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The lack of publicly available, large, and unbiased datasets is a key bottleneck for the application of machine learning (ML) methods in synthetic chemistry. Data from electronic laboratory notebooks (ELNs) could provide less biased, large datasets, but no such datasets have been made publicly available. The first real-world dataset from the ELNs of a large pharmaceutical company is disclosed and its relationship to high-throughput experimentation (HTE) datasets is described. For chemical yield predictions, a key task in chemical synthesis, an attributed graph neural network (AGNN) performs as good or better than the best previous models on two HTE datasets for the Suzuki and Buchwald-Hartwig reactions. However, training of the AGNN on the ELN dataset does not lead to a predictive model. The implications of using ELN data for training ML-based models are discussed in the context of yield predictions.

The borylation of aryl and heteroaryl C–H bonds is valuable for the site-selective functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine ligands catalyze the borylation of the aryl C–H bonds that are most acidic and least sterically hindered, but predicting the site of borylation in molecules containing multiple arenes is difficult. To address this challenge, we report a hybrid computational model that predicts the Site of Borylation (SoBo) in complex molecules. The SoBo model combines density functional theory, semi-empirical quantum mechanics, cheminformatics, linear regression, and machine learning to predict site selectivity and to extrapolate these predictions to new chemical space. Experimental validation of SoBo showed that the model predicts the major site of borylation of pharmaceutical intermediates with higher accuracy than prior machine-learning models or human experts, demonstrating that SoBo will be useful to guide experiments for the borylation of specific C(sp2)–H bonds during pharmaceutical development.

Ferrocene derivatives have a wide range of applications, including as ligands in asymmetric catalysis, due to their chemical stability, rigid backbone, steric bulk, and ability to encode stereochemical information via planar chirality. Unfortunately, few of the available molecular mechanics force fields incorporate parameters for the accurate study of this important building block. Here, we present a MM3* force field for ferrocenyl ligands, which was generated using the quantum-guided molecular mechanics (Q2MM) method. Detailed validation by comparison to DFT calculations and crystal structures demonstrates the accuracy of the parameters and uncovers the physical origin of deviations through excess energy analysis. Combining the ferrocene force field with a force field for Pd-allyl complexes and comparing the crystal structures shows the compatibility with previously developed MM3* force fields. Finally, the ferrocene force field was combined with a previously published transition-state force field to predict the stereochemical outcomes of the aminations of Pd-allyl complexes with different amines and different chiral ferrocenyl ligands, with an

Vinylbenziodoxolones have recently been identified as efficient hypervalent iodine(III) reagents for electrophilic vinylations under transition metal-free conditions. Their unique reactivity allows synthesis of either internal or terminal alkenes, depending on the nucleophile class. This paper constitutes the first mechanistic investigation of VBX vinylations, and makes use of NMR studies, deuterium labelling and computations to rationalize the observed regio- and stereochemical outcome. Internal alkene formation in S-vinylation was found to proceed through the ligand coupling mechanism typical of diaryliodonium salts, whereas terminal alkene formation in P-vinylations took place via a phosphinous acid-coordinated VBX complex, which underwent concerted deprotonation and Michael-type addition. Subsequent base-assisted protonation and E2 elimination delivered the terminal alkene. The findings can be used to predict the regioselectivity in vinylations of other nucleophile classes.

A bis(18‐crown‐6) Tröger's base receptor and 4‐substituted hepta‐1,7‐diyl bisammonium salt ligands have been used as a model system to study the interactions between non‐polar side chains of peptides and an aromatic cavity of a protein. NMR titrations and NOESY/ROESY NMR spectroscopy were used to analyze the discrimination of the ligands by the receptor based on the substituent of the ligand, both quantitatively (free binding energies) and qualitatively (conformations). The analysis showed that an all‐anti conformation of the heptane chain was preferred for most of the ligands, both free and when bound to the receptor, and that for all of the receptor‐ligand complexes, the substituent was located inside or partly inside of the aromatic cavity of the receptor. We estimated the free binding energy of a methyl‐ and a phenyl group to an aromatic cavity, via CH‐π, and combined aromatic CH‐π and π‐π interactions to be −1.7 and −3.3 kJ mol−1, respectively. The experimental results were used to assess the accuracy of different computational methods, including molecular mechanics (MM) and density functional theory (DFT) methods, showing that MM was superior., A model system to study interactions between aromatic cavities and non‐polar side chains was developed and studied by different NMR methods, where a weak but evident side‐chain discrimination was observed. The experimental quantitative and qualitative data was used to evaluate different computational methods, with the conclusion that for this system, molecular mechanics gave more accurate results than density functional theory calculations.

Vinylbenziodoxolones have recently been identified as efficient hypervalent iodine(III) reagents for electrophilic vinylations under transition metal-free conditions. The regiochemistry of the products have been found to vary with the nucleophile class, with thiols giving internal alkenes whereas phosphine oxides and similar P-nucleophiles give terminal alkenes. This paper constitutes the first mechanistic investigation of VBX vinylations, and makes use of NMR studies, deuterium label-ling and computations to rationalize the observed regio- and stereochemical outcome. While the S-vinylation was found to proceed through the ligand coupling mechanism typical of diaryliodonium salts, the P-vinylations took place via a phos-phinous acid-coordinated VBX complex, which underwent concerted deprotonation and Michael-type addition. Subsequent base-assisted protonation and E2 elimination delivered the terminal alkene. The findings can be used to predict the regiose-lectivity in vinylations of other nucleophile classes.

As more data are introduced in the building of models of chemical reactivity, the mechanistic component can be reduced until ‘big data’ applications are reached. These methods no longer depend on underlying mechanistic hypotheses, potentially learning them implicitly through extensive data training. Reactivity models often focus on reaction barriers, but can also be trained to directly predict lab-relevant properties, such as yields or conditions. Calculations with a quantum-mechanical component are still preferred for quantitative predictions of reactivity. Although big data applications tend to be more qualitative, they have the advantage to be broadly applied to different kinds of reactions. There is a continuum of methods in between these extremes, such as methods that use quantum-derived data or descriptors in machine learning models. Here, we present an overview of the recent machine learning applications in the field of chemical reactivity from a mechanistic perspective. Starting with a summary of how reactivity questions are addressed by quantum-mechanical methods, we discuss methods that augment or replace quantum-based modelling with faster alternatives relying on machine learning. Following a progression from quantum mechanics to modern data-driven methods, this Review presents the methodological spectrum of modelling organic reactions.

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to reach the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale. Application of this approach to the second hydride transfer transition state of HMG-CoA reductase from Pseudomonas mevalonii (PmHMGR) identified three remote residues, R396, E399 and L407, (15–27 Å away from the active site) that have a remote dynamic effect on enzyme activity. The predictions were subsequently validated experimentally via site-directed mutagenesis. These results show that microsecond timescale MD simulations of transition states are possible and can predict rather than just rationalize remote allosteric residues., Transition state force fields enable MD simulations at the transition state of HMGCoA reductase that sample the transition state ensemble on the μs timescale to identify remote residues that affect the reaction rate.

Application of computational methods to understanding and predicting properties of analogues for drug discovery has enjoyed a long history of success. However, the drug development space (post-cand...

The organic chemist’s toolbox is vast, with technologies to accelerate the synthesis of novel chemical matter. The field of asymmetric catalysis is one approach to accessing new areas of chemical space and computational power is today sufficient to assist in this exploration. Unfortunately, existing techniques generally require computational expertise and are therefore underutilized in synthetic chemistry. Here we present our platform Virtual Chemist, which allows bench chemists to predict outcomes of asymmetric chemical reactions ahead of testing in the laboratory, in just a few clicks. Modular workflows facilitate the simulation of various sets of experiments, including the four realistic scenarios discussed: one-by-one design, library screening, hit optimization and substrate-scope evaluation. Catalyst candidates are screened within hours and the enantioselectivity predictions provide substantial enrichments compared to random testing. The achieved accuracies within ~1 kcal mol–1 provide opportunities for computational chemistry in the field of asymmetric catalyst design, allowing bench chemists to guide the design and discovery of asymmetric catalysts. Computational chemistry has remained largely inaccessible to the experimental chemistry community. Here we report the VIRTUAL CHEMIST, a software suite free for academic use, that enables organic chemists without expertise in computational chemistry to perform virtual screening experiments for asymmetric catalyst discovery and design.

A method for generation of Pd/phosphite-oxazoline catalysts containing an alkyl backbone chain has been successfully applied to Pd-catalyzed allylic substitution reactions. By carefully selecting t...

The development of computational tools to support organic synthesis, including the prediction of reaction pathways, optimization and selectivity, is a topic of intense current interest. Transition state force fields, derived by the quantum-guided molecular mechanics method, rapidly calculate the stereoselectivity of organic reactions accurately enough to allow predictive virtual screening. Here we describe CatVS, an automated tool for the virtual screening of substrate and ligand libraries for asymmetric catalysis within hours. It is shown for the OsO4-catalysed cis-dihydroxylation that the results from the automated set-up are indistinguishable from a manual substrate screen. Predictive computational ligand selection is demonstrated in the virtual ligand screen of a library of diphosphine ligands for the rhodium-catalysed asymmetric hydrogenation of enamides. Subsequent experimental testing verified that the most selective substrate–ligand combinations are successfully identified by the virtual screen. CatVS is therefore a promising tool to increase the efficiency of high-throughput experimentation. Predicting highly enantioselective ligands for a given asymmetric catalytic reaction is very challenging, but could greatly reduce the need for high-throughput, trial-and-error experimentation. Here, the authors report a freely available, automated tool to identify appropriate chiral ligands for given substrates in asymmetric catalysis.

At the early stages of the drug development process, thousands of compounds are synthesized in order to attain the best possible potency and pharmacokinetic properties. Once successful scaffolds are identified, large libraries of analogues are made, which is a challenging and time-consuming task. Recently, late stage functionalization (LSF) has become increasingly prominent since these reactions selectively functionalize C-H bonds, allowing to quickly produce analogues. Classical electrophilic aromatic halogenations are a powerful type of reaction in the LSF toolkit. However, the introduction of an electrophile in a regioselective manner on a drug-like molecule is a challenging task. Herein we present a machine learning model able to predict the reactive site of an electrophilic aromatic substitution with an accuracy of 93% (internal validation set). The model takes as input a SMILES of a compound and uses six quantum mechanics descriptors to identify its reactive site(s). On an external validation set, 90% of all molecules were correctly predicted.

The conjugate addition of aryl boronic acids to enones is a powerful synthetic tool to introduce quaternary chiral centers, but the experimentally observed stereoselectivities vary widely, and the identification of suitable substrate–ligand combinations requires significant effort. We describe the development and application of a transition-state force field (TSFF) by the quantum-guided molecular mechanics (Q2MM) method that is validated using an automated screen of 9 ligands, 38 aryl boronic acids, and 22 enones, leading to a MUE of 1.8 kJ/mol and a R(2) value of 0.877 over 82 examples. A detailed error analysis identified the structural origin for the deviations in the small group of outliers. The TSFF was then used to predict the stereoselectivity for 27 ligands and 59 enones. The vast majority of the virtual screening results are in line with the expected results. Selected results for 6-substituted pyrox ligands, which were not part of the training set, were followed up by density functional theory and experimental studies.

The parameterization of a transition state force field for the title reaction is described. Validation for 82 literature examples leads to a MUE of 1.8 kJ/mol and an R2 of 0.877 between computed and experimental stereoselectivities. The use if the TSFF is demonstrated for a virtual library of 27 ligands and 59 enones.

The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we have shown that transition state force fields (TSFFs), fitted to the functional form of MM3* force fields using the quantum guided molecular mechanics (Q2MM) method, provide an accurate description of transition states that can be used for stereoselectivity predictions of small molecule reactions. Here, we demonstrate the applicability of the method for fit TSFFs to the well-established Amber force field, which could be used for molecular dynamics studies of enzyme reaction. As a case study, the fitting of a TSFF to the second hydride transfer in Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed.

Photodegradation of pharmaceutical and agrochemical compounds is an important concern for health and the environment. Amiloride derivatives undergo clean photosubstitution in protic solvents. We have studied this apparent photo-SNAr reaction with a range of experimental and computational techniques. Available evidence points to a mechanism starting with photoexcitation followed by absorption of a second photon to eject an electron to give a radical cation intermediate. Subsequent substitution reaction with the protic solvent is assisted by a general base, possibly strengthened by the proximal solvated electron. Final recombination with the solvated electron generates the observed product. Quantum chemical computations reveal that excited state antiaromaticity is relieved when an electron is ejected from the photoexcited molecule by the second photon, leading to a weakly aromatic radical cation. The mechanism indicated here could have wide applicability to photoinduced degradation of similar heteroaromatic compounds in the environment as well as in protic solvents. There are also strong similarities to a class of increasingly popular synthetic photoredox methods.

A transition state force field (TSFF) was developed using the quantum-guided molecular mechanics (Q2MM) method to describe the stereodetermining migratory insertion step of the enantioselective redox-relay Heck reaction for a range of multisubstituted alkenes. We show that the TSFF is highly predictive through an external validation of the TSFF against 151 experimentally determined stereoselectivities resulting in an R(2) of 0.89 and MUE of 1.8 kJ/mol. In addition, limitations in the underlying force field were identified by comparison of the TSFF results to DFT level calculations. A novel application of the TSFF was demonstrated for 31 cases where the enantiomer predicted by the TSFF differed from the originally published values. Experimental determination of the absolute configuration demonstrated that the computational predictions were accurate, suggesting that TSFFs can be used for the rapid prediction of the absolute stereochemistry for a class of reactions. Finally, a virtual ligand screen was conducted utilizing both the TSFF and a simple molecular correlation method. Both methods were similarly predictive, but the TSFF was able to show greater utility through transferability, speed, and interpretability.

Compounds with dibenzannelated heterocycles with eight π-electrons are found in a range of applications. These molecules often adopt a bent structure in the ground state (S0 ) but can become planar in the first excited states (S1 and T1 ) because of the cyclically conjugated 4nπ central ring, which fulfils the requirements for excited state aromaticity. We report on a quantum chemical investigation of the aromatic character in the S1 and T1 states of dibenzannelated seven- and six-membered heterocycles with one, two, or three heteroatoms in the 8π-electron ring. These states could have ππ* or nπ* character. We find that compounds with one or two heteroatoms in the central ring have ππ* states as their S1 and T1 states. They are to a significant degree influenced by excited state aromaticity, and their optimal structures are planar or nearly planar. Among the heteroatoms, nitrogen provides for the strongest excited state aromaticity whereas oxygen provides for the weakest, following the established trend of the S0 state. Yet, dibenzannelated seven-membered-ring compounds with N=N bonds have non-aromatic nπ* states with strongly puckered structures as their S1 and T1 states.

Microbial arene oxidation of benzoic acid with Ralstonia eutropha B9 provides a chiral highly functionalized cyclohexadiene, suitable for further structural diversification. Subjecting this scaffold to a palladium-catalyzed Heck reaction effects a regioselective and stereoselective arylation of the cyclohexadiene ring. The arylation proceeds with a highly selective 1,3-chirality transfer of stereogenic information installed in the microbial arene oxidation. Quantum chemical calculations have provided insightinto the mechanism of the palladium catalyzed arylation. The high selectivity can be explained both by a kinetic preference for the observed arylation position and, interestingly, by reversible carbopalladation in competing positions. Functional groups that were well tolerated on the diene substrate included a range of esters, amides and a Weinreb amide, affording a total of 23 different productsin good yields. These products, which can be considered as latent enolic nucleophiles, also possess a unique three dimensional structure which can be utilized in further stereoselective transformations. This was demonstrated by subjecting one of the products, which contained a protected aldehyde, to a tandem deprotection – cyclization sequence. The reaction proceeded with complete stereoselectivityand afforded a tricyclic ketone product possessing four stereogenic centers. This demonstrates the capability of the method to introduce stereochemical complexity from a planar molecule such as benzoic acid in just a few steps.

Summary Haloaromatic drug molecules of the amiloride family are plagued by photodegradation with associated toxicity. Herein, we report on the photodegradation of analogs of amiloride, which are known to undergo photosubstitution in water. Model compounds built on the same scaffold undergo clean photosubstitution also in alcoholic solvent, where a certain amount of photodehalogenation is normally expected. Available evidence points to a mechanism starting with photoexcitation followed by photoionization to give a radical cation intermediate. Subsequent substitution reaction with the protic solvent is assisted by a general base, possibly strengthened by the proximal solvated electron. Recombination with the solvated electron generates the observed product. Quantum chemical computations reveal that excited state antiaromaticity is relieved when an electron is ejected from the photoexcited molecule by the second photon. The mechanism indicated here could have wide applicability to photoinduced degradation of similar heteroaromatic compounds in the environment, as well as to a class of increasingly popular synthetic photoredox methods.

During compatibility study of the AZD7986 project, a peak of 3 area% at the tail (RRT 1.03) of the active pharmaceutical ingredient (API) was discovered for all tablets containing sodium stearyl fumarate (PRUV) under humid condition (e.g. 50 °C/75% RH), regardless of choice of disintegrant or filler combination. The degradant was needed to be identified to understand the corresponding reaction mechanism and help the final formulation design. Structure elucidation was therefore done by analysis using high resolution mass spectrometry. The degradant was found to be a Michael addition product of the API and fumaric acid. Reaction between deuterated fumaric acid and the API was carried to confirm the proposed structure and reaction mechanism. Fumaric acid was a degradant product of PRUV in the presence of other excipients, revealed by the stability study. The Michael addition reaction needs facilitation by water and basic conditions. The result from this study should serve as a precaution note for projects using PRUV as one of excipients where the API could act as a nucleophile. In such cases the microenvironment should be optimised to minimize the reaction, such as pH adjustment and incorporating protection from moisture.

Microbial arene oxidation of benzoic acid with Ralstonia eutropha B9 provides a chiral highly functionalized cyclohexadiene, suitable for further structural diversification. Subjecting this scaffold to a palladium-catalyzed Heck reaction effects a regioselective and stereospecific arylation of the cyclohexadiene ring, with transfer of the stereogenic information installed in the microbial arene oxidation. Functional groups that were well tolerated on the diene substrate included a range of esters, amides and a Weinreb amide, affording a total of 23 different products in good yields. These products, which can be considered as latent enolic nucleophiles, also possess a unique three dimensional structure which can be utilized in further stereoselective transformations. This was demonstrated by subjecting one of the products, which contained a protected aldehyde, to a tandem deprotection – cyclization sequence. The reaction proceeded with complete stereoselectivity and afforded a tricyclic ketone product possessing four stereogenic centers. This demonstrates the capability of the method to introduce stereochemical complexity from non-chiral benzoic acid in just a few steps. Quantum chemical calculations have provided insight into the mechanism of the palladium-catalyzed arylation. The high selectivity can be explained both by a kinetic preference for the observed arylation position and by reversible carbopalladation in competing positions.

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. QM/MM methods have been extensively used to study these reactions, but the difficulties arising from the hybrid treatment of the system are well documented. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to react the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale. Application of this approach the second hydride transfer transition state of HMG-CoA reductase from Pseudomonas mevalonii (PmHMGR) identified three remote residues, R396 E399 and L407, (15-27 Å away from the active site) that have a remote dynamic effect on enzyme activity. The predictions were subsequently validated experimentally via site-directed mutagenesis. These results show that microsecond timescale MD simulations of transition states are possible and can predict rather than just rationalize remote allosteric residues.

The organic chemist’s toolbox is vast with technologies to accelerate the synthesis of novel chemical matter. The field of asymmetric catalysis is one approach to access new areas of chemical space and computational power is today sufficient to assist in this exploration. Unfortunately, existing techniques generally require computational expertise and are therefore under-utilized in synthetic chemistry. We present herein our platform Virtual Chemist that allows bench chemists to predict outcomes of asymmetric chemical reactions ahead of testing in the lab, in just a few clicks. Modular workflows facilitate the simulation of various sets of experiments, including the four realistic scenarios discussed: one-by-one design, library screening, hit optimization, and substrate scope evaluation. Catalyst candidates are screened within hours and the enantioselectivity predictions provide substantial enrichments compared to random testing. The achieved accuracies within ~1 kcal/mol provide new opportunities for computational chemistry in asymmetric catalysis.

Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities.

Quantum-Guided Molecular Mechanics (Q2MM) can be used to derive transition state force fields (TSFFs) that allow the fast and accurate predictions of stereoselectivity for a wide range of catalytic enantioselective reactions. The basic ideas behind the derivation of TSFFs using Q2MM are discussed and the steps involved in obtaining a TSFF using the Q2MM code, publically available at github.com/q2mm, are shown. The applicability for a range of reactions, including several non-standard applications of Q2MM, is demonstrated. Future developments of the method are also discussed.

The substrate scope and the mechanism have been investigated for the MnCl2-catalyzed cross coupling reaction between aryl halides and Grignard reagents. The transformation proceeds rapidly and in good yield when the aryl halide is a chloride containing a cyano or an ester group in the para position or a cyano group in the ortho position. A range of other substituents gave no conversion of the aryl halide or led to the formation of side products. A broader scope was observed for the Grignard reagents where a variety of alkyl- and arylmagnesium chlorides participated in the coupling. Two radical clock experiments were performed which in both cases succeeded in trapping an intermediate aryl radical. The cross coupling is therefore believed to proceed by a SRN1 mechanism, where a triorganomanganate complex serves as the most likely nucleophile and single electron donor. Other mechanistic scenarios were excluded based on the substrate scope of the aryl halide.

Summary Efficient functionalization of C−H bonds can be achieved using transition metal catalysts, such as Pd(OAc)2. To better control the regioselectivity in these reactions, some functional groups on the substrate may be used as directing groups, guiding the reactivity to an ortho position. Herein, we describe a methodology to score the relative strength of such directing groups in palladium-catalyzed aromatic C−H activation. The results have been collected into a scale that serves to predict the regioselectivity on molecules with multiple competing directing groups. We demonstrate that this scale yields accurate predictions on over a hundred examples, taken from the literature. In addition to the regioselectivity prediction on complex molecules, the knowledge of the relative strengths of directing groups can also be used to work with new combinations of functionalities, exploring uncharted chemical space., Graphical Abstract, Highlights • Directing group strength for ortho-palladation can be predicted quantum chemically • Correlation with fragments allow regioselectivity predictions in complex molecules • Directing strength is enhanced by deprotonation under the reaction conditions • Palladation in between two directing groups is disfavored sterically; no synergy, Catalysis; Computational Molecular Modelling; Organic Reaction

1,4‐ and 1,5‐diols undergo cyclodehydration upon treatment with cationic N‐heterocyclic carbene (NHC)–IrIII complexes to give tetrahydrofurans and tetrahydropyrans, respectively. The mechanism was investigated, and a metal‐hydride‐driven pathway was proposed for all substrates, except for very electron‐rich ones. This contrasts with the well‐established classical pathways that involve nucleophilic substitution., Hydrogen transfer vs. acid catalysis: Mechanistic studies on the iridium‐catalyzed cyclodehydration of a series of diols are carried out. Hammett and Hammett–Brown analyses of the reactivity data are compared, along with kinetic isotope effect and crossover experiments. This analysis enabled the elucidation of the reaction mechanisms, which are found to be dependent on the electronic properties of the substrates (see picture).

Hydrogen borrowing provides an efficient and atom economical method for carbon–nitrogen and carbon–carbon bond formation from alcohol precursors. Glycerol is a renewable nontoxic polyol and a potential precursor to small functional organic molecules. We here report the direct amination of solketal, a 1,2-hydroxy-protected derivative of glycerol, via ruthenium-catalyzed hydrogen borrowing, affording up to 99% conversion and 92% isolated yield using [Ru(p-cymene)Cl2]2 as the catalyst precursor. The synthesis of an antitussive agent in 86% overall yield from solketal was also demonstrated using this methodology.

The highly enantioselective hydrogenation of linear enones catalyzed by Ir complexes that bear a chiral P,N ligand have been investigated computationally. Compared to the results of previous studies, the mechanism is different because of the coordination of the substrate. In the favored pathway Ir stays in the +3 oxidation state throughout the entire catalytic cycle, the olefinic group is coordinated trans to the ligand N atom, and the carbonyl group binds trans to a spectator hydride. After migratory insertion, a H2 coordinates and delivers the second H atom by σ-metathesis. The calculated path rationalizes the observed enantioselectivities and allows the development of a predictive quadrant model for this class of substrate–ligand combination.