Understanding Catalyst Activation Drives Transition from Iridium to Manganese Catalyzed Hydrogen Autotransfer Chemistry

As an alternative to iridium catalysts, a procedure to access and employ a more earth-adundant Mn2(CO)10-derived pincer complex was successfully demonstrated in the synthesis of a complex pharmaceutically relevant ketone from milligram to 500g scales. Mechanistic studies revealed that the dissociation of CO driven by light is a critical step in forming the active catalyst. This robust and mechanistically informed method reliably promotes hydrogen autotransfer of alcohols, catalyzing a diverse array of C–C and C–N bond formations. This emphasizes the importance of precatalyst selection and understanding catalyst activation to enable rapid and successful uptake of novel methods in sustainable catalysis.

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Hacking 3D printers as laboratory robots

The emergence of affordable and reliable 3D printers has enabled laboratories to optimize setups, print custom parts, accelerate research, and rapidly prototype. A new movement has emerged in the past...

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Room-Temperature Decarboxylative Amination of Electron-Deficient (Hetero)Aromatic Carboxylic Acids

Decarboxylative amination reactions offer the opportunity to access (hetero)aromatic amines from readily available carboxylic acid starting materials. However, the reliance of the Curtius rearrangemen...

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Bioinspired Diversification of Short Peptides via Tyrosine Umpolung | ChemRxiv

Herein, we report a bioinspired strategy for the selective modification of tyrosine residues in short peptides based on a formal umpolung of the phenolic side chain. Mild oxidation with a hypervalent iodine(V) reagent enables the in situ generation of ...

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Collective asymmetric synthesis of the Strychnos alkaloids via thiophene S,S-dioxide cycloadditions - Nature Chemistry

Thiophene S,S-dioxides are excellent substrates for cycloaddition reactions, but underused in target-oriented synthesis. Here the authors show how these heterocycles enable the asymmetric synthesis of...

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Process Development and Scale-Up of RLY-2139: A Selective CDK2 Inhibitor Targeting ER+/HER2– Breast Cancer

RLY-2139 is a potent and selective orthosteric CDK2/Cyclin E inhibitor in development for the treatment of ER+/HER2– breast cancer. It showed an on target IC50 of 4 nM for CDK2/CycE and good biochemic...

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Oxidative Cleavage of β-Substituted Primary Alcohols in Flow

Herein, we report a scalable oxidative cleavage of β-substituted primary alcohols under continuous-flow conditions using a silica-supported hypervalent iodine(V) catalyst and TBA-Oxone as terminal oxi...

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Fixing A Reaction

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Annulative Skeletal Diversification of Pyrimidines to Expanded Heteroaromatic Space

Single-atom skeletal editing has recently emerged as a powerful strategy for the direct diversification of the heterocyclic cores of various compounds. Yet, methods that enable monocycle-to-bicycle tr...

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Oxygen migration into carbon–carbon single bonds by photochemical oxidation - Nature Synthesis

Heteroatom insertions into chemically inert carbon–carbon single bonds are rare compared to their unsaturated analogues. Now, ligand-to-metal charge transfer offers a promising entry point for oxygen ...

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Deep-Red to Near-Infrared Light-Driven Radical Generation from Organoboron Compounds via Ligand-Induced Direct Excitation Catalysis

We report a catalytic strategy for generating carbon-centered radicals from organoboron compounds under deep-red to near-infrared (DR to NIR) light irradiation via direct excitation of substrate–catal...

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Safety Letter: Evaluation of the Popular Oxidant 2-Iodoxybenzoic Acid (IBX)

2-Iodoxybenzoic acid (IBX) is a versatile oxidant used in chemical synthesis. It has been employed as a reagent in more than 1400 publications since its initial use as an oxidant described in 1994. Wh...

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Magnetic Stirring May Cause Irreproducible Results in Chemical Reactions

Magnetic stirrers, the most widely used and ubiquitous devices for performing chemical reactions in laboratory settings, may cause reproducibility problems. Reproducibility in a range of chemical proc...

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Reimagining Advanced Chemistry Education: A Community-based Approach to Course Design for Modern Learners

Chemistry education at the graduate level and beyond faces the formidable challenge of a boundless and constantly expanding frontier of knowledge on many fronts. While modern learners have an increasi...

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Automated Determination of the Molecular Substructure from Nuclear Magnetic Resonance Spectra Using Neural Networks

Nuclear magnetic resonance (NMR) spectroscopy is an indispensable tool for determining the structural characteristics of a molecule by analyzing its chemical shifts. A wealth of NMR spectra therefore exists and continues to amass on a daily basis, at an ever-increasing rate owing to the progressive automation of chemical analysis. This growth and automation have led to the data analysis step in NMR spectroscopy becoming the main bottleneck in the structural characterization of a new chemical compound. In particular, the data interpretation step is slow and prone to error as it requires manual examination by a suitably trained scientist. Machine learning (ML) methods could overcome this bottleneck, pending that they can automatically correlate the collection of peaks in an NMR spectrum with the substructure of its subject molecule. This study explores the art of the possible using three types of ML methods that are based on neural-network architectures: a multilayer perceptron (MLP) + long short-term memory (LSTM) neural network, a convolutional neural network (CNN), and an MLP + recurrent neural network (RNN). NMR spectrum–structure correlations were encoded into each type of neural network using two forms of molecular representation, one employing functional groups and the other using a novel neighbor-based method. These models were trained on 34,503 and 17,311 experimental 13C and 1H NMR spectra, respectively. The influence of incorporating metadata about experimental conditions (NMR field strength, temperature, and solvent) into the neural-network model was also investigated. The models incorporated coupling constants as a proxy for spectral intensities in the case of 13C NMR spectra. We found that the MLP + LSTM model achieved the highest accuracy (88%) when trained on 13C NMR spectra and incorporating experimental metadata (compared to 77% without incorporating it). While the CNN model performance was slightly lower (86% accuracy), it determined molecular substructures in one-third of the computational run time compared to the MLP + LSTM model. Thus, the CNN model emerged as the practically best model when considering performance, time, and cost.

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Sulfur fluoride exchange with carbon pronucleophiles

Aryl alkyl sulfones are an important class of compounds in drug discovery; thus, new methods toward their synthesis are desirable. A general sulfur fluoride exchange (SuFEx) method to couple aryl sulf...

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Journal Impact Nonsense

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From carboxylic acids or their derivatives to amines and ethers: modern decarboxylative approaches for sustainable C–N and C–O bond formation

Amines and ethers represent essential structural motifs in pharmaceuticals, natural products, organic materials, and catalytic systems. The development of novel, environmentally friendly, and cost-eff...

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