The nucleotide and partial amino acid sequences of rat fetuin

Fetuins are among the major plasma proteins, yet their biological role has remained elusive. Here we report the molecular cloning of rat fetuin and the sequence analysis of a full-length clone, RF619 of 1456 bp with an open reading frame of 1056 bp encoding 352 amino acid residues. The coding part of RF619 was identical with the cDNA sequence of the natural inhibitor of the insulin receptor tyrosine kinase from rat (pp63) except for four substitutions and a single base insertion causing divergence of the predicted protein sequences. Partial amino acid sequences of rat plasma fetuin were in agreement with the predictions based on the RF619 cDNA. Purified rat fetuin inhibited the insulin receptor tyrosine kinase in vitro. Therefore, we conclude that RF619 and pp63 cDNA encode the same protein, i.e. authentic rat fetuin which is a functional tyrosine kinase inhibitor

Application of multiple statistical tests to enhance mass spectrometry-based biomarker discovery

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry-based biomarker discovery has long been hampered by the difficulty in reconciling lists of discriminatory peaks identified by different laboratories for the same diseases studied. We describe a multi-statistical analysis procedure that combines several independent computational methods. This approach capitalizes on the strengths of each to analyze the same high-resolution mass spectral data set to discover consensus differential mass peaks that should be robust biomarkers for distinguishing between disease states.</p> <p>Results</p> <p>The proposed methodology was applied to a pilot narcolepsy study using logistic regression, hierarchical clustering, t-test, and CART. Consensus, differential mass peaks with high predictive power were identified across three of the four statistical platforms. Based on the diagnostic accuracy measures investigated, the performance of the consensus-peak model was a compromise between logistic regression and CART, which produced better models than hierarchical clustering and t-test. However, consensus peaks confer a higher level of confidence in their ability to distinguish between disease states since they do not represent peaks that are a result of biases to a particular statistical algorithm. Instead, they were selected as differential across differing data distribution assumptions, demonstrating their true discriminatory potential.</p> <p>Conclusion</p> <p>The methodology described here is applicable to any high-resolution MALDI mass spectrometry-derived data set with minimal mass drift which is essential for peak-to-peak comparison studies. Four statistical approaches with differing data distribution assumptions were applied to the same raw data set to obtain consensus peaks that were found to be statistically differential between the two groups compared. These consensus peaks demonstrated high diagnostic accuracy when used to form a predictive model as evaluated by receiver operating characteristics curve analysis. They should demonstrate a higher discriminatory ability as they are not biased to a particular algorithm. Thus, they are prime candidates for downstream identification and validation efforts.</p

An Expanded Set of Amino Acid Analogs for the Ribosomal Translation of Unnatural Peptides

BACKGROUND: The application of in vitro translation to the synthesis of unnatural peptides may allow the production of extremely large libraries of highly modified peptides, which are a potential source of lead compounds in the search for new pharmaceutical agents. The specificity of the translation apparatus, however, limits the diversity of unnatural amino acids that can be incorporated into peptides by ribosomal translation. We have previously shown that over 90 unnatural amino acids can be enzymatically loaded onto tRNA. METHODOLOGY/PRINCIPAL FINDINGS: We have now used a competition assay to assess the efficiency of tRNA-aminoacylation of these analogs. We have also used a series of peptide translation assays to measure the efficiency with which these analogs are incorporated into peptides. The translation apparatus tolerates most side chain derivatives, a few alpha,alpha disubstituted, N-methyl and alpha-hydroxy derivatives, but no beta-amino acids. We show that over 50 unnatural amino acids can be incorporated into peptides by ribosomal translation. Using a set of analogs that are efficiently charged and translated we were able to prepare individual peptides containing up to 13 different unnatural amino acids. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that a diverse array of unnatural building blocks can be translationally incorporated into peptides. These building blocks provide new opportunities for in vitro selections with highly modified drug-like peptides