Advances in machine learning with chemical language models in molecular property and reaction outcome predictions.

Molecular properties and reactions form the foundation of chemical space. Over the years, innumerable molecules have been synthesized, a smaller fraction of them found immediate applications, while a larger proportion served as a testimony to creative and empirical nature of the domain of chemical science. With increasing emphasis on sustainable practices, it is desirable that a target set of molecules are synthesized preferably through a fewer empirical attempts instead of a larger library, to realize an active candidate. In this front, predictive endeavors using machine learning (ML) models built on available data acquire high timely significance. Prediction of molecular property and reaction outcome remain one of the burgeoning applications of ML in chemical science. Among several methods of encoding molecular samples for ML models, the ones that employ language like representations are gaining steady popularity. Such representations would additionally help adopt well-developed natural language processing (NLP) models for chemical applications. Given this advantageous background, herein we describe several successful chemical applications of NLP focusing on molecular property and reaction outcome predictions. From relatively simpler recurrent neural networks (RNNs) to complex models like transformers, different network architecture have been leveraged for tasks such as de novo drug design, catalyst generation, forward and retro-synthesis predictions. The chemical language model (CLM) provides promising avenues toward a broad range of applications in a time and cost-effective manner. While we showcase an optimistic outlook of CLMs, attention is also placed on the persisting challenges in reaction domain, which would optimistically be addressed by advanced algorithms tailored to chemical language and with increased availability of high-quality datasets.

Molecular Machine Learning for Chemical Catalysis: Prospects and Challenges.

ConspectusIn the domain of reaction development, one aims to obtain higher efficacies as measured in terms of yield and/or selectivities. During the empirical cycles, an admixture of outcomes from low to high yields/selectivities is expected. While it is not easy to identify all of the factors that might impact the reaction efficiency, complex and nonlinear dependence on the nature of reactants, catalysts, solvents, etc. is quite likely. Developmental stages of newer reactions would typically offer a few hundreds of samples with variations in participating molecules and/or reaction conditions. These "observations" and their "output" can be harnessed as valuable labeled data for developing molecular machine learning (ML) models. Once a robust ML model is built for a specific reaction under development, it can predict the reaction outcome for any new choice of substrates/catalyst in a few seconds/minutes and thus can expedite the identification of promising candidates for experimental validation. Recent years have witnessed impressive applications of ML in the molecular world, most of them aimed at predicting important chemical or biological properties. We believe that an integration of effective ML workflows can be made richly beneficial to reaction discovery.As with any new technology, direct adaptation of ML as used in well-developed domains, such as natural language processing (NLP) and image recognition, is unlikely to succeed in reaction discovery. Some of the challenges stem from ineffective featurization of the molecular space, unavailability of quality data and its distribution, in making the right choice of ML model and its technically robust deployment. It shall be noted that there is no universal ML model suitable for an inherently high-dimensional problem such as chemical reactions. Given these backgrounds, rendering ML tools conducive for reactions is an exciting as well as challenging endeavor at the same time. With the increased availability of efficient ML algorithms, we focused on tapping their potential for small-data reaction discovery (a few hundreds to thousands of samples).In this Account, we describe both feature engineering and feature learning approaches for molecular ML as applied to diverse reactions of high contemporary interest. Among these, catalytic asymmetric hydrogenation of imines/alkenes, ß-C(sp3)-H bond functionalization, and relay Heck reaction employed a feature engineering approach using the quantum-chemically derived physical organic descriptors as the molecular features─all designed to predict the enantioselectivity. The selection of molecular features to customize it for a reaction of interest is described, along with emphasizing the chemical insights that could be gathered through the use of such features. Feature learning methods for predicting the yield of Buchwald-Hartwig cross-coupling, deoxyfluorination of alcohols, and enantioselectivity of N,S-acetal formation are found to offer excellent predictions. We propose a transfer learning protocol, wherein an ML model such as a language model is trained on a large number of molecules (105-106) and fine-tuned on a focused library of target task reactions, as an effective alternative for small-data reaction discovery (102-103 reactions). The exploitation of deep neural network latent space as a method for generative tasks to identify useful substrates for a reaction is demonstrated as a promising strategy.

Combinatorial Ligand Assisted Simultaneous Control of Axial and Central Chirality in Highly Stereoselective C-H Allylation.

The significance of stereoselective C-H bond functionalization thrives on its direct application potential to pharmaceuticals or complex chiral molecule synthesis. Complication arises when there are multiple stereogenic elements such as a center and an axis of chirality to control. Over the years cooperative assistance of multiple chiral ligands has been applied to control only chiral centers. In this work, we harness the essence of cooperative ligand approach to control two different stereogenic elements in the same molecule by atroposelective allylation to synthesize axially chiral biaryls from its racemic precursor. The crucial roles played by chiral phosphoric acid and chiral amino acid ligand in concert helped us to obtain one major stereoisomer out of four distinct possibilities.

Role of Noncovalent Interactions in Inducing High Enantioselectivity in an Alcohol Reductive Deoxygenation Reaction Involving a Planar Carbocationic Intermediate.

The involvement of planar carbocation intermediates is generally considered undesirable in asymmetric catalysis due to the difficulty in gaining facial control and their intrinsic stability issues. Recently, suitably designed chiral catalyst(s) have enabled a guided approach of nucleophiles to one of the prochiral faces of carbocations affording high enantiocontrol. Herein, we present the vital mechanistic insights from our comprehensive density functional theory (B3LYP-D3) study on a chiral Ir-phosphoramidite-catalyzed asymmetric reductive deoxygenation of racemic tertiary α-substituted allenylic alcohols. The catalytic transformation relies on the synergistic action of a phosphoramidite-modified Ir catalyst and Bi(OTf)3, first leading to the formation of an Ir-π-allenyl carbocation intermediate through a turn-over-determining SN1 ionization, followed by a face-selective hydride transfer from a Hantzsch ester analogue to yield an enantioenriched product. Bi(OTf)3 was found to promote a significant number of ionic interactions as well as noncovalent interactions (NCIs) with the catalyst and the substrates (allenylic alcohol and Hantzsch ester), thus providing access to a lower energy route as compared to the pathways devoid of Bi(OTf)3. In the nucleophilic addition, the chiral induction was found to depend on the number and efficacy of such key NCIs. The curious case of reversal of enantioselectivity, when the α-substituent of the allenyl alcohol is changed from methyl to cyclopropyl, was identified to originate from a change in mechanism from an enantioconvergent pathway (α-methyl) to a dynamic kinetic asymmetric transformation (α-cyclopropyl). These molecular insights could lead to newer strategies to tame tertiary carbocations in enantioselective reactions using suitable combinations of catalysts and additives.

Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions.

Burgeoning developments in machine learning (ML) and its rapidly growing adaptations in chemistry are noteworthy. Motivated by the successful deployments of ML in the realm of molecular property prediction (MPP) and chemical reaction prediction (CRP), herein we highlight some of its most recent applications in predictive chemistry. We present a nonmathematical and concise overview of the progression of ML implementations, ranging from an ensemble-based random forest model to advanced graph neural network algorithms. Similarly, the prospects of various feature engineering and feature learning approaches that work in conjunction with ML models are described. Highly accurate predictions reported in MPP tasks (e.g., lipophilicity, solubility, distribution coefficient), using methods such as D-MPNN, MolCLR, SMILES-BERT, and MolBERT, offer promising avenues in molecular design and drug discovery. Whereas MPP pertains to a given molecule, ML applications in chemical reactions present a different level of challenge, primarily arising from the simultaneous involvement of multiple molecules and their diverse roles in a reaction setting. The reported RMSEs in MPP tasks range from 0.287 to 2.20, while those for yield predictions are well over 4.9 in the lower end, reaching thresholds of >10.0 in several examples. Our Review concludes with a set of persisting challenges in dealing with reaction data sets and an overall optimistic outlook on benefits of ML-driven workflows for various MPP as well as CRP tasks.

A unified machine-learning protocol for asymmetric catalysis as a proof of concept demonstration using asymmetric hydrogenation.

Design of asymmetric catalysts generally involves time- and resource-intensive heuristic endeavors. In view of the steady increase in interest toward efficient catalytic asymmetric reactions and the rapid growth in the field of machine learning (ML) in recent years, we envisaged dovetailing these two important domains. We selected a set of quantum chemically derived molecular descriptors from five different asymmetric binaphthyl-derived catalyst families with the propensity to impact the enantioselectivity of asymmetric hydrogenation of alkenes and imines. The predictive power of the random forest (RF) built using the molecular parameters of a set of 368 substrate-catalyst combinations is found to be impressive, with a root-mean-square error (rmse) in the predicted enantiomeric excess (%ee) of about 8.4 ± 1.8 compared to the experimentally known values. The accuracy of RF is found to be superior to other ML methods such as convolutional neural network, decision tree, and eXtreme gradient boosting as well as stepwise linear regression. The proposed method is expected to provide a leap forward in the design of catalysts for asymmetric transformations.

Molecular Insights on Solvent Effects in Organic Reactions as Obtained through Computational Chemistry Tools.

Molecular understanding of the role of protic solvents in a gamut of organic transformations can be developed using density functional and ab initio computational studies focused on the reaction mechanism. Inclusion of explicit solvent molecules in the vital TSs has been proven to be valuable toward improving the energetic estimates of organocatalytic as well as transition-metal-catalyzed organic reactions. Herein, we provide an overview of the importance of an explicit-implicit solvation model using a number of interesting examples.

Ir-Catalyzed Ligand-Free Directed C-H Borylation of Arenes and Pharmaceuticals: Detailed Mechanistic Understanding.

An efficient method for Ir-catalyzed ligand free ortho borylation of arenes (such as, 2-phenoxypyridines, 2-anilinopyridines, benzylamines, benzylpiperazines, benzylmorpholines, benzylpyrrolidine, benzylpiperidines, benzylazepanes, α-amino acid derivatives, aminophenylethane derivatives, and other important scaffolds) and pharmaceuticals has been developed. The reaction underwent via an interesting mechanistic pathway, as revealed by the detailed mechanistic investigations by using kinetic isotope studies and DFT calculations. The catalytic cycle is found to involve the intermediacy of an Ir-boryl complex where the substrate C-H activation is the turnover determining step, intriguingly without any appreciable primary KIE. The method displays a broad range of substrate scope and functional group tolerance. Numerous late-stage borylation of various important molecules and drugs were achieved using this developed strategy. The borylated compounds were further converted into more valuable functionalities. Moreover, utilizing the benefit of the B-N intramolecular interaction of the mono borylated compounds, an operationally simple method has been developed for the selective diborylation of 2-phenoxypyridines and numerous functionalized arenes. Furthermore, the synthetic utility has been showcased with the removal of the pyridyl directing group from the borylated product to achieve ortho borylated phenol along with the ipso-borylation for the preparation of 1,2-diborylated benzene.

Machine learning studies on asymmetric relay Heck reaction-Potential avenues for reaction development.

The integration of machine learning (ML) methods into chemical catalysis is evolving as a new paradigm for cost and time economic reaction development in recent times. Although there have been several successful applications of ML in catalysis, the prediction of enantioselectivity (ee) remains challenging. Herein, we describe a ML workflow to predict ee of an important class of catalytic asymmetric transformation, namely, the relay Heck (RH) reaction. A random forest ML model, built using quantum chemically derived mechanistically relevant physical organic descriptors as features, is found to predict the ee remarkably well with a low root mean square error of 8.0 ± 1.3. Importantly, the model is effective in predicting the unseen variants of an asymmetric RH reaction. Furthermore, we predicted the ee for thousands of unexplored complementary reactions, including those leading to a good number of bioactive frameworks, by engaging different combinations of catalysts and substrates drawn from the original dataset. Our ML model developed on the available examples would be able to assist in exploiting the fuller potential of asymmetric RH reactions through a priori predictions before the actual experimentation, which would thus help surpass the trial and error loop to a larger degree.

Iridium-Catalyzed Ligand-Controlled Remote para-Selective C-H Activation and Borylation of Twisted Aromatic Amides.

A method of para-selective borylation of aromatic amides is described. The borylation proceeded via an unprecedented substrate-ligand distortion between the twisted aromatic amides and a newly designed ligand framework (defa) that is different from the traditionally used ligand (dtbpy) for the C-H borylation reactions. The designed ligand framework (defa) has led to the development of a new type of catalytic system that shows excellent para selectivity for a range of aromatic amides. Moreover, the designed ligand has shown excellent reactivity and selectivity for a range of heterocyclic aromatic amides. The identification of key transition states and intermediates using the DFT computations associated with the three regio-isomeric pathways revealed that the most efficient catalytic pathway with the defa ligand leads to the para borylation while in the case of bpy the borylation at the para and meta sites compete.

Iridium-Catalyzed Regioselective Borylation through C-H Activation and the Origin of Ligand-Dependent Regioselectivity Switching.

Research efforts in catalytic regioselective borylation using C-H bond activation of arenes have gained considerable recent attention. The ligand-enabled regiocontrol, such as in the borylation of benzaldehyde, the selectivity could be switched from the ortho to meta position, under identical conditions, by just changing the external ligand (L) from 8-aminoquinoline (8-AQ) to tetramethylphenanthroline (TMP). The DFT(B3LYP-D3) computations helped us learn that the energetically preferred catalytic pathway includes the formation of an Ir-π-complex between the active catalyst [Ir(L)(Bpin)3] and benzaldimine, a C-H bond oxidative addition (OA) to form an Ir(V)aryl-hydride intermediate, and a reductive elimination to furnish the borylated benzaldehyde as the final product. The lowest energetic span (δEortho = 26 kcal/mol with 8-AQ) is noted in the ortho borylation pathway, with the OA transition state (TS) as the turnover-determining TS. The change in regiochemical preference to the meta borylation (δEmeta = 26) with TMP is identified. A hemilabile mode of 8-AQ participation is found to exhibit a δEortho of 24 kcal/mol for the ortho borylation, relative to that in the chelate mode (δEortho = 26 kcal/mol). The predicted regioselectivity switching is in good agreement with the earlier experimental observations.

On the question of steric repulsion versus noncovalent attractive interactions in chiral phosphoric acid catalyzed asymmetric reactions.

The origin of enantioselectivity in asymmetric catalysis is often built around the differential steric interaction in the enantiocontrolling transition states (TSs). A closer perusal of enantiocontrolling TSs in an increasingly diverse range of reactions has revealed that the cumulative effect of weak noncovalent interactions could even outweigh the steric effects. While enunciating this balance is conspicuously important, quantification of such intramolecular forces within a TS continues to remain scarce and challenging. Herein, we demonstrate the utility of the fragment molecular orbital method in establishing the relative contributions of various attractive and repulsive contributions in the total interaction energy between the suitably chosen fragments in enantiocontrolling TSs. Three types of reactions of high contemporary importance, namely, axially chiral phosphoric acid (CPA) catalyzed kinetic resolution of rac-α-methyl-γ-hydroxy ester (reaction I), asymmetric dearomative amination of ß-naphthols by dimethyl azodicarboxylate (IIa and IIb), and intramolecular desymmetrization of ß,ß-disubstituted methyl oxetanes (IIIa) and hydroxyl oxetane (IIIb), bearing a tethered alcohol (-OCH2CH2OH or -(CH2)2CH2OH), are considered. In all the five reactions, the differences in the stabilizing contributions arising due to electrostatic, charge-transfer, and dispersion interactions between the catalyst and the reacting partners in the enantiocontrolling transition states are weighed against the destabilizing exchange interaction. The balancing interactions are found to be between dispersion and exchange repulsion in reaction I, a combination of charge transfer and dispersion energies offsets the repulsive energy in reaction IIb involving the electron rich anthryl groups in the catalyst, whereas the -(CF3)2C6H4 3,3'-substituent in the catalyst (reaction IIa) leads to a trade-off between dispersion and exchange energies. In reactions IIIa and IIIb, however, electrostatic and dispersion energies help compensate the repulsive interactions. These quantitative insights on the intramolecular interactions in the stereocontrolling TSs could help in the rational design of asymmetric catalysis.

Unraveling the Importance of Noncovalent Interactions in Asymmetric Hydroformylation Reactions.

For catalytic asymmetric hydroformylation (AHF) of alkenes to chiral aldehydes, though a topic of high interest, the contemporary developments remain largely empirical owing to rather limited molecular insights on the origin of enantioselectivity. Given this gap, herein, we present the mechanistic details of Rh-(S,S)-YanPhos-catalyzed AHF of α-methylstyrene, as obtained through a comprehensive DFT (ω-B97XD and M06) study. The challenges with the double axially chiral YanPhos, bearing an N-benzyl BINOL-phosphoramidite and a BINAP-bis(3,5-t-Bu-aryl)phosphine, are addressed through exhaustive conformational sampling. The C-H···π, π···π, and lone pair···π noncovalent interactions (NCIs) between the N-benzyl and the rest of the chiral ligand limit the N-benzyl conformers. Similarly, the C-H···π and π···π NCIs between the chiral catalyst and α-methylstyrene render the si-face binding to the Rh-center more preferred over the re-face. The transition state (TS) for the regiocontrolling migratory insertion, triggered by the Rh-hydride addition to the alkene, to the more substituted α-carbon is 3.6 kcal/mol lower than that to the ß-carbon, thus favoring the linear chiral aldehyde over the achiral branched alternative. In the linear pathway, the TS for the hydride addition to the si-face is 1.5 kcal/mol lower than that to the re-face, with a predicted ee of 85% for the S aldehyde (expt. 87%). The energetic span analysis reveals the reductive elimination as the turnover determining step for the preferred S linear aldehyde. These molecular insights could become valuable for exploiting AHF reactions for substituted alkenes and for eventual industrial implementation.

Insights on Absolute and Relative Stereocontrol in Stereodivergent Cooperative Catalysis.

An increasing number of examples demonstrate that the use of two mutually compatible chiral catalysts in one-pot conditions can help realize the long-cherished goal of simultaneous control of absolute and relative configurations in asymmetric catalysis. Engaging two transition metal catalysts for this goal presents a considerable degree of mechanistic challenge to control the mode of substrate activation as well as origin of enantio- and diastereoselectivities, both of which are central to the burgeoning domain of stereodivergent catalysis. We have employed density functional theory (B3LYP-D3) computations to investigate an important stereodivergent reaction between azaaryl acetamide and cinnamyl methyl carbonate. These compounds participate in the stereocontrolling C-C bond formation in the form of activated substrates, respectively, when bound to chiral Cu-Walphos and Ir-phosphoramidite catalysts. Herein, we provide the molecular origin of how all four stereoisomers of the product bearing two contiguous stereogenic centers could be accessed by changing the combinations of chiral catalysts (C1(R,Rp) or C2(S,Sp) of Cu-Walphos in conjunction with P1(R,R,R) or P2(S,S,S) of Ir-phosphoramidite catalysts). The origin of stereodivergence is identified to depend on the differences in the number and nature of noncovalent interactions (NCIs) in the stereocontrolling transition states. In particular, NCIs between the chiral catalysts (C-H···π in C1-P1 catalyst dyad and C-H···π, C-H···F, and π···π in C2-P1) in stereocontrolling transition states are found to be the differentiating factors rendering one of the four stereochemically distinct transition states to be the lowest energy one for a given catalyst combination. These molecular insights suggest that subtle modifications to the catalyst framework could be further exploited in stereodivergent catalysis.

Pd-Catalyzed γ-C(sp3)-H Fluorination of Free Amines.

The first example of free amine γ-C(sp3)-H fluorination is realized using 2-hydroxynicotinaldehyde as the transient directing group. A wide range of cyclohexyl and linear aliphatic amines could be fluorinated selectively at the γ-methyl and methylene positions. Electron withdrawing 3,5-disubstituted pyridone ligands were identified to facilitate this reaction. Computational studies suggest that the turnover determining step is likely the oxidative addition step for methylene fluorination, while it is likely the C-H activation step for methyl fluorination. The explicit participation of Ag results in a lower energetic span for methylene fluorination and a higher energetic span for methyl fluorination, which is consistent with the experimental observation that the addition of silver salt is desirable for methylene but not for methyl fluorination. Kinetic studies on methyl fluorination suggest that the substrate and PdL are involved in the rate-determining step, indicating that the C-H activation step may be partially rate-determining. Importantly, an energetically preferred pathway has identified an interesting pyridone-assisted bimetallic transition state for the oxidative addition step in methylene fluorination, thus uncovering a potential new role of the pyridone ligand.

Palladium-Catalyzed meta-C-H Allylation of Arenes: A Unique Combination of a Pyrimidine-Based Template and Hexafluoroisopropanol.

Controlling remote selectivity and delivering novel functionalities at distal positions in arenes are an important endeavor in contemporary organic synthesis. In this vein, template engineering and mechanistic understanding of new functionalization strategies are essential for enhancing the scope of such methods. Herein, meta-C-H allylation of arenes has been achieved with the aid of a palladium catalyst, pyrimidine-based auxiliary, and allyl phosphate. 1,1,1,3,3,3-Hexafluoroisopropanol (HFIP) was found as a critical solvent in this transformation. The role of HFIP throughout the catalytic cycle has been systematically studied. A broad substrate scope with phenethyl ether, phenol, benzylsulfonyl ester, phenethylsulfonyl ester, phenylacetic acid, hydrocinnamic acid, and 2-phenylbenzoic acid derivatives has been demonstrated. Interestingly, conformationally flexible arenes have also been selectively allylated at the meta-position using allyl phosphate. A combination of 1H NMR, 31P NMR, ESI-MS, kinetic experiments, and density functional theory (DFT) computations suggested that reaction proceeds through a ligand-assisted meta-C-H activation, allyl addition forming a Pd-π-allyl complex which is then followed by a turnover determining the C-C bond formation step leading to the meta-allylated product.

Harnessing Noncovalent Interactions in Dual-Catalytic Enantioselective Heck-Matsuda Arylation.

The use of more than one catalyst in one-pot reaction conditions has become a rapidly evolving protocol in the development of asymmetric catalysis. The lack of molecular insights on the mechanism and enantioselectivity in dual-catalytic reactions motivated the present study focusing on an important catalytic asymmetric Heck-Matsuda cross-coupling. A comprehensive density functional theory (M06 and B3LYP-D3) investigation of the coupling between a spirocyclic cyclopentene and 4-fluorophenyl diazonium species under a dual-catalytic condition involving Pd2(dba)3 (dba = trans, trans-dibenzylideneacetone) and chiral 2,2'-binaphthyl diamine (BINAM)-derived phosphoric acids (BDPA, 2,2'-binaphthyl diamine-derived phosphoric acids) is presented. Among various mechanistic possibilities examined, the pathway with explicit inclusion of the base (in situ generated sodium bicarbonate/sodium biphosphate) is found to be energetically more preferred over the analogous base-free routes. The chiral phosphate generated by the action of sodium carbonate on BDPA is found to remain associated with the reaction site as a counterion. The initial oxidative addition of Pd(0) to the aryl diazonium bond gives rise to a Pd-aryl intermediate, which then goes through the enantiocontrolling migratory insertion to the cyclic alkene, leading to an arylated cycloalkene intermediate. Insights on how a series of noncovalent interactions, such as C-H···O, C-H···N, C-H···F, C-H···π, lp···π, O-H···π, and C-F···π, in the enantiocontrolling transition state (TS) render the migration of the Pd-aryl to the si prochiral face of the cyclic alkene more preferred over that to the re face are utilized for modulating the enantioselectivity. Aided by molecular insights on the enantiocontrolling transition states, we predicted improved enantioselectivity from 37% to 89% by changes in the N-aryl substituents of the catalyst. Subsequent experiments in our laboratory offered very good agreement with the predicted enantioselectivities.

Cooperativity and serial ligand catalysis in an allylic amination reaction by Pd(ii)-bis-sulfoxide and Brønsted acids.

In recent years, transition metal catalysts have been increasingly employed in conjunction with Brønsted acids under one-pot reaction conditions, opening up newer avenues for dual catalytic protocols. Under such dual catalytic conditions, the general premise of holding the native ligands on the catalyst in the same manner throughout the catalytic cycle becomes immediately questionable. We have invoked the likelihood of Serial Ligand Catalysis in an important intramolecular allylic amination of N-Boc (N-tert-butoxycarbonyl) protected homoallylic amine leading to an anti-oxazolidinone product. The reported reaction conditions employed (bis-sulfoxide)Pd(OAc)2 and dibutyl phosphoric acid (DBPOH) as the catalysts and benzoquinone (BQ) as the oxidant. We used density functional theory computations at the B3LYP-D3 level of theory to examine a comprehensive set of ligand combinations around the Pd center so as to identify the energetically most preferred pathway. The key catalytic events consist of (i) a C-H activation at the allylic position in the catalyst-substrate complex [Pd(L)(L')2(substrate)], leading to a (L)(L')Pd-π-allyl intermediate, and (ii) an intramolecular C-O bond formation between the carbonyl oxygen of the N-Boc amine and the allyl carbon. Interesting cooperativity between the catalysts in both these steps has been found, wherein the Pd(DBPO-)2(BS) species is involved in the C-H activation transition state and Pd(DBPO-)(BQ) in the C-O bond formation step. The energetic advantage in swapping the bis-sulfoxide ligand on Pd with a benzoquinone upon moving from the first step to the second step confirms the significance of serial ligand catalysis in dual catalytic reactions.

Mechanism and Origin of Enantioselectivity in Nickel-Catalyzed Alkyl-Alkyl Suzuki Coupling Reaction.

Enantioselective Suzuki coupling reactions are a widely used method in asymmetric synthesis of chiral compounds. In an important extension of this protocol, 1-bromo-1-fluoroalkanes were coupled with alkyl-9-BBN using chiral NiCl2L* as the catalyst (where L* = bis(pyrrolidine) ligand) under Suzuki conditions to obtain a product with a stereogenic center bearing a fluorine. In view of the current interest in chiral fluorine-containing compounds as well as lack of clarity on the mechanism of Ni-catalyzed asymmetric Suzuki coupling reactions, we decided to examine various mechanistic pathways of the title reaction. The (U)M06 density functional theory computations have been employed to identify the energetically preferred pathway first and then to probe the origin of high enantioselectivity. In particular, we have compared the likely involvement of different redox couples such as Ni(0)/Ni(II) and Ni(I)/Ni(III) in the catalytic cycle. For the Ni(0)/Ni(II) pathway, both singlet and triplet spin states have been considered whereas a doublet spin multiplicity has been examined in the case of the Ni(I)/Ni(III) system. The most preferred catalytic pathway is found to proceed through a Ni(I)/Ni(III) redox cycle with key mechanistic steps such as (a) a transmetalation involving the transfer of the alkyl group of 9-BBN to the Ni-catalyst, (b) an oxidative addition of bromo(fluoro) alkane to give a penta-coordinate Ni(III) intermediate, and (c) an enantio-controlling reductive elimination (RE) that facilitates the C-C bond formation between the Ni-bound fluoroalkyl and alkyl moieties to yield the final product. The transmetalation is found to be the turnover determining transition state (TS) according to the activation span model. The RE is found to be the enantio-controlling step, wherein the TS for the addition of the si prochiral face of the Ni-bound fluoro alkyl moiety to the alkyl group is 4.3 kcal/mol lower than the corresponding re face addition. Distortion-Interaction analysis suggested that the extent of distortion in the catalyst Ni(Br)L* fragment in the si face reductive elimination TS is much lower than in the re face addition, thus making a vital contribution to the energy difference between diastereomeric TS.

Rhodium Catalyzed Asymmetric Hydroamination of Internal Alkynes with Indoline: Mechanism, Origin of Enantioselectivity, and Role of Additives.

A comprehensive mechanistic study on the title reaction by using DFT(B3LYP-D3) computational method is reported. Explicit consideration of mono- (m-xylylic) and dicarboxylic acid (phthalic) in the key transition states reveals active participation of the carboxylic acid, beginning with the generation of a monomeric Rh(I) active catalyst and in the ensuing catalytic steps. In the early catalytic event, uptake of alkyne is predicted to take place only after the oxidative addition of the Rh(I) active catalyst to the carboxylic acid. The hydrometalation of the alkyne bound to the Rh(III)-H intermediate then generates a Rh(III)-vinyl intermediate, which in turn converts to a Rh(III)-allyl species. The inclusion of m-xylylic acid results in a two-step pathway to Rh(III)-allyl species via Rh-allene intermediate. A number of weak noncovalent interactions (hydrogen bonding and C-H···π) between the catalyst and the substrates and that involving m-xylylic acid are found to have a direct impact on the regiochemical preference toward the branched product and the enantiocontrolling hydroamination step involving C-N bond formation leading to the major enantiomer (S-allylic amine). The chiral induction is enabled by cumulative effect of noncovalent interactions, which is an insight that could aid future developments of chiral ligands for asymmetric hydroamination.