Efficient translation of mRNAs in influenza A virus-infected cells is independent of the viral 5' untranslated region.

We test the hypothesis that the translation machinery in cells infected by influenza A virus efficiently translates only mRNAs that possess the influenza viral 5' untranslated region (5'-UTR) by introducing mRNAs directly into the cytoplasm of infected cells. This strategy avoids effects due to the inhibition of the nuclear export of cellular mRNAs mediated by the viral NS1 protein. In one approach, we transfect in vitro synthesized mRNAs into infected cells and demonstrate that these mRNAs are efficiently translated whether or not they possess the influenza viral 5'-UTR. In the second approach, an mRNA is synthesized endogenously in the cytoplasm of influenza A virus infected cells by a constitutively expressed T7 RNA polymerase. Although this mRNA is uncapped and lacks the influenza viral 5'-UTR sequence, it is efficiently translated in infected cells via an internal ribosome entry site. We conclude that the translation machinery in influenza A virus infected cells is capable of efficiently translating all mRNAs and that the switch from cellular to virus-specific protein synthesis that occurs during infection results from other processes.

Protein structural domain parsing by consensus reasoning over multiple knowledge sources and methods.

Domain parsing, or the detection of signals of protein structural domains from sequence data, is a complex and difficult problem. If carried out reliably it would be a powerful interpretive and predictive tool for genomic and proteomic studies. We report on a novel approach to domain parsing using consensus techniques based on Hidden Markov Models (HMMs) and BLAST searches built from a training set of 1471 continuous structural domains from the Dali Domain Dictionary (DDD). Validation on an independent test sample of family-matched structural domain sequences from the Scop database yields a consensus prediction performance rate of 75.5%, well above the 58% obtained by simple agreement of methods.

Solution NMR structure and folding dynamics of the N terminus of a rat non-muscle alpha-tropomyosin in an engineered chimeric protein.

Tropomyosin is an alpha-helical coiled-coil protein that aligns head-to-tail along the length of the actin filament and regulates its function. The solution structure of the functionally important N terminus of a short 247-residue non-muscle tropomyosin was determined in an engineered chimeric protein, GlyTM1bZip, consisting of the first 19 residues of rat short alpha-tropomyosin and the last 18 residues of the GCN4 leucine zipper. A gene encoding GlyTM1bZip was synthesized, cloned and expressed in Escherichia coli. Triple resonance NMR spectra were analyzed with the program AutoAssign to assign its backbone resonances. Multidimensional nuclear Overhauser effect spectra, X-filtered spectra and (3)J(H(N)-H(alpha)) scalar coupling were analyzed using AutoStructure. This is the first application of this new program to determine the three-dimensional structure of a symmetric homodimer and a structure not previously reported. Residues 7-35 in GlyTM1bZip form a coiled coil, but neither end is helical. Heteronuclear (15)N-(1)H nuclear Overhauser effect data showed that the non-helical N-terminal residues are flexible. The (13)C' chemical shifts of the coiled-coil backbone carbonyl groups in GlyTM1bZip showed a previously unreported periodicity, where resonances arising from residues at the coiled-coil interface in a and d positions of the heptad repeat were displaced relatively upfield and those arising from residues in c positions were displaced relatively downfield. Heteronuclear single quantum coherence spectra, collected as a function of temperature, showed that cross-peaks arising from the alpha-helical backbone and side-chains at the coiled-coil interface broadened or shifted with T(M) values approximately 20 degrees C lower than the loss of alpha-helix measured by circular dichroism, suggesting the presence of a folding intermediate. The side-chain of Ile14, a residue essential for binding interactions, exhibited multiple conformations. The conformational flexibility of the N termini of short tropomyosins may be important for their binding specificity.

SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics.

High-throughput structural proteomics is expected to generate considerable amounts of data on the progress of structure determination for many proteins. For each protein this includes information about cloning, expression, purification, biophysical characterization and structure determination via NMR spectroscopy or X-ray crystallography. It will be essential to develop specifications and ontologies for standardizing this information to make it amenable to retrospective analysis. To this end we created the SPINE database and analysis system for the Northeast Structural Genomics Consortium. SPINE, which is available at bioinfo.mbb.yale.edu/nesg or nesg.org, is specifically designed to enable distributed scientific collaboration via the Internet. It was designed not just as an information repository but as an active vehicle to standardize proteomics data in a form that would enable systematic data mining. The system features an intuitive user interface for interactive retrieval and modification of expression construct data, query forms designed to track global project progress and external links to many other resources. Currently the database contains experimental data on 985 constructs, of which 740 are drawn from Methanobacterium thermoautotrophicum, 123 from Saccharomyces cerevisiae, 93 from Caenorhabditis elegans and the remainder from other organisms. We developed a comprehensive set of data mining features for each protein, including several related to experimental progress (e.g. expression level, solubility and crystallization) and 42 based on the underlying protein sequence (e.g. amino acid composition, secondary structure and occurrence of low complexity regions). We demonstrate in detail the application of a particular machine learning approach, decision trees, to the tasks of predicting a protein's solubility and propensity to crystallize based on sequence features. We are able to extract a number of key rules from our trees, in particular that soluble proteins tend to have significantly more acidic residues and fewer hydrophobic stretches than insoluble ones. One of the characteristics of proteomics data sets, currently and in the foreseeable future, is their intermediate size ( approximately 500-5000 data points). This creates a number of issues in relation to error estimation. Initially we estimate the overall error in our trees based on standard cross-validation. However, this leaves out a significant fraction of the data in model construction and does not give error estimates on individual rules. Therefore, we present alternative methods to estimate the error in particular rules.

Lipari-Szabo mapping: A graphical approach to Lipari-Szabo analysis of NMR relaxation data using reduced spectral density mapping.

In this paper, we explore connections between the Lipari-Szabo formalism and reduced spectral density mapping, and show how spectral density estimates can be associated with Lipari-Szabo parameters via a simple geometric construction which we call Lipari-Szabo mapping. This relationship can be used to estimate Lipari-Szabo parameters from spectral density estimates without the need for nonlinear optimization, and to perform 'model selection' in a graphical manner. The Lipari-Szabo map also provides insight into the Lipari-Szabo model, and allows us to determine when a given set of experimental spectral densities are inconsistent with the Lipari-Szabo formalism. Practical applications of Lipari-Szabo mapping in conjunction with more traditional analysis methods are discussed.

Protein NMR spectroscopy in structural genomics.

Protein NMR spectroscopy provides an important complement to X-ray crystallography for structural genomics, both for determining three-dimensional protein structures and in characterizing their biochemical and biophysical functions.

A Bayesian statistical method for the detection and quantification of rotational diffusion anisotropy from NMR relaxation data.

It has recently become more widely appreciated that the presence of rotational diffusional anisotropy in proteins and other macromolecules can have a significant affect on the interpretation of NMR relaxation data in terms of molecular motion. In this paper, we show how commonly used NMR relaxation data (R(1), R(2), and NOE) obtained at two spectrometer frequencies can be analyzed using a Bayesian statistical approach to reliably detect and quantify the degree of rotational diffusion anisotropy. Our approach differs from previous methods in that it does not make assumptions concerning the internal motions experienced by the residues which are used to quantify the diffusion anisotropy, but rather averages the results over all internal motions consistent with the data. We demonstrate our method using synthetic data corresponding to isotropic, axially symmetric anisotropic, and fully asymmetric anisotropic rotational diffusion, as well as experimental NMR data. We compare the Bayesian statistical approach with a widely used method for extracting tumbling parameters using both synthetic and experimental data. While it can be difficult to separate the effects of chemical exchange from rotational anisotropy using this "standard" method, these effects are readily separated using Bayesian statistics. In addition, we find that the Bayesian statistical approach requires considerably less CPU time than an equivalent standard analysis.

Partial NMR assignments for uniformly (13C, 15N)-enriched BPTI in the solid state.

We demonstrate that high-resolution multidimensional solid state NMR methods can be used to correlate many backbone and side chain chemical shifts for hydrated micro-crystalline U-13C,15N Basic Pancreatic Trypsin Inhibitor (BPTI), using a field strength of 800 MHz for protons, magic angle sample spinning rates of 20 kHz and proton decoupling field strengths of 140 kHz. Results from two homonuclear transfer methods, radio frequency driven dipolar recoupling and spin diffusion, were compared. Typical 13C peak line widths are 0.5 ppm, resulting in Calpha-Cbeta and Calpha-CO regions that exhibit many resolved peaks. Two-dimensional carbon-carbon correlation spectra of BPTI have sufficient resolution to identify and correlate many of the spin systems associated with the amino acids. As a result, we have been able to assign a large number of the spin systems in this protein. The agreement between shifts measured in the solid state and those in solution is typically very good, although some shifts near the ion binding sites differ by at least 1.5 ppm. These studies were conducted with approximately 0.2 to 0.4 micromol of enriched material; the sensitivity of this method is apparently adequate for other biological systems as well.

Solution NMR evidence for a cis Tyr-Ala peptide group in the structure of [Pro93Ala] bovine pancreatic ribonuclease A.

Proline peptide group isomerization can result in kinetic barriers in protein folding. In particular, the cis proline peptide conformation at Tyr92-Pro93 of bovine pancreatic ribonuclease A (RNase A) has been proposed to be crucial for chain folding initiation. Mutation of this proline-93 to alanine results in an RNase A molecule, P93A, that exhibits unfolding/refolding kinetics consistent with a cis Tyr92-Ala93 peptide group conformation in the folded structure (Dodge RW, Scheraga HA, 1996, Biochemistry 35:1548-1559). Here, we describe the analysis of backbone proton resonance assignments for P93A together with nuclear Overhauser effect data that provide spectroscopic evidence for a type VI beta-bend conformation with a cis Tyr92-Ala93 peptide group in the folded structure. This is in contrast to the reported X-ray crystal structure of [Pro93Gly]-RNase A (Schultz LW, Hargraves SR, Klink TA, Raines RT, 1998, Protein Sci 7:1620-1625), in which Tyr92-Gly93 forms a type-II beta-bend with a trans peptide group conformation. While a glycine residue at position 93 accommodates a type-II bend (with a positive value of phi93), RNase A molecules with either proline or alanine residues at this position appear to require a cis peptide group with a type-VI beta-bend for proper folding. These results support the view that a cis Pro93 conformation is crucial for proper folding of wild-type RNase A.

Comparison of local and global stability of an analogue of a disulfide-folding intermediate with those of the wild-type protein in bovine pancreatic ribonuclease A: identification of specific regions of stable structure along the oxidative folding pathway.

We have identified specific regions of the polypeptide chain of bovine pancreatic ribonuclease A (RNase A) that are critical for stabilizing the oxidative folding intermediate des-[40-95] (with three native disulfide bonds but lacking the fourth native Cys40-Cys95 disulfide bond) in an ensemble of largely disordered three-disulfide precursors (3S if des-[40-95]). A stable analogue of des-[40-95], viz., [C40A, C95A] RNase A, which contains three out of four native disulfide pairings, was previously found to have a three-dimensional structure very similar to that of the wild-type protein. However, it is determined here from GdnHCl denaturation experiments to have significantly reduced global stability, i.e., = 4.5 kcal /mol at 20 degrees C and pH 4.6. The local stability of [C40A, C95A] RNase A was also examined using site-specific amide (2)H/(1)H exchange measurements at pD 5.0 to determine the individual unfolding free energy of specific residues under both strongly native (12 degrees C) and more destabilizing (20 degrees C) conditions. Comparison of the relative stabilities at specific amide sites of [C40A, C95A] RNase A at both temperatures with the corresponding values for the wild-type protein at 35 degrees C corroborates previous experimental evidence that unidentified intramolecular contacts in the vicinity of the preferentially formed native one-disulfide (C65-C72) loop are crucial for stabilizing early folding intermediates, leading to des-[40-95]. Moreover, values of for residues at or near the third alpha-helix, and in part of the second beta-sheet of [C40A, C95A] RNase A, indicate that these two regions of regular backbone structure contribute to stabilizing the global chain fold of the des-[40-95] disulfide-folding intermediate in the wild-type protein. More significantly, we have identified numerous specific residues in the first alpha-helix and the first beta-sheet of the protein that are stabilized in the final step of the major oxidative regeneration pathway of RNase A (des-[40-95] --> N).

Automated analysis of NMR assignments and structures for proteins.

Recent developments in protein NMR technology have provided spectral data that are highly amenable to analysis by advanced computer software systems. Specific data collection strategies, coupled with these computer programs, allow automated analysis of extensive backbone and sidechain resonance assignments and three-dimensional structures for proteins of 50 to 200 amino acids.

Estimation of dynamic parameters from NMR relaxation data using the Lipari-Szabo model-free approach and Bayesian statistical methods.

In order to analyze NMR relaxation data in terms of parameters which describe internal motion, one must first obtain a description of the overall tumbling of the macromolecule in solution. Methods currently used to estimate these global parameters may not always provide reliable estimates of their values and uncertainties. In this paper, we present a general data analysis formalism based on products of Bayesian marginal probability densities which can be used to efficiently combine the information content from multiple experiments, such as R(1), R(2), and NOE data collected at multiple magnetic field strengths, or data from cross-correlation or rotating frame relaxation dispersion experiments. Our approach allows the estimation of global tumbling and internal dynamical parameters and their uncertainties without some of the assumptions which are made in the commonly-used methods for model-selection and global parameter estimation. Compared to an equivalent classical statistical approach, the Bayesian method not only is more computationally efficient, but also provides greater insight into the information content of the data. We demonstrate that this approach can be used to estimate both the isotropic rotational correlation time in the context of the original and "extended" Lipari-Szabo formalisms [Lipari & Szabo, J. Am. Chem. Soc. 1982, 104, 4546; Clore et al., J. Am. Chem. Soc. 1990, 112, 4989], as well as the rotational diffusion coefficients for axially symmetric anisotropic tumbling.

Sensitivity-enhanced sim-CT HMQC PFG-HBHA(CO)NH and PFG-CBCA(CO)NH triple-resonance experiments.

Short transverse relaxation times of Calpha and Cbeta single-quantum coherences reduce the sensitivity of triple-resonance experiments involving transfers of Calpha/Cbeta or Halpha/Hbeta coherences. Multiple-quantum line-narrowing techniques improve the relaxation properties of 13C coherences, thereby increasing the sensitivity of the experiment. In the present work, we describe PFG-CBCA(CO)NH and PFG-HBHA(CO)NH experiments that utilize heteronuclear multiple-quantum coherences in a simultaneous constant-time period to obtain completely decoupled spectra with improved sensitivity. Results indicate that approximately 30% of cross peaks show an average enhancement of approximately 15% in the CBCA(CO)NH experiment. In the related HBHA(CO)NH experiment, approximately 97% of the cross peaks show an average enhancement of approximately 40%.

RNA binding by the novel helical domain of the influenza virus NS1 protein requires its dimer structure and a small number of specific basic amino acids.

The RNA-binding/dimerization domain of the NS1 protein of influenza A virus (73 amino acids in length) exhibits a novel dimeric six-helical fold. It is not known how this domain binds to its specific RNA targets, one of which is double-stranded RNA. To elucidate the mode of RNA binding, we introduced single alanine replacements into the NS1 RNA-binding domain at specific positions in the three-dimensional structure. Our results indicate that the dimer structure is essential for RNA binding, because any alanine replacement that causes disruption of the dimer also leads to the loss of RNA-binding activity. Surprisingly, the arginine side chain at position 38, which is in the second helix of each monomer, is the only amino-acid side chain that is absolutely required only for RNA binding and not for dimerization, indicating that this side chain probably interacts directly with the RNA target. This interaction is primarily electrostatic, because replacement of this arginine with lysine had no effect on RNA binding. A second basic amino acid, the lysine at position 41, which is also in helix 2, makes a strong contribution to the affinity of binding. We conclude that helix 2 and helix 2', which are antiparallel and next to each other in the dimer conformation, constitute the interaction face between the NS1 RNA-binding domain and its RNA targets, and that the arginine side chain at position 38 and possibly the lysine side chain at position 41 in each of these antiparallel helices contact the phosphate backbone of the RNA target.