The new farnesyl pyrophosphate (FPP) derivative with a shifted olefinic double bond from C6‐C7 to C7‐C8 is accepted and converted by the sesquiterpene cyclases protoilludene synthase (Omp7) as well as viridiflorene synthase (Tps32). In both cases, a so far unknown germacrene derivative was found to be formed, which we name “germacrene F”. Both cases are examples in which a modification around the central olefinic double bond in FPP leads to a change in the mode of initial cyclization (from 1→11 to 1→10). For Omp7 a rationale for this behaviour was found by carrying out molecular docking studies. Temperature‐dependent NMR experiments, accompanied by NOE studies, show that germacrene F adopts a preferred mirror‐symmetric conformation with both methyl groups oriented in the same directions in the cyclodecane ring.

Macrocyclization of peptides is typically used to fix specific bioactive conformations and improve their pharmacological properties. Recently, macrobicyclic peptides have received special attention owing to their capacity to mimic protein structures or be key components of peptide-drug conjugates. Here, we describe the development of novel synthetic strategies for two distinctive types of peptide macrobicycles. A multicomponent macrocyclo-dimerization approach is introduced for the production of interconnected β-turns, allowing two macrocyclic rings to be formed and dimerized in one pot. Also, an on-resin double stapling strategy is described for the assembly of lactam-bridged macrobicycles with stable tertiary folds.

Silyl ether protecting groups are important tools in organic synthesis, ensuring selective reactions of hydroxyl functional groups. Enantiospecific formation or cleavage could simultaneously enable the resolution of racemic mixtures and thus significantly increase the efficiency of complex synthetic pathways. Based on reports that lipases, which today are already particularly important tools in chemical synthesis, can catalyze the enantiospecific turnover of trimethylsilanol (TMS)-protected alcohols, the goal of this study was to determine the conditions under which such a catalysis occurs. Through detailed experimental and mechanistic investigation, we demonstrated that although lipases mediate the turnover of TMS-protected alcohols, this occurs independently of the known catalytic triad, as this is unable to stabilize a tetrahedral intermediate. The reaction is essentially non-specific and therefore most likely completely independent of the active site. This rules out lipases as catalysts for the resolution of racemic mixtures alcohols through protection or deprotection with silyl groups.

Terpene synthase-mediated biotransformation of eleven synthetic sulfur- or oxygen-containing non-natural prenyl diphosphates resulted in the formation of five novel terpenoids and analogues. Uniquely, they trap intermediate steps and form heterocycles or compounds with alkyne side chains. Computational modelling differentiates convertible from inconvertible substrates and thereby provides an understanding of the detailed molecular mechanism of terpene cyclases. Two terpene cyclases were used as biocatalytic tool, namely, limonene synthase from Cannabis sativa (CLS) and 5-epi-aristolochene synthase (TEAS) from Nicotiana tabacum. They showed significant substrate flexibility towards non-natural prenyl diphosphates to form novel terpenoids, including core oxa- and thia-heterocycles and alkyne-modified terpenoids. We elucidated the structures of five novel monoterpene-analogues and a known sesquiterpene-analogue. These results reflected the terpene synthases′ ability and promiscuity to broaden the pool of terpenoids with structurally complex analogues. Docking studies highlight an on-off conversion of the unnatural substrates.

Type 1 secretion systems (T1SS) have a relatively simple architecture compared to other classes of secretion systems and therefore, are attractive to be optimized by protein engineering. Here, we report a KnowVolution campaign for the hemolysin (Hly) enhancer fragment, an untranslated region upstream of the hlyA gene, of the hemolysin T1SS of Escherichia coli to enhance its secretion efficiency. The best performing variant of the Hly enhancer fragment contained five nucleotide mutations at  five positions (A30U, A36U, A54G, A81U, and A116U) resulted in a 2-fold increase in the secretion level of a model lipase fused to the secretion carrier HlyA1. Computational analysis suggested that altered affinity to the generated enhancer fragment towards the S1 ribosomal protein contributes to the enhanced secretion levels. Furthermore, we demonstrate that involving a native terminator region along with the generated Hly enhancer fragment increased the secretion levels of the Hly system up to 5-fold.

4-Hydroxyphenylacetate 3-hydroxylase (4HPA3H), a flavin-dependent monooxygenase from E. coli that catalyzes the hydroxylation of monophenols to catechols, was modified by rational re-design to convert also more bulky substrates, especially phenolic natural products like phenylpropanoids, flavones or coumarins. Selected amino acid positions in the binding pocket of 4HPA3H were exchanged by residues from the homologous protein from Pseudomonas aeruginosa, yielding variants with improved conversion of spacious substrates such as the flavonoid naringenin or the alkaloid mimetic 2-hydroxycarbazole. Reactions were followed by an adapted Fe(III)-catechol chromogenic assay selective for the products. Especially substitution of the residue Y301 facilitated modulation of substrate specificity: introduction of non-aromatic but hydrophobic (iso)leucine resulted in the preference of the substrate ferulic acid (having a guaiacyl (guajacyl) moiety, part of the vanilloid motif) over unsubstituted monophenols. The in vivo (whole-cell biocatalysts) and in vitro (three-enzyme cascade) transformations of substrates by 4HPA3H and its optimized variants was strictly regiospecific and proceeded without generation of by-products.

The recently described flavin‐dependent halogenase BrvH is able to catalyze both bromination and chlorination of indole, but shows significantly higher bromination activity. BrvH was annotated as a tryptophan halogenase, but does not accept tryptophan as a substrate. Its native substrate remains unknown. A predictive model with the data available for BrvH was analysed. A training set of compounds tested in vitro was docked into the active site of a complete protein model based on the X‐ray structure of BrvH. The atoms not resolved experimentally have been modelled using molecular mechanics force fields to obtain this protein model. Furthermore, docking poses for the substrates and known non‐substrates have been calculated. Parameters like distance, partial charge, and hybridization state have been analysed to derive rules for prediction of activity. With this model for activity of the BrvH, a virtual screening suggested several structures for potential substrates. Some of the thus preselected compounds were tested in vitro and several could be verified as convertible substrates. Based on information on halogenated natural products, a new dataset was created to specifically search for natural products as substrates/products, and virtual screening in this database yielded further hits.

Human drug‐metabolizing cytochrome P450 monooxygenases (CYPs) have enormous substrate promiscuity; this makes them promising tools for the expansion of natural product diversity. Here, we used CYP3A4 for the targeted diversification of a plant biosynthetic route leading to monoterpenoid indole alkaloids. In silico, in vitro and in planta studies proved that CYP3A4 was able to convert the indole alkaloid vinorine into vomilenine, the former being one of the central intermediates in the ajmaline pathway in the medicinal plant Rauvolfia serpentina (L.) Benth. ex Kurz. However, to a much larger extent, the investigated conversion yielded vinorine (19R ,20R)‐epoxide, a new metabolite with an epoxide functional group that is rare for indole alkaloids. The described work represents a successful example of combinatorial biosynthesis towards an increase in biodiversity of natural metabolites. Moreover, characterisation of the products of the in vitro and in planta transformation of potential pharmaceuticals with human CYPs might be indicative of the route of their conversion in the human organism.

BackgroundMolecule identification is a crucial step in metabolomics and environmental sciences. Besides in silico fragmentation, as performed by MetFrag, also machine learning and statistical methods evolved, showing an improvement in molecule annotation based on MS/MS data. In this work we present a new statistical scoring method where annotations of m/z fragment peaks to fragment-structures are learned in a training step. Based on a Bayesian model, two additional scoring terms are integrated into the new MetFrag2.4.5 and evaluated on the test data set of the CASMI 2016 contest.ResultsThe results on the 87 MS/MS spectra from positive and negative mode show a substantial improvement of the results compared to submissions made by the former MetFrag approach. Top1 rankings increased from 5 to 21 and Top10 rankings from 39 to 55 both showing higher values than for CSI:IOKR, the winner of the CASMI 2016 contest. For the negative mode spectra, MetFrag’s statistical scoring outperforms all other participants which submitted results for this type of spectra.ConclusionsThis study shows how statistical learning can improve molecular structure identification based on MS/MS data compared on the same method using combinatorial in silico fragmentation only. MetFrag2.4.5 shows especially in negative mode a better performance compared to the other participating approaches.

BackgroundTranscriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. Approaches for de-novo motif discovery can be subdivided in phylogenetic footprinting that takes into account phylogenetic dependencies in aligned sequences of more than one species and non-phylogenetic approaches based on sequences from only one species that typically take into account intra-motif dependencies. It has been shown that modeling (i) phylogenetic dependencies as well as (ii) intra-motif dependencies separately improves de-novo motif discovery, but there is no approach capable of modeling both (i) and (ii) simultaneously.ResultsHere, we present an approach for de-novo motif discovery that combines phylogenetic footprinting with motif models capable of taking into account intra-motif dependencies. We study the degree of intra-motif dependencies inferred by this approach from ChIP-seq data of 35 transcription factors. We find that significant intra-motif dependencies of orders 1 and 2 are present in all 35 datasets and that intra-motif dependencies of order 2 are typically stronger than those of order 1. We also find that the presented approach improves the classification performance of phylogenetic footprinting in all 35 datasets and that incorporating intra-motif dependencies of order 2 yields a higher classification performance than incorporating such dependencies of only order 1.ConclusionCombining phylogenetic footprinting with motif models incorporating intra-motif dependencies leads to an improved performance in the classification of transcription factor binding sites. This may advance our understanding of transcriptional gene regulation and its evolution.