Johanna Kreissl

Since the discovery of caffeine in 1819 by Runge, its role in the sensory perception of coffee remains unclear. To further investigate its influence, the caffeine–chlorogenate complex was examined using NMR spectroscopy as well as sensory experiments. It was found that the complex formation between caffeine and chlorogenic acid (CQA) has no impact on the bitter taste of caffeine. The changes of the ¹H NMR resonance signals of caffeine in the coffee matrix compared to an aqueous reference solution suggested that caffeine interacts, besides its complex with CQA, with the high molecular weight melanoidins containing fraction of coffee. After isolating the melanoidins from the coffee beverage, these interactions were confirmed in model studies using ¹H NMR spectroscopy. Sensory studies with caffeine and the melanoidins in their natural concentrations showed a strong reduction in bitter intensity by about half compared to an aqueous caffeine solution of the same concentration.

Houttuynia cordata is a culinary herb from Asia. Its edible rhizomes and leaves have a fishy aroma, the molecular background of which was unknown. A comparative aroma extract dilution analysis applied to fresh rhizomes and leaves resulted in 44 and 41 odorants, respectively, 38 of which were present with FD factors ≥1 in both samples. The odorant with the highest FD factors, whether in the rhizomes or leaves, was identified as metallic, soapy, fishy smelling 3-oxododecanal. Toward clarifying its tautomeric composition, quantum calculations suggested a predominance of the enol forms in the plant. However, the form perceived at the sniffing port during GC–O remained unclear.

Masking the bitter taste of foods is one of the key strategies to improve their taste and palatability, particularly in the context of clean labeling, where natural compounds are preferred. Despite the demand, the availability of natural bitter-masking compounds remains limited. Here, we identified the bitter-masking compound 4 '-demethyl-3,9-dihydroeucomin (DMDHE) isolated from the resin of Daemonorops draco by means of an activity-guided in vivo (sensory bitterness rating of quinine) and in vitro (cell-based bitter response assays) approach. First, a mean bitter-masking effect of -29.6 +/- 6.30% on the bitterness perceived from quinine [10 ppm] was demonstrated for an organic solvent extract of the resin of D. draco (= DD [500 ppm]) in a sensory trial. The results were verified in a cell-based bitter assay in which the bitter taste receptor (TAS2R)-dependent proton secretion serves as an outcome measure of the cellular bitter response in parietal HGT-1 cells. By means of preparative RP-18 high-performance liquid chromatography (HPLC) analysis combined with activity-guided sensory evaluations, the most potent bitter-masking fractions were identified. Subsequent quantitative liquid chromatography/high-resolution mass spectrometry/charged aerosol detection/ultraviolet (LC-HRMS/CAD/UV), NMR analysis, followed by gram-scale synthesis, led to the characterization of DMDHE as bitter-masking homoisoflavanone. DMDHE decreased the sensory bitterness of quinine by 14.8 +/- 5.00%. Functional involvement of TAS2R14 was demonstrated by means of a CRISPR-Cas9 approach, which revealed a reduction of the DMDHE-evoked bitter-masking effect by 40.4 +/- 9.32% in HGT-1 TAS2R14ko versus HGT-1 wt cells.

The aroma of red wine results from the intricate interplay between aroma compounds (odorants) and complex polymers generated during fermentation. This study combines density functional theory (DFT), human sensory experiments, and nuclear magnetic resonance to investigate the impact of odorant-polymer interactions on wine aroma. Molecular aggregation patterns of odorants with polymer segments are identified, indicating the crucial role of intermolecular noncovalent interactions, such as hydrogen bonds and van der Waals interactions, in stabilizing odorant-polymer conformations. Certain odorants, including 3-isobutyl-2-methoxypyrazine and cis-whisky lactone, exhibit high binding affinity to specific polymer segments, such as (+)-catechin and p-coumaric acid, resulting in substantial changes in the perceived aroma. Their strong binding affinities correlate with changes in sensory experiments for binary mixtures. The results provide insights into the molecular mechanisms of odorant-polymer interactions in red wine with the potential of DFT calculations as a tool for predicting and tailoring red wine aroma.

The aroma of red wine is suggested to be influenced by interactions with nonvolatile polymers. To investigate this aroma binding effect in red wine, the key aroma compounds of a Primitivo red wine were quantified using GC-MS and an aroma recombinant with 27 odorants was prepared. In sensory experiments, an overall strong effect on the odor perception of the aroma recombinant was observed when high-molecular-weight (HMW) polymers of Primitivo red wine were added. An ¹H NMR-based approach was developed to get an insight into the molecular mechanisms of this aroma binding effect in red wine. Evaluation of qualitative changes in the NMR spectra and quantitative time-dependent measurements revealed a clear distinction between different molecular interaction types: (i) no interactions for esters, alcohols, furanones, ketones, and C₁₃-norisoprenoids, (ii, iii) noncovalent interactions for acids, aldehydes, and lactones, and (iv) π-π interactions for pyrazines and phenols. Additionally, the influence of the molecular weight of polymers was evaluated, where the HMW fraction 30-50 kDa showed the highest interaction activity, for example for π-π interactions. Based on these results, the new approach allowed the direct analysis of noncovalent interactions between odorants and HMW polymers and therefore allowed for the first time the description of the aroma binding effect on a molecular basis.

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here we report two additional agonists and functional data of the most potent compound on two mutants, L104 ^3.32 and L255 ^6.51 . Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models, and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

The aroma of pea protein (Pisum sativum L.) was decrypted for knowledge-based flavor optimization of new food products containing pea protein. Sensomics helped to determine several volatiles via ultra-high performance liquid chromatography tandem mass spectrometry and 3-nitrophenylhydrazine derivatization. Among the investigated volatiles, representatives of aldehydes, ketones, and acids were reported in literature as especially important in pea and pea-related matrices. After validation of the method and quantitation of the corresponding analytes, sensory reconstitution as well as omission studies of a selected pea protein were performed and revealed nine odor-active compounds as key food odorants (3-methylbutanal, hexanal, acetaldehyde, (E,E)-2,4-nonadienal, (E)-2-octenal, benzaldehyde, heptanal, 2-methylbutanal, and nonanoic acid). Interestingly, eight out of nine compounds belonged to the chemical class of aldehydes. Statistical heatmap and cluster analysis of all odor activity values of different pea proteins confirmed the obtained sensory results and generalize these nine key food odorants in other pea proteins. The knowledge of key components gained shows potential for simplifying industrial flavor optimization of pea protein-based food.