsible for most output movements in the long horizon.
    Economic Analysis and Policy. 09/2013; 43(2):195–215.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefitted from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. © Proteins 2014;. © 2014 Wiley Periodicals, Inc.
    Proteins Structure Function and Bioinformatics 10/2014; · 3.34 Impact Factor

Full-text (2 Sources)

Download
38 Downloads
Available from
Jun 1, 2014