Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

In contrast to the myriad of methods available to produce α‐helices and antiparallel β‐sheets in synthetic peptides, just a few are known for the construction of stable, non‐cyclic parallel β‐sheets. Herein, we report an efficient on‐resin approach for the assembly of parallel β‐sheet peptides in which the N‐alkylated turn moiety enhances the stability and gives access to a variety of functionalizations without modifying the parallel strands. The key synthetic step of this strategy is the multicomponent construction of an N‐alkylated turn using the Ugi reaction on varied isocyano‐resins. This four‐component process assembles the orthogonally protected turn fragment and incorporates handles serving for labeling/conjugation purposes or for reducing peptide aggregation. NMR and circular dichroism analyses confirm the better‐structured and more stable parallel β‐sheets in the N‐alkylated peptides compared to the non‐functionalized variants.

For the first time, the Petasis (borono‐Mannich) reaction is employed for the multicomponent labeling and stapling of peptides. The report includes the solid‐phase derivatization of peptides at the N‐terminus, Lys, and Nϵ‐MeLys side‐chains by an on‐resin Petasis reaction with variation of the carbonyl and boronic acid components. Peptides were simultaneously functionalized with aryl/vinyl substituents bearing fluorescent/affinity tags and oxo components such as dihydroxyacetone, glyceraldehyde, glyoxylic acid, and aldoses, thus encompassing a powerful complexity‐generating approach without changing the charge of the peptides. The multicomponent stapling was conducted in solution by linking Nϵ‐MeLys or Orn side‐chains, positioned at i, i+7 and i, i+4, with aryl tethers, while hydroxy carbonyl moieties were introduced as exocyclic fragments. The good efficiency and diversity oriented character of these methods show prospects for peptide drug discovery and chemical biology.

Metabolic fingerprinting is a powerful analytical technique, giving access to high-throughput identification and relative quantification of multiple metabolites. Because of short analysis times, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is the preferred instrumental platform for fingerprinting, although its power in analysis of free fatty acids (FFAs) is limited. However, these metabolites are the biomarkers of human pathologies and indicators of food quality. Hence, a high-throughput method for their fingerprinting is required. Therefore, here we propose a MALDI-TOF-MS method for identification and relative quantification of FFAs in biological samples of different origins. Our approach relies on formation of monomolecular Langmuir films (LFs) at the interphase of aqueous barium acetate solution, supplemented with low amounts of 2,5-dihydroxybenzoic acid, and hexane extracts of biological samples. This resulted in detection limits of 10–13–10–14 mol and overall method linear dynamic range of at least 4 orders of magnitude with accuracy and precision within 2 and 17%, respectively. The method precision was verified with eight sample series of different taxonomies, which indicates a universal applicability of our approach. Thereby, 31 and 22 FFA signals were annotated by exact mass and identified by tandem MS, respectively. Among 20 FFAs identified in Fucus algae, 14 could be confirmed by gas chromatography-mass spectrometry.

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

Die Funktionalisierung von C‐H‐Bindungen mit Nichtedelmetallkatalysatoren ist ein wichtiges Forschungsgebiet für die Entwicklung effizienter und nachhaltiger Synthesemethoden. In diesem Artikel beschreiben wir die Entwicklung Eisenporphyrin‐katalysierter Reaktionen von Diazoacetonitril mit N‐Heterocyclen um so einen Zugang zu wertvollen Vorläufern zu Tryptaminen zu erhalten. Darüberhinaus berichten wir über experimentelle mechanistische Studien sowie über konzeptionelle Studien zu einer enzymatischen Synthese mit dem Enzym YfeX. Mit dem leicht zugänglichen FeTPPCl‐Katalysator konnten wir hoch effiziente C‐H‐Funktionalisierungsreaktionen von Indol und Indazol‐Heterocyclen zeigen. Diese Reaktionen können unter milden Reaktionsbedingungen, mit exzellenten Ausbeuten und großer Toleranz funktioneller Gruppen inklusive Anwendungen im Grammmaßstab durchgeführt werden und eröffnen so einen einzigartigen, effizienten Zugang zu Tryptaminen.

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

An important development in the field of macrocyclization strategies towards molecular cages is described. The approach comprises the utilization of a double Ugi four‐component macrocyclization for the assembly of macromulticycles with up to four different tethers, that is, hybrid cages. The innovation of this method rests on setting up the macromulticycle connectivities not through the tethers but through the bridgeheads, which in this case involve N‐substituted amino acids. Both dilution and metal‐template‐driven macrocyclization conditions were implemented with success, enabling the one‐pot formation of cryptands and cages including steroidal, polyether, heterocyclic, peptidic, and aryl tethers. This method demonstrates substantial complexity‐generating character and is suitable for applications in molecular recognition and catalysis.

The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS1 abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application “MetFamily”, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS1-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS1 patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR.

Demands in research investigating small molecules by applying untargeted approaches have been a key motivator for the development of repositories for mass spectrometry spectra and automated tools to aid compound identification. Comparatively little attention has been afforded to using retention times (RTs) to distinguish compounds and for liquid chromatography there are currently no coordinated efforts to share and exploit RT information. We therefore present PredRet; the first tool that makes community sharing of RT information possible across laboratories and chromatographic systems (CSs). At http://predret.org, a database of RTs from different CSs is available and users can upload their own experimental RTs and download predicted RTs for compounds which they have not experimentally determined in their own experiments. For each possible pair of CSs in the database, the RTs are used to construct a projection model between the RTs in the two CSs. The number of compounds for which RTs can be predicted and the accuracy of the predictions are dependent upon the compound coverage overlap between the CSs used for construction of projection models. At the moment, it is possible to predict up to 400 RTs with a median error between 0.01 and 0.28 min depending on the CS and the median width of the prediction interval ranging from 0.08 to 1.86 min. By comparing experimental and predicted RTs, the user can thus prioritize which isomers to target for further characterization and potentially exclude some structures completely. As the database grows, the number and accuracy of predictions will increase.