Tandem Cyclization in Ruthenium Vinylidene Complexes with Two Ester Groups

The reaction of [Ru]-Cl ([Ru] = Cp(PPh3)2Ru) with o-ethynyl-substituted methyl benzoate, followed by a sequential deprotonation and electrophilic alkylation reactions by further reacting with base and various alkyl haloacetates, respectively, generated several disubstituted ruthenium vinylidene complexes. In the deprotonation reactions of these disubstituted vinylidene complexes containing two ester groups, tandem cyclizations of the ligand is accompanied with a methanol elimination to generate a new organometallic product containing a three-ring indenofuranone ligand, which structure has been confirmed by a single-crystal X-ray diffraction analysis. Facile protonation and methylation are observed in these indenofuranone complexes. Additionally, for the simple furyl complex containing an O-benzyl group, a 1,3-migration of the benzyl group is observed to yield a lactone product and a Claisen rearrangement is also observed in analogous complexes with O-allyl or O-propargyl groups

Accuracies (%) of various predictors on classification of proteins with and without signal peptides.

<p>Accuracies (%) of various predictors on classification of proteins with and without signal peptides.</p

MCCs (%) of various predictors on classification of proteins with and without signal peptides.

<p>MCCs (%) of various predictors on classification of proteins with and without signal peptides.</p

Specificities (%) of various predictors on the non-signal peptide protein benchmark datasets.

<p>Specificities (%) of various predictors on the non-signal peptide protein benchmark datasets.</p

Sensitivities (%) of various predictors on the signal peptide protein benchmark datasets.

<p>Sensitivities (%) of various predictors on the signal peptide protein benchmark datasets.</p

List of unique proteins and their similar non-signal peptide proteins.

<p>List of unique proteins and their similar non-signal peptide proteins.</p

Basic statistics in the selected seven proteomes of Mycobacterium tuberculosis (*) and Mycobacterium bovis (**).

<p>Basic statistics in the selected seven proteomes of Mycobacterium tuberculosis (*) and Mycobacterium bovis (**).</p

An example, O95994 (AGR2_HUMAN), of biochemical feature profiles in a 100-residue N-terminal subsequence predicted to contain a signal peptide.

<p>An example, O95994 (AGR2_HUMAN), of biochemical feature profiles in a 100-residue N-terminal subsequence predicted to contain a signal peptide.</p

The hierarchical architecture of SVMSignal.

<p>The hierarchical architecture of SVMSignal.</p

MAGIC: An Automated N‑Linked Glycoprotein Identification Tool Using a Y1-Ion Pattern Matching Algorithm and <i>in Silico</i> MS² Approach

Glycosylation is a highly complex modification influencing the functions and activities of proteins. Interpretation of intact glycopeptide spectra is crucial but challenging. In this paper, we present a mass spectrometry-based automated glycopeptide identification platform (MAGIC) to identify peptide sequences and glycan compositions directly from intact N-linked glycopeptide collision-induced-dissociation spectra. The identification of the Y1 (peptideY0 + GlcNAc) ion is critical for the correct analysis of unknown glycoproteins, especially without prior knowledge of the proteins and glycans present in the sample. To ensure accurate Y1-ion assignment, we propose a novel algorithm called Trident that detects a triplet pattern corresponding to [Y0, Y1, Y2] or [Y0−NH₃, Y0, Y1] from the fragmentation of the common trimannosyl core of N-linked glycopeptides. To facilitate the subsequent peptide sequence identification by common database search engines, MAGIC generates <i>in silico</i> spectra by overwriting the original precursor with the naked peptide <i>m</i>/<i>z</i> and removing all of the glycan-related ions. Finally, MAGIC computes the glycan compositions and ranks them. For the model glycoprotein horseradish peroxidase (HRP) and a 5-glycoprotein mixture, a 2- to 31-fold increase in the relative intensities of the peptide fragments was achieved, which led to the identification of 7 tryptic glycopeptides from HRP and 16 glycopeptides from the mixture via Mascot. In the HeLa cell proteome data set, MAGIC processed over a thousand MS² spectra in 3 min on a PC and reported 36 glycopeptides from 26 glycoproteins. Finally, a remarkable false discovery rate of 0 was achieved on the N-glycosylation-free <i>Escherichia coli</i> data set. MAGIC is available at http://ms.iis.sinica.edu.tw/COmics/Software_MAGIC.html