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We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using text-like representation of chemical reactions (SMILES) and Natural Language Processing (NLP) neural network Transformer architecture. We showed that data augmentation, which is a powerful method used in image processing, eliminated the effect of data memorization by neural networks and improved their performance for prediction of new sequences. This effect was observed when augmentation was used simultaneously for input and the target data simultaneously. The top-5 accuracy was 84.8% for the prediction of the largest fragment (thus identifying principal transformation for classical retro-synthesis) for the USPTO-50k test dataset, and was achieved by a combination of SMILES augmentation and a beam search algorithm. The same approach provided significantly better results for the prediction of direct reactions from the single-step USPTO-MIT test set. Our model achieved 90.6% top-1 and 96.1% top-5 accuracy for its challenging mixed set and 97% top-5 accuracy for the USPTO-MIT separated set. It also significantly improved results for USPTO-full set single-step retrosynthesis for both top-1 and top-10 accuracies. The appearance frequency of the most abundantly generated SMILES was well correlated with the prediction outcome and can be used as a measure of the quality of reaction prediction. Development of algorithms to predict reactant and reagents given a target molecule is key to accelerate retrosynthesis approaches. Here the authors demonstrate that applying augmentation techniques to the SMILE representation of target data significantly improves the quality of the reaction predictions.

To increase the reliability and success rate of drug discovery, efforts have been made to increase the C( sp 3 ) fraction and avoid flat molecules. sp 3 -Rich enantiopure amines are most frequently encountered as chiral auxiliaries, synthetic intermediates for pharmaceutical agents and bioactive natural products. Streamlined construction of chiral aliphatic amines has long been regarded as a paramount challenge. Mainstream approaches, including hydrogenation of enamines and imines, C–H amination, and alkylation of imines, were applied for the synthesis of chiral amines with circumscribed skeleton structures; typically, the chiral carbon centre was adjacent to an auxiliary aryl or ester group. Herein, we report a mild and general nickel-catalysed asymmetric reductive hydroalkylation to effectively convert enamides and enecarbamates into drug-like α-branched chiral amines and derivatives. This reaction involves the regio- and stereoselective hydrometallation of an enamide or enecarbamate to generate a catalytic amount of enantioenriched alkylnickel intermediate, followed by C–C bond formation via alkyl electrophiles. Enantiopure aliphatic amines are frequently encountered as chiral auxiliaries and synthetic intermediates for bioactive compounds. Here, the authors report a mild nickel-catalysed asymmetric reductive hydroalkylation to convert enamides and enecarbamates into α-branched chiral amines and derivatives.

Molecular recognition, binding and catalysis are often mediated by non-covalent interactions involving aromatic functional groups. Although the relative complexity of these so-called π interactions has made them challenging to study, theory and modelling have now reached the stage at which we can explain their physical origins and obtain reliable insight into their effects on molecular binding and chemical transformations. This offers opportunities for the rational manipulation of these complex non-covalent interactions and their direct incorporation into the design of small-molecule catalysts and enzymes. Our increasing understanding of non-covalent interactions involving aromatic systems is reviewed, and the use of these insights in the design of small-molecule catalysts and enzymes is surveyed. Non-covalent interactions in catalyst design (Toste 21701, Review) Non-covalent interactions involving aromatic systems play an important part in molecular recognition and binding. Dean Toste and colleagues survey our growing understanding of the physical factors that govern these complex interactions and examine how such interactions influence chemical transformations. The insights gained from computational and empirical studies make it increasingly possible to incorporate such subtle non-covalent interactions into the design of small-molecule catalysts and enzymes.

A mechanistic understanding of catalytic organic reactions is crucial for the design of new catalysts, modes of reactivity and the development of greener and more sustainable chemical processes 1 – 13 . Kinetic analysis lies at the core of mechanistic elucidation by facilitating direct testing of mechanistic hypotheses from experimental data. Traditionally, kinetic analysis has relied on the use of initial rates 14 , logarithmic plots and, more recently, visual kinetic methods 15 – 18 , in combination with mathematical rate law derivations. However, the derivation of rate laws and their interpretation require numerous mathematical approximations and, as a result, they are prone to human error and are limited to reaction networks with only a few steps operating under steady state. Here we show that a deep neural network model can be trained to analyse ordinary kinetic data and automatically elucidate the corresponding mechanism class, without any additional user input. The model identifies a wide variety of classes of mechanism with outstanding accuracy, including mechanisms out of steady state such as those involving catalyst activation and deactivation steps, and performs excellently even when the kinetic data contain substantial error or only a few time points. Our results demonstrate that artificial-intelligence-guided mechanism classification is a powerful new tool that can streamline and automate mechanistic elucidation. We are making this model freely available to the community and we anticipate that this work will lead to further advances in the development of fully automated organic reaction discovery and development. Mechanistic elucidation through currently available kinetic analysis is limited by mathematical approximations and human interpretation, here a deep neural network model has been trained to analyse ordinary kinetic data and automatically elucidate the corresponding mechanism class.

When searching for the ideal molecule to fill a particular functional role (for example, a medicine), the difference between success and failure can often come down to a single atom 1 . Replacing an aromatic carbon atom with a nitrogen atom would be enabling in the discovery of potential medicines 2 , but only indirect means exist to make such C-to-N transmutations, typically by parallel synthesis 3 . Here, we report a transformation that enables the direct conversion of a heteroaromatic carbon atom into a nitrogen atom, turning quinolines into quinazolines. Oxidative restructuring of the parent azaarene gives a ring-opened intermediate bearing electrophilic sites primed for ring reclosure and expulsion of a carbon-based leaving group. Such a ‘sticky end’ approach subverts existing atom insertion–deletion approaches and as a result avoids skeleton-rotation and substituent-perturbation pitfalls common in stepwise skeletal editing. We show a broad scope of quinolines and related azaarenes, all of which can be converted into the corresponding quinazolines by replacement of the C3 carbon with a nitrogen atom. Mechanistic experiments support the critical role of the activated intermediate and indicate a more general strategy for the development of C-to-N transmutation reactions. A new type of transformation converting a heteroaromatic carbon atom into a nitrogen atom, turning quinolines into quinazolines to enable manipulation of molecular properties, is reported.

A long-standing challenge in synthetic chemistry is the development of the transamidation reaction. This process, which involves the conversion of one amide to another, is typically plagued by unfavourable kinetic and thermodynamic factors. Although some advances have been made with regard to the transamidation of primary amide substrates, secondary amide transamidation has remained elusive. Here we present a simple two-step approach that allows for the elusive overall transformation to take place using non-precious metal catalysis. The methodology proceeds under exceptionally mild reaction conditions and is tolerant of amino-acid-derived nucleophiles. In addition to overcoming the classic problem of secondary amide transamidation, our studies expand the growing repertoire of new transformations mediated by base metal catalysis. Transamidation reactions are kinetically and thermodynamically challenging because of the stability of the amide starting materials. Here, the authors show a two-step process—activation of a secondary amide, followed by nickel-catalysed C–N bond cleavage—that allows mild and high yielding transamidation.

The intermolecular three-component alkene vicinal dicarbofunctionalization (DCF) reaction allows installation of two different carbon fragments. Despite extensive investigation into its ionic chemistry, the enantioseletive radical-mediated versions of DCF reactions remain largely unexplored. Herein, we report an intermolecular, enantioselective three-component radical vicinal dicarbofunctionalization reaction of olefins enabled by merger of radical addition and cross-coupling using photoredox and copper dual catalysis. Key to the success of this protocol relies on chemoselective addition of acyl and cyanoalkyl radicals, generated in situ from the redox-active oxime esters by a photocatalytic N-centered iminyl radical-triggered C-C bond cleavage event, onto the alkenes to form new carbon radicals. Single electron metalation of such newly formed carbon radicals to TMSCN-derived L1 Cu(II)(CN) 2 complex leads to asymmetric cross-coupling. This three-component process proceeds under mild conditions, and tolerates a diverse range of functionalities and synthetic handles, leading to valuable optically active β –cyano ketones and alkyldinitriles, respectively, in a highly enantioselective manner (>60 examples, up to 97% ee). Vicinal dicarbofunctionalization (DCF) reactions of alkenes have been extensively explored in ionic chemistry but the enantioselective radical mediated version of DCF remains largely unexplored. Here, the authors demonstrate a radical vicinal DCF reaction of olefins by merging of radical addition and cross-coupling using photoredox and copper dual catalysis.

Frustrated Lewis pairs (FLPs) are well documented for the activation of small molecules such as dihydrogen and carbon dioxide 1 – 4 . Although canonical FLP chemistry is heterolytic in nature, recent work has shown that certain FLPs can undergo single-electron transfer to afford radical pairs 5 . Owing to steric encumbrance and/or weak bonding association, these radicals do not annihilate one another, and they have thus been named frustrated radical pairs (FRPs). Notable preliminary results suggest that FRPs may be useful reagents in chemical synthesis 6 – 8 , although their applications remain limited. Here we demonstrate that the functionalization of C( sp 3 )–H bonds can be accomplished using a class of FRPs generated from disilazide donors and an N -oxoammonium acceptor. Together, these species undergo single-electron transfer to generate a transient and persistent radical pair capable of cleaving unactivated C–H bonds to furnish aminoxylated products. By tuning the structure of the donor, it is possible to control regioselectivity and tailor reactivity towards tertiary, secondary or primary C–H bonds. Mechanistic studies lend strong support for the formation and involvement of radical pairs in the target reaction. Regioselective functionalization of aliphatic carbon–hydrogen bonds is achieved using frustrated radical pairs generated from disilazide donors and an N -oxoammonium acceptor.

Synthetic chemistry aims to build up molecular complexity from simple feedstocks 1 . However, the ability to exert precise changes that manipulate the connectivity of the molecular skeleton itself remains limited, despite possessing substantial potential to expand the accessible chemical space 2 , 3 . Here we report a reaction that ‘deletes’ nitrogen from organic molecules. We show that N -pivaloyloxy- N -alkoxyamides, a subclass of anomeric amides, promote the intermolecular activation of secondary aliphatic amines to yield intramolecular carbon–carbon coupling products. Mechanistic experiments indicate that the reactions proceed via isodiazene intermediates that extrude the nitrogen atom as dinitrogen, producing short-lived diradicals that rapidly couple to form the new carbon–carbon bond. The reaction shows broad functional-group tolerance, which enables the translation of routine amine synthesis protocols into a strategy for carbon–carbon bond constructions and ring syntheses. This is highlighted by the use of this reaction in the syntheses and skeletal editing of bioactive compounds. Nitrogen is ‘deleted’ from secondary amines using anomeric amide reagents, which react with the amine to form an isodiazene, after which nitrogen gas is released and the resulting carbon radicals combine to form a carbon–carbon bond.

New carbon–carbon bond formation reactions expand our horizon of retrosynthetic analysis for the synthesis of complex organic molecules. Although many methods are now available for the formation of C( sp 2 )–C( sp 3 ) and C( sp 3 )–C( sp 3 ) bonds via transition metal-catalyzed cross-coupling of alkyl organometallic reagents, direct use of readily available olefins in a formal fashion of hydrocarbonation to make C( sp 2 )–C( sp 3 ) and C( sp 3 )–C( sp 3 ) bonds remains to be developed. Here we report the discovery of a general process for the intermolecular reductive coupling of unactivated olefins with alkyl or aryl electrophiles under the promotion of a simple nickel catalyst system. This new reaction presents a conceptually unique and practical strategy for the construction of C( sp 2 )–C( sp 3 ) and C( sp 3 )–C( sp 3 ) bonds without using any organometallic reagent. The reductive olefin hydrocarbonation also exhibits excellent compatibility with varieties of synthetically important functional groups and therefore, provides a straightforward approach for modification of complex organic molecules containing olefin groups. Olefins are employed in many coupling procedures but direct hydrocarbonations of unactivated olefins remain to be developed. Here, the authors report the nickel-catalyzed reductive coupling of olefins with aryl and alky electrophiles under mild conditions and with a broad substrate scope.