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.

The production of fine-flavor cocoa represents a promising avenue to enhance socioeconomic development in Colombia and Latin America. Premium chocolate is obtained through a post-harvesting process, which relies on semi-standardized techniques. The change in the metabolic profile during cocoa processing considerably impacts flavor and nutraceutical properties of the final product. Understanding this impact considering both volatiles and non-volatile compounds is crucial for process and product re-engineering of cocoa post-harvesting. Consequently, this work studied the metabolic composition of cocoa liquor by untargeted metabolomics and lipidomics. This approach offered a comprehensive view of cocoa biochemistry, considering compounds associated with bioactivity and flavor in cocoa liquor. Their variations were traced back over the cocoa processing (i.e., drying, and roasting), highlighting their impact on flavor development and the nutraceutical properties. These results represent the basis for future studies aimed to re-engineer cocoa post-harvesting considering the variation of key flavor and bioactive compounds over processing.

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.

Tomatoes show diverse phytochemical attributes that contribute to their nutritive and health values. This study comprehensively dissects primary and secondary metabolite profiles of seven tomato varieties. UHPLC-qTOF-MS assisted molecular networking was used to monitor 206 metabolites, 30 of which were first-time to be reported. Flavonoids, as valuable antioxidants, were enriched in light-colored tomatoes (golden sweet, sun gold, and yellow plum) versus high tomatoside A, an antihyperglycemic saponin, in cherry bomb and red plum varieties. UV–Vis analysis revealed similar results with a strong absorbance corresponding to rich phenolic content in light varieties. GC–MS unveiled monosaccharides as the main contributors to samples’ segregation, found abundant in San Marzano tomato accounting for its sweet flavor. Fruits also demonstrated potential antioxidant activities in correlation to their flavonoids and phospholipids. This work provides a complete map of tomatoes’ metabolome heterogeneity for future breeding programs and a comparative approach utilizing different metabolomic platforms for tomato analysis.

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.

M. oleifera known as “miracle tree” is increasingly used in nutraceuticals for the reported health effects and nutritional value of its leaves. This study presents the first metabolome profiling of M. oleifera leaves of African origin using different solvent polarities via HR-UPLC/MS based molecular networking followed by multivariate data analyses for samples classification. 119 Chemicals were characterized in both positive and negative modes belonging to 8 classes viz. phenolic acids, flavonoids, peptides, fatty acids/amides, sulfolipids, glucosinolates and carotenoids. New metabolites i.e., polyphenolics, fatty acids, in addition to a new class of sulfolipids were annotated for the first time in Moringa leaves. In vitro anti-inflammatory and anti-aging bioassays of the leaf extracts were assessed and in correlation to their metabolite profile via multivariate data analyses. Kaempferol, quercetin and apigenin-O/C-glycosides, fatty acyl amides and carotenoids appeared crucial for biological activities and leaves origin discrimination.

With a favored taste and various bioactivities, coffee has been consumed as a daily beverage worldwide. The current study presented a multi-faceted comparative metabolomics approach dissecting commercially available coffee products in the Middle East region for quality assessment and functional food purposes using NMR and GC/MS platforms. NMR metabolites fingerprinting led to identification of 18 metabolites and quantification (qNMR) of six prominent markers for standardization purposes. An increase of β-ethanolamine (MEA) reported for the first time, 5-(hydroxymethyl) furfural (5-HMF), concurrent with a reduction in chlorogenic acid, kahweol, and sucrose levels post roasting as revealed using multivariate data analyses (MVA). The diterpenes kahweol and cafestol were identified in green and roasted Coffea arabica, while 16-O-methyl cafestol in roasted C. robusta. Moreover, GC/MS identified a total of 143 metabolites belonging to 15 different chemical classes, with fructose found enriched in green C. robusta versus fatty acids abundance, i.e., palmitic and stearic acids in C. arabica confirming NMR results. These potential results aided to identify novel quality control attributes, i.e., ethanolamine, for coffee in the Middle East region and have yet to be confirmed in other coffee specimens.

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.

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 impact of cocoa lipid content on chocolate quality has been extensively described. Nevertheless, few studies have elucidated the cocoa lipid composition and their bioactive properties, focusing only on specific lipids. In the present study the lipidome of fine-flavor cocoa fermentation was analyzed using LC-MS-QTOF and a Machine Learning model to assess potential bioactivity was developed. Our results revealed that the cocoa lipidome, comprised mainly of fatty acyls and glycerophospholipids, remains stable during fine-flavor cocoa fermentations. Also, several Machine Learning algorithms were trained to explore potential biological activity among the identified lipids. We found that K-Nearest Neighbors had the best performance. This model was used to classify the identified lipids as bioactive or non-bioactive, nominating 28 molecules as potential bioactive lipids. None of these compounds have been previously reported as bioactive. Our work is the first untargeted lipidomic study and systematic effort to investigate potential bioactivity in fine-flavor cocoa lipids.