Leveraging Limited Experimental Data with Machine Learning: Differentiating a Methyl from an Ethyl Group in the Corey-Bakshi-Shibata Reduction.

We present a case study on how to improve an existing metal-free catalyst for a particularly difficult reaction, namely, the Corey-Bakshi-Shibata (CBS) reduction of butanone, which constitutes the classic and prototypical challenge of being able to differentiate a methyl from an ethyl group. As there are no known strategies on how to address this challenge, we leveraged the power of machine learning by constructing a realistic (for a typical laboratory) small, albeit high-quality, data set of about 100 reactions (run in triplicate) that we used to train a model in combination with a key-intermediate graph (of substrate and catalyst) to predict the differences in Gibbs activation energies ΔΔ of the enantiomeric reaction paths. With the help of this model, we were able to select and subsequently screen a small selection of catalysts and increase the selectivity for the CBS reduction of butanone to 80% enantiomeric excess (ee), the highest possible value achieved to date for this substrate with a metal-free catalyst, thereby also exceeding the best available enzymatic systems (64% ee) and the selectivity with Corey's original catalyst (60% ee).

Determining Ultra-Low Organic Molecular Odor Thresholds in Air Helps Identify the Most Potent Fungal Aroma Compound.

The determination of odor threshold values can be performed in various matrices, including air, and serves as a parameter to compare the potencies of odorous compounds. Typically, the odor thresholds in air are determined by gas chromatography-olfactory (GC-O) and referenced to an internal standard, most often ()-dec-2-enal. Herein, a direct gas chromatography-flame ionization detector-olfactory analysis method for the determination of odor thresholds in air is reported.

Quantifying Intermolecular Interactions in Asymmetric Peptide Organocatalysis as a Key toward Understanding Selectivity.

The kinetic resolution of -cyclohexane-1,2-diol with a lipophilic oligopeptide catalyst shows extraordinary selectivities. To improve our understanding of the factors governing selectivity, we quantified the Gibbs free energies of interactions of the peptide with both enantiomers of -cyclohexane-1,2-diol using nuclear magnetic resonance (NMR) spectroscopy. For this, we use advanced methods such as transverse relaxation (), diffusion measurements, saturation transfer difference (STD), and chemical shift (δ) analysis of peptide-diol mixtures upon varying their composition (NMR titrations).

Structure Elucidation of Aroma-Active Bicyclic Benzofuran Derivatives Formed by .

Among the monoterpenoid aroma compounds formed by the basidiomycete are highly potent bicyclic benzofuran derivatives. In addition to the dill ethers previously described in a few fungi, two stereoisomers of the rare 3,6-dimethyl-3a,4,5,6,7,7a-hexahydro-3-1-benzofuran-2-one ( and ), also known as dihydromenthofurolactones, and a C3-unsaturated analogue () are formed by . The analysis of synthesized reference standards of the lactones allowed an unambiguous assignment of the stereoisomers formed by the fungus.