We study the hyperactivation of α‐chymotrypsin (α‐ChT) using the acrylate polymer poly(2‐carboxyethyl) acrylate (PCEA) in comparison to the commonly used poly(acrylic acid) (PAA). The polymers are added during the enzymatic cleavage reaction of the substrate N‐glutaryl‐L‐phenylalanine p‐nitroanilide (GPNA). Enzyme activity assays reveal a pronounced enzyme hyperactivation capacity of PCEA, which reaches up to 950% activity enhancement, and is significantly superior to PAA (revealing an activity enhancement of approx. 450%). In a combined experimental and computational study, we investigate α‐ChT/polymer interactions to elucidate the hyperactivation mechanism of the enzyme. Isothermal titration calorimetry reveals a pronounced complexation between the polymer and the enzyme. Docking simulations reveal that binding of polymers significantly improves the binding affinity of GPNA to α‐ChT. Notably, a higher binding affinity is found for the α‐ChT/PCEA compared to the α‐ChT/PAA complex. Further molecular dynamics (MD) simulations reveal changes in the size of the active site in the enzyme/polymer complexes, with PCEA inducing a more pronounced alteration compared to PAA, facilitating an easier access for the substrate to the active site of α‐ChT.

Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using the Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using a CWL description on WorkflowHub. During the submission process on WorkflowHub, a CWL description is used for packaging MAW using the Workflow RO-Crate profile, which includes metadata in Bioschemas. Researchers can use this narrative discussion as a guideline to commence using FAIR practices for their bioinformatics or cheminformatics workflows while incorporating necessary amendments specific to their research area.

Dalbergia melanoxylon Guill. & Perr (Fabaceae) is widely utilized in the traditional medicine of East Africa, showing effects against a variety of ailments including microbial infections. Phytochemical investigation of the root bark led to the isolation of six previously undescribed prenylated isoflavanones together with eight known secondary metabolites comprising isoflavanoids, neoflavones and an alkyl hydroxylcinnamate. Structures were elucidated based on HR-ESI-MS, 1- and 2-D NMR and ECD spectra. The crude extract and the isolated compounds of D. melanoxylon were tested for their antibacterial, antifungal, anthelmintic and cytotoxic properties, applying established model organisms non-pathogenic to humans. The crude extract exhibited significant antibacterial activity against Gram-positive Bacillus subtilis (97% inhibition at 50 μg/mL) and antifungal activity against the phytopathogens Phytophthora infestans, Botrytis cinerea and Septoria tritici (96, 89 and 73% at 125 μg/mL, respectively). Among the pure compounds tested, kenusanone H and (3R)-tomentosanol B exhibited, in a panel of partially human pathogenic bacteria and fungi, promising antibacterial activity against Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA) and Mycobacterium showing MIC values between 0.8 and 6.2 μg/mL. The observed biological effects support the traditional use of D. melanoxylon and warrant detailed investigations of its prenylated isoflavanones as antibacterial lead compounds.

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.

Rational re-design of the substrate pocket of phenylpropanoid-flavonoid O-methyltransferase (PFOMT) from Mesembryanthe-mum crystallinum, an enzyme that selectively methylates the 3’-position (= meta-position) in catechol-moieties of flavonoids to guiacol-moieties, provided the basis for the generation of variants with opposite, i. e. 4’- (para-) regioselectivity and enhanced catalytic efficiency. A double variant (Y51R/N202W) identified through a newly developed colorimetric assay efficiently modified the para-position in flavanone and flavano-nol substrates, providing access to the sweetener molecule hesperetin and other rare plant flavonoids having an isovanil-loid motif.

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics experiments have become increasingly popular because of the wide range of metabolites that can be analyzed and the possibility to measure novel compounds. LC-MS instrumentation and analysis conditions can differ substantially among laboratories and experiments, thus resulting in non-standardized datasets demanding customized annotation workflows. We present an ecosystem of R packages, centered around the MetaboCoreUtils, MetaboAnnotation and CompoundDb packages that together provide a modular infrastructure for the annotation of untargeted metabolomics data. Initial annotation can be performed based on MS1 properties such as m/z and retention times, followed by an MS2-based annotation in which experimental fragment spectra are compared against a reference library. Such reference databases can be created and managed with the CompoundDb package. The ecosystem supports data from a variety of formats, including, but not limited to, MSP, MGF, mzML, mzXML, netCDF as well as MassBank text files and SQL databases. Through its highly customizable functionality, the presented infrastructure allows to build reproducible annotation workflows tailored for and adapted to most untargeted LC-MS-based datasets. All core functionality, which supports base R data types, is exported, also facilitating its re-use in other R packages. Finally, all packages are thoroughly unit-tested and documented and are available on GitHub and through Bioconductor.

Bioinspired, synthetic porphyrin complexes are important catalysts in organic synthesis and play a pivotal role in efficient carbene transfer reactions. The advances in this research area stimulated recent, “chemo‐inspired” developments in biocatalysis. Today, both synthetic iron complexes and enzymes play an important role to conduct carbene transfer reactions. The advances and potential developments in both research areas are discussed in this concept article.

Catalyst discovery and development requires the screening of large reaction sets necessitating analytic methods with the potential for high‐throughput screening. These techniques often suffer from substrate dependency or the requirement of expert knowledge. Chromatographic techniques (GC/LC) can overcome these limitations but are generally hampered by long analysis time or the need for special equipment. The herein developed multiple injections in a single experimental run (MISER) GC‐MS technique allows a substrate independent 96‐well microtiter plate analysis within 60 min. This method can be applied to any laboratory equipped with a standard GC‐MS. With this concept novel, unspecific peroxygenase (UPO) chimeras, could be identified, consisting of subdomains from three different fungal UPO genes. The GC‐technique was additionally applied to evaluate an YfeX library in an E. coli whole‐cell system for the carbene‐transfer reaction on indole, which revealed the thus far unknown axial heme ligand tryptophan.

Background: different Solanaceae and Erythroxylaceae species produce tropane alkaloids. These alkaloids are the starting material in the production of different pharmaceuticals. The commercial demand for tropane alkaloids is covered by extracting them from cultivated plants. Datura stramonium is cultivated under greenhouse conditions as a source of tropane alkaloids. Here we investigate the effect of different levels of water availability in the soil on the production of tropane alkaloids by D. stramonium. Methods: We tested four irrigation levels on the accumulation of tropane alkaloids. We analyzed the profile of tropane alkaloids using an untargeted liquid chromatography/mass spectrometry method. Results: Using a combination of informatics and manual interpretation of mass spectra, we generated several structure hypotheses for signals in D. stramonium extracts that we assign as putative tropane alkaloids. Quantitation of mass spectrometry signals for our structure hypotheses across different anatomical organs allowed us to identify patterns of tropane alkaloids associated with different levels of irrigation. Furthermore, we identified anatomic partitioning of tropane alkaloid isomers with pharmaceutical applications. Conclusions: Our results show that soil water availability is an effective method for maximizing the production of specific tropane alkaloids for industrial applications.

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub.