Forty years of progress in the fields of gas chromatography and data collection have culminated in flavoromics. This is a combination of chemometrics and metabolomics. Essentially, it is the non-targeted way of rapidly collecting a significant amount of data from a wide range of sample populations and using the data to study complicated topics. Now that we have the required tools, we can carry out high-throughput trace investigations that incorporate both gustatory and olfactory signals. Flavoro

A central challenge in olfaction is understanding how the olfactory system detects and distinguishes odorants with diverse physicochemical properties and molecular configurations. Vertebrate animals perceive odors via G protein-coupled odorant receptors (ORs). In humans, ∼400 ORs enable the sense of smell. The OR family is composed of two major classes: Class I ORs are tuned to carboxylic acids while Class II ORs, representing the vast majority of the human repertoire, respond to a wide variety of odorants. How ORs recognize chemically diverse odorants remains poorly understood. A fundamental bottleneck is the inability to visualize odorant binding to ORs. Here, we uncover fundamental molecular properties of odorant-OR interactions by employing engineered ORs crafted using a consensus protein design strategy. Because such consensus ORs (consORs) are derived from the 17 major subfamilies of human ORs, they provide a template for modeling individual native ORs with high sequence and structural homology. The biochemical tractability of consORs enabled four cryoEM structures of distinct consORs with unique ligand recognition properties. The structure of a Class I consOR, consOR51, showed high structural similarity to the native human receptor OR51E2 and yielded a homology model of a related member of the human OR51 family with high predictive power. Structures of three Class II consORs revealed distinct modes of odorant-binding and activation mechanisms between Class I and Class II ORs. Thus, the structures of consORs lay the groundwork for understanding molecular recognition of odorants by the OR superfamily. ### Competing Interest Statement H.M. has received royalties from Chemcom, research grants from Givaudan, and consultant fees from Kao. A.M. is a founder of Epiodyne and Stipple Bio, consults for Abalone, and serves on the scientific advisory board of Septerna.

Quantitative structure–odor relationships are critically important for studies related to the function of olfaction. Current literature data sets contain expert-labeled molecules but lack feature data. This paper introduces QuantumScents, a quantum mechanics augmented derivative of the Leffingwell data set. QuantumScents contains 3.5k structurally and chemically diverse molecules ranging from 2 to 30 heavy atoms (CNOS) and their corresponding 3D coordinates, total PBE0 energy, molecular dipole moment, and per-atom Hirshfeld charges, dipoles, and ratios. The authors demonstrate that Hirshfeld charges and ratios contain sufficient information to perform molecular classification by training a Message Passing Neural Network with chemprop (Heid, E.; et al. ChemRxiv, 2023, DOI: 10.26434/chemrxiv-2023-3zcfl) to predict scent labels. The QuantumScents data set is freely available on Zenodo along with the authors’ code, example models, and data set generation workflow (https://zenodo.org/doi/10.5281/zenodo.8239853).

University of Florida scientists have found ethyl vanillin—an aroma compound in many artificial vanilla-flavored food products—in a UF/IFAS-bred strawberry. This is a key finding for the food and ...

Sniffing in stereo.

It's not just your skin that can feel.

So, are you better than an algorithm?

The iconic Proustian madeleine moment meets science. Is it strange that the smell of wet soil can be more appealing than tropical flowers? Don't worry; we're all drawn to unconventional odors like burning rubber, Play-Doh, or chlorine. Is it true that preferences are culturally relative, driven by individual tastes, or universally influenced by molecular structures? Science offers various explanations

Scientists don't understand why the correlation exists. Many ideas have been offered, but none are convincing.