Literature DB >> 19564690

What can we learn by computing 13Calpha chemical shifts for X-ray protein models?

Yelena A Arnautova1, Jorge A Vila, Osvaldo A Martin, Harold A Scheraga.   

Abstract

The room-temperature X-ray structures of ubiquitin (PDB code 1ubq) and of the RNA-binding domain of nonstructural protein 1 of influenza A virus (PDB code 1ail) solved at 1.8 and 1.9 A resolution, respectively, were used to investigate whether a set of conformations rather than a single X-ray structure provides better agreement with both the X-ray data and the observed 13Calpha chemical shifts in solution. For this purpose, a set of new conformations for each of these proteins was generated by fitting them to the experimental X-ray data deposited in the PDB. For each of the generated structures, which show R and Rfree factors similar to those of the deposited X-ray structure, the 13Calpha chemical shifts of all residues in the sequence were computed at the DFT level of theory. The sets of conformations were then evaluated by their ability to reproduce the observed 13Calpha chemical shifts by using the conformational average root-mean-square-deviation (ca-r.m.s.d.). For ubiquitin, the computed set of conformations is a better representation of the observed 13Calpha chemical shifts in terms of the ca-r.m.s.d. than a single X-ray-derived structure. However, for the RNA-binding domain of nonstructural protein 1 of influenza A virus, consideration of an ensemble of conformations does not improve the agreement with the observed 13Calpha chemical shifts. Whether an ensemble of conformations rather than any single structure is a more accurate representation of a protein structure in the crystal as well as of the observed 13Calpha chemical shifts is determined by the dispersion of coordinates, in terms of the all-atom r.m.s.d. among the generated models; these generated models satisfy the experimental X-ray data with accuracy as good as the PDB structure. Therefore, generation of an ensemble is a necessary step to determine whether or not a single structure is sufficient for an accurate representation of both experimental X-ray data and observed 13Calpha chemical shifts in solution.

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Year:  2009        PMID: 19564690      PMCID: PMC2703576          DOI: 10.1107/S0907444909012086

Source DB:  PubMed          Journal:  Acta Crystallogr D Biol Crystallogr        ISSN: 0907-4449


  19 in total

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6.  Cross-validated maximum likelihood enhances crystallographic simulated annealing refinement.

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7.  Automated prediction of 15N, 13Calpha, 13Cbeta and 13C' chemical shifts in proteins using a density functional database.

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8.  A novel RNA-binding motif in influenza A virus non-structural protein 1.

Authors:  C Y Chien; R Tejero; Y Huang; D E Zimmerman; C B Ríos; R M Krug; G T Montelione
Journal:  Nat Struct Biol       Date:  1997-11

9.  Crystal structure of the unique RNA-binding domain of the influenza virus NS1 protein.

Authors:  J Liu; P A Lynch; C Y Chien; G T Montelione; R M Krug; H M Berman
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10.  Performance of density functional models to reproduce observed (13)C(alpha) chemical shifts of proteins in solution.

Authors:  Jorge A Vila; Héctor A Baldoni; Harold A Scheraga
Journal:  J Comput Chem       Date:  2009-04-30       Impact factor: 3.376

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  9 in total

1.  Assessing the fractions of tautomeric forms of the imidazole ring of histidine in proteins as a function of pH.

Authors:  Jorge A Vila; Yelena A Arnautova; Yury Vorobjev; Harold A Scheraga
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2.  Physics-based method to validate and repair flaws in protein structures.

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3.  Quantum-mechanics-derived 13Calpha chemical shift server (CheShift) for protein structure validation.

Authors:  Jorge A Vila; Yelena A Arnautova; Osvaldo A Martin; Harold A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-08       Impact factor: 11.205

4.  Limiting Values of the one-bond C-H Spin-Spin Coupling Constants of the Imidazole Ring of Histidine at High-pH.

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Review 5.  My 65 years in protein chemistry.

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6.  Assessing the accuracy of protein structures by quantum mechanical computations of 13C(alpha) chemical shifts.

Authors:  Jorge A Vila; Harold A Scheraga
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7.  Analysis of 13Calpha and 13Cbeta chemical shifts of cysteine and cystine residues in proteins: a quantum chemical approach.

Authors:  Osvaldo A Martin; Myriam E Villegas; Jorge A Vila; Harold A Scheraga
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8.  CheShift-2 resolves a local inconsistency between two X-ray crystal structures.

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9.  ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins.

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  9 in total

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