The nucleocapsid protein (N) of the severe acute respiratory syndrome coronavirus (SARS-CoV) packages the viral genomic RNA and is crucial for viability. However, the RNA-binding mechanism is poorly understood. We have shown previously that the N protein contains two structural domains-the N-terminal domain (NTD; residues 45 to 181) and the C-terminal dimerization domain (CTD; residues 248 to 365)-flanked by long stretches of disordered regions accounting for almost half of the entire sequence. Small-angle X-ray scattering data show that the protein is in an extended conformation and that the two structural domains of the SARS-CoV N protein are far apart. Both the NTD and the CTD have been shown to bind RNA. Here we show that all disordered regions are also capable of binding to RNA. Constructs containing multiple RNA-binding regions showed Hill coefficients greater than 1, suggesting that the N protein binds to RNA cooperatively. The effect can be explained by the "coupled-allostery" model, devised to explain the allosteric effect in a multidomain regulatory system. Although the N proteins of different coronaviruses share very low sequence homology, the physicochemical features described above may be conserved across different groups of Coronaviridae. The current results underscore the important roles of multisite nucleic acid binding and intrinsic disorder in N protein function and RNP packaging.Severe acute respiratory syndrome (SARS) is the first pandemic of the 21st century that spread to multiple nations, with a fatality rate of ca. 8%. The disease is caused by a novel SARS-associated coronavirus (SARS-CoV) closely related to the group II coronaviruses, which include the human coronavirus OC43 and murine hepatitis virus (6, 18). Traditional antiviral treatments have had little success against SARS during the outbreak, and vaccines have yet to be developed (35).Coronaviruses are positive-sense single-stranded RNA (ssRNA) viruses. The coronavirus genomic RNA is encapsidated into a helical capsid by the nucleocapsid (N) protein, which is one of the most abundant coronavirus proteins (19). The N protein has nonspecific binding activity toward nucleic acids, including ssRNA, single-stranded DNA, and double-stranded DNA (33). It can also act as an RNA chaperone (39). However, the mechanism of binding of the N protein to nucleic acids is poorly understood.The SARS-CoV N protein is a homodimer composed of 422 amino acids (aa) in each chain. The N protein can be divided into two structural domains interspersed with disordered (unstructured) regions (Fig. 1A) (2). The N-terminal domain (NTD; also called RBD) serves as a putative RNA-binding domain, while the C-terminal domain (CTD; also called DD) is a dimerization domain (13,36). Both the NTD and the CTD bind to nucleic acids through electropositive regions on their surfaces (3, 13, 32). All coronaviruses share similar domain architectures at both the sequence and structure levels. No structure of N protein or any of its domains in complex with nucleic acids is ava...

The C-terminal domain (CTD) of the severe acute respiratory syndrome coronavirus (SARS-CoV) nucleocapsid protein (NP) contains a potential RNA-binding region in its N-terminal portion and also serves as a dimerization domain by forming a homodimer with a molecular mass of 28 kDa. So far, the structure determination of the SARS-CoV NP CTD in solution has been impeded by the poor quality of NMR spectra, especially for aromatic resonances. We have recently developed the stereo-array isotope labeling (SAIL) method to overcome the size problem of NMR structure determination by utilizing a protein exclusively composed of stereo- and regio-specifically isotope-labeled amino acids. Here, we employed the SAIL method to determine the high-quality solution structure of the SARS-CoV NP CTD by NMR. The SAIL protein yielded less crowded and better resolved spectra than uniform (13)C and (15)N labeling, and enabled the homodimeric solution structure of this protein to be determined. The NMR structure is almost identical with the previously solved crystal structure, except for a disordered putative RNA-binding domain at the N-terminus. Studies of the chemical shift perturbations caused by the binding of single-stranded DNA and mutational analyses have identified the disordered region at the N-termini as the prime site for nucleic acid binding. In addition, residues in the beta-sheet region also showed significant perturbations. Mapping of the locations of these residues onto the helical model observed in the crystal revealed that these two regions are parts of the interior lining of the positively charged helical groove, supporting the hypothesis that the helical oligomer may form in solution.

No abstract

No abstract

No abstract

Because this method limits the initial number of suspicious mass regions while retaining high sensitivity, it may be applicable to clinically usable computer-aided diagnosis schemes.

The purpose of this study is to explore the potential application of region conspicuity as an index of difficulty for mass detection using computer-assisted diagnosis (CAD) schemes on mammograms and to assess the performance improvement of our own CAD scheme by incorporation of conspicuity as well as other features related to tissue background. Two independent image databases that contained 978 images were used to train and test the CAD scheme. Using a growth algorithm of three adaptive topographic layers, 592 positive mass regions and another 3,790 suspicious but actually negative regions were initially selected from these two image databases. For each region, a set of 2 1 image features was computed, including five features from surrounding tissue background. Using these image features as input data, an artificial neural network was employed to classify regions as positive or negative for masses. Both the area under the ROC curve and the false-positive detection rate at 80% sensitivity were used as indices of CAD performance. The experimental results demonstrated that region conspicuity could be used as an effective index of identification difficulty of suspicious mass regions. The performance of our own CAD scheme improves monotonously and substantially as the regions with lower conspicuity are removed from the training and testing databases. The experimental results also revealed that region conspicuity and other relevant image features extracted from surrounding tissue background carried independent, hence potentially useful, information in the identification of suspicious mass regions. In this experiment, a five percent increase in the area under the ROC curve, or a 1 5 percent reduction in the false-positive detection rate at a given sensitivity of 80 percent, was obtained after incorporating five tissue background-related features as input to the scheme.

No abstract