Assays for Methionine γ‑Lyase and <i>S</i>‑Adenosyl‑l‑homocysteine Hydrolase Based on Enzymatic Formation of CdS Quantum Dots <i>in Situ</i>

<i>S</i>-Adenosyl-l-homocysteine hydrolase (AHCY) hydrolyzes its substrate <i>S</i>-adenosyl-l-homocysteine (AdoHcy) to l-homocysteine (Hcy). Methionine γ-lyase (MGL) catalyzes the decomposition of Hcy to hydrogen sulfide which forms fluorescent CdS nanoparticles in the presence of Cd­(NO₃)₂. On the basis of these enzymatic reactions, two new simple and robust fluorogenic enzymatic assays for MGL and AHCY were developed and applied to detection of AHCY inhibitors

Metallacycle-Catalyzed S_NAr Reaction in Water: Supramolecular Inhibition by Means of Host–Guest Complexation

The performance of a Pt^II diazapyrenium-based metallacycle as a reusable substoichiometric catalyst for the S_NAr reaction between halodinitrobenzenes and sodium azide at rt in aqueous media is reported. The results suggest that the catalytic effect is promoted by the association of the azide to the diazapyrenium cationic subunits of the catalyst. The findings demonstrate that the formation of an inclusion complex between pyrene and the metallacycle has a regulatory effect over the system, resulting in allosteric-like inhibition of the S_NAr reaction

Polymorphism-Triggered Reversible Thermochromic Fluorescence of a Simple 1,8-Naphthyridine

The fluorescent behavior in the solid state of a naphthyridine-based donor–acceptor heterocycle is presented. Synthesized as a crystalline blue-emissive solid (<i>Pbca</i>), the compound can easily be transformed in its <i>P</i>2₁/<i>c</i> polymorphic form by heating. The latter material shows blue to cyan emission switching triggered by a reversible thermally induced phase transformation. This fact, the reversible acidochromism, and the strong anisotropic fluorescence of the compound in the solid state, account for the potential of 1,8-naphthyridines as simple and highly tunable organic compounds in materials science

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study