Computational ligand design in enantio- and diastereoselective ynamide [5+2] cycloisomerization

Data-driven discovery of active phosphine ligand space for cross-coupling reactions

The design of highly active catalysts is a main theme in organic chemistry, but it still relies heavily on expert experience. Herein, powered by machine-learning global structure exploration, we forge a Metal-Phosphine Catalyst Database (MPCD) with a meticulously designed ligand replacement energy metric, a key descriptor to describe the metal-ligand interactions. It pushes the rational design of organometallic catalysts to a quantitative era, where a ±10 kJ mol-1 window of relative ligand binding strength, a so-called active ligand space (ALS), is identified for highly effective catalyst screening. We highlight the chemistry interpretability and effectiveness of ALS for various C-N, C-C and C-S cross-coupling reactions via a Sabatier-principle-based volcano plot and demonstrate its predictive power in discovering low-cost ligands in catalyzing Suzuki cross-coupling involving aryl chloride. The advent of the MPCD provides a data-driven new route for speeding up organometallic catalysis and other applications.

Ir/Zn-cocatalyzed chemo- and atroposelective [2+2+2] cycloaddition for construction of C─N axially chiral indoles and pyrroles

Here, an Ir/Zn-cocatalyzed atroposelective [2+2+2] cycloaddition of 1,6-diynes and ynamines was developed, forging various functionalized C─N axially chiral indoles and pyrroles in generally good to excellent yields (up to 99%), excellent chemoselectivities, and high enantioselectivities (up to 98% enantiomeric excess) with wide substrate scope. This cocatalyzed strategy not only provided an alternative promising and reliable way for asymmetric alkyne [2+2+2] cyclotrimerization in an easy handle but also settled the issues of previous [Rh(COD)2]BF4-catalyzed system on the construction of C─N axial chirality such as complex operations, limited substrate scope, and low efficiency. In addition, control experiments and theoretical calculations disclosed that Zn(OTf)2 markedly reduced the barrier of migration insertion to significantly increase reaction efficiency, which was distinctly different from previous work on the Lewis acid for improving reaction yield through accelerating oxidative addition and reductive elimination.

Regioselective and Enantioselective Copper-Catalyzed Hydroaminocarbonylation of Unactivated Alkenes and Alkynes

Given the prevalence of amide backbones in marketed pharmaceuticals and their ubiquity as critical binding units in natural peptides and proteins, it remains important to develop novel methods to construct amide bonds. We report here a general method for the anti-Markovnikov hydroaminocarbonylation of unactivated alkenes under mild conditions, using copper catalysis in combination with hydroxylamine electrophile reagents and poly(methylhydrosiloxane) (PMHS) as a cheap and environmentally friendly hydride source. The reaction tolerates a variety of functional groups and efficiently converts unactivated terminal alkenes, 1,1-disubstituted alkenes, and cyclic alkenes to the corresponding amides with exclusive anti-Markovnikov selectivity (and high enantioselectivities/diastereoselectivities). Additionally, with minimal modification of the reaction conditions, alkynes can also undergo tandem hydrogenation-hydroaminocarbonylation to alkyl amides.

Reproducibility of density functional approximations: How new functionals should be reported

Density functional theory is the workhorse of chemistry and materials science, and novel density functional approximations are published every year. To become available in program packages, the novel density functional approximations (DFAs) need to be (re)implemented. However, according to our experience as developers of Libxc [Lehtola et al., SoftwareX 7, 1 (2018)], a constant problem in this task is verification due to the lack of reliable reference data. As we discuss in this work, this lack has led to several non-equivalent implementations of functionals such as Becke-Perdew 1986, Perdew-Wang 1991, Perdew-Burke-Ernzerhof, and Becke's three-parameter hybrid functional with Lee-Yang-Parr correlation across various program packages, yielding different total energies. Through careful verification, we have also found many issues with incorrect functional forms in recent DFAs. The goal of this work is to ensure the reproducibility of DFAs. DFAs must be verifiable in order to prevent the reappearance of the above-mentioned errors and incompatibilities. A common framework for verification and testing is, therefore, needed. We suggest several ways in which reference energies can be produced with free and open source software, either with non-self-consistent calculations with tabulated atomic densities or via self-consistent calculations with various program packages. The employed numerical parameters-especially the quadrature grid-need to be converged to guarantee a ≲0.1 μEh precision in the total energy, which is nowadays routinely achievable in fully numerical calculations. Moreover, as such sub-μEh level agreement can only be achieved when fully equivalent implementations of the DFA are used, the source code of the reference implementation should also be made available in any publication describing a new DFA.

Sequencing palladium-catalyzed cycloisomerization cascades in a synthesis of the gelsemine core

Transition metal-catalyzed cycloisomerization is a powerful strategy for the construction of cyclic organic molecules, and the use of palladium catalysts can deliver a wide range of monocyclic and bicyclic products. However, applications of cycloisomerizations in complex target synthesis in which more than one cycloisomerization process is deployed in a cascade context are rare. Here we report investigations of the relative rates of two different types of ene-ynamide cycloisomerization that form fused and spirocyclic rings, and use of these results to design a sequence-controlled cascade cycloisomerization that prepares the tetracyclic core of gelsemine in a single step. Crucial to this work was an evaluation of the kinetics of each cycloisomerization in competition experiments, which revealed a key influence of the ynamide electron-withdrawing group on the cycloisomerization reaction.

Computational molecular refinement to enhance enantioselectivity by reinforcing hydrogen bonding interactions in major reaction pathway

Computational analyses have revealed that the distortion of a catalyst and the substrates and their interactions are key to determining the stability of the transition state. Hence, two strategies "distortion strategy" and "interaction strategy" can be proposed for improving enantiomeric excess in enantioselective reactions. The "distortion strategy" is used as a conventional approach that destabilizes the TS (transition state) of the minor pathway. On the other hand, the "interaction strategy" focuses on the stabilization of the TS of the major pathway in which an enhancement of the reaction rate is expected. To realize this strategy, we envisioned the TS stabilization of the major reaction pathway by reinforcing hydrogen bonding and adopted the chiral phosphoric acid-catalysed enantioselective Diels-Alder reaction of 2-vinylquinolines with dienylcarbamates. The intended "interaction strategy" led to remarkable improvements in the enantioselectivity and reaction rate.

Double isomerization/cycloisomerization/aromatization of 1-(allyloxy)-2-(cyclopropylmethyl)benzenes to give 2-ethyl-3-isopropylbenzofurans using a multitasking single rhodium catalyst

Multitasking single-catalyst systems that allow multiple chemical transformations within a single reaction vessel are important for the development of eco-compatible chemistry. Here, we have developed a rhodium-catalyzed system that transforms 1-(allyloxy)-2-(cyclopropylmethyl)benzene derivatives to 2-ethyl-3-isopropylbenzofurans via double isomerization/cycloisomerization/aromatization.

Noncovalent CH-π and π-π Interactions in Phosphoramidite Palladium(II) Complexes with Strong Conformational Preference

The weak noncovalent interactions and flexibility of ligands play a key role in enantioselective metal-catalyzed reactions. In transition metal complexes and their catalytic applications, the experimental assessment and the design of key interactions is as difficult as the prediction of the enantioselectivities, especially for flexible, privileged ligands such as chiral phosphoramidites. Therefore, the interligand interactions in cis-PdII L2 Cl2 phosphoramidite complexes were investigated by NMR spectroscopy and computations. We were able to induce a strong conformational preference by breaking the symmetry of the C2 -symmetric side chain of one of the ligands, and shift the equilibrium between hetero- and homocomplexes towards heterocomplexes because of interligand interactions in the cis-complexes. The modulation of aryl substituents was exploited, along with the solvent effect. The combined CH-π and π-π interactions reveal design patterns for binding and folding of chiral ligands and catalysts.

Carboxylation of a Palladacycle Formed via C(sp3 )-H Activation: Theory-Driven Reaction Design

Theory-driven organic synthesis is a powerful tool for developing new organic transformations. A palladacycle(II), generated from 8-methylquinoline via C(sp³ )-H activation, is frequently featured in the scientific literature, albeit that the reactivity toward CO₂ , an abundant, inexpensive, and non-toxic chemical, remains elusive. We have theoretically discovered potential carboxylation pathways using the artificial force induced reaction (AFIR) method, a density-functional-theory (DFT)-based automated reaction path search method. The thus obtained results suggest that the reduction of Pd(II) to Pd(I) is key to promote the insertion of CO₂ . Based on these computational findings, we employed various one-electron reductants, such as Cp*₂ Co, a photoredox catalyst under blue LED irradiation, and reductive electrolysis ((+)Mg/(-)Pt), which afforded the desired carboxylated products in high yields. After screening phosphine ligands under photoredox conditions, we discovered that bidentate ligands such as dppe promoted this carboxylation efficiently, which was rationally interpreted in terms of the redox potential of the Pd(II)-dppe complex as well as on the grounds of DFT calculations. We are convinced that these results could serve as future guidelines for the development of Pd(II)-catalyzed C(sp³ )-H carboxylation reactions with CO₂ .

Synthesis of Polysubstituted Fused Pyrroles by Gold-Catalyzed Cycloisomerization/1,2-Sulfonyl Migration of Yndiamides

Yndiamides (bis-N-substituted alkynes) are valuable precursors to azacycles. Here we report a cycloisomerization/1,2-sulfonyl migration of alkynyl-yndiamides to form tetrahydropyrrolopyrroles, unprecedented heterocyclic scaffolds that are relevant to medicinal chemistry. This functional group tolerant transformation can be achieved using Au(I) catalysis that proceeds at ambient temperature, and a thermally promoted process. The utility of the products is demonstrated by a range of reactions to functionalize the fused pyrrole core.

Trends in computational molecular catalyst design

Computational methods have emerged as a powerful tool to augment traditional experimental molecular catalyst design by providing useful predictions of catalyst performance and decreasing the time needed for catalyst screening. In this perspective, we discuss three approaches for computational molecular catalyst design: (i) the reaction mechanism-based approach that calculates all relevant elementary steps, finds the rate and selectivity determining steps, and ultimately makes predictions on catalyst performance based on kinetic analysis, (ii) the descriptor-based approach where physical/chemical considerations are used to find molecular properties as predictors of catalyst performance, and (iii) the data-driven approach where statistical analysis as well as machine learning (ML) methods are used to obtain relationships between available data/features and catalyst performance. Following an introduction to these approaches, we cover their strengths and weaknesses and highlight some recent key applications. Furthermore, we present an outlook on how the currently applied approaches may evolve in the near future by addressing how recent developments in building automated computational workflows and implementing advanced ML models hold promise for reducing human workload, eliminating human bias, and speeding up computational catalyst design at the same time. Finally, we provide our viewpoint on how some of the challenges associated with the up-and-coming approaches driven by automation and ML may be resolved.

Understanding the mechanism of the chiral phosphoric acid-catalyzed aza-Cope rearrangement

The first catalytic enantioselective aza-Cope rearrangement was reported in 2008 by Rueping et al. The reaction is catalyzed by a 1,1'-bi-2-naphthol-derived (BINOL-derived) phosphoric acid and achieved high yields and enantioselectivities (up to 97 : 3 er with 75% yield). This work utilizes Density Functional Theory to understand the mechanism of the reaction and explain the origins of the enantioselectivity. An extensive conformational search was carried out to explore the different activation modes by the catalyst and, the Transition State (TS) leading to the major product was found to be 1.3 kcal mol-1 lower in energy than the TS leading to the minor product. The origin of this stabilization was rationalized with NBO and NCI analysis: it was found that the major TS has a greater number of non-bonding interactions between the substrate and the catalyst, and shows stronger H-bond interactions between H atoms in the substrate and the O atoms in the phosphate group of the catalyst.

Electro-Descriptors for the Performance Prediction of Electro-Organic Synthesis

Electrochemical organic synthesis has attracted increasing attentions as a sustainable and versatile synthetic platform. Quantitative assessment of the electro-organic reactions, including reaction thermodynamics, electro-kinetics, and coupled chemical processes, can lead to effective analytical tool to guide their future design. Herein, we demonstrate that electrochemical parameters such as onset potential, Tafel slope, and effective voltage can be utilized as electro-descriptors for the evaluation of reaction conditions and prediction of reactivities (yields). An "electro-descriptor-diagram" is generated, where reactive and non-reactive conditions/substances show distinct boundary. Successful predictions of reaction outcomes have been demonstrated using electro-descriptor diagram, or from machine learning algorithms with experimentally-derived electro-descriptors. This method represents a promising tool for data-acquisition, reaction prediction, mechanistic investigation, and high-throughput screening for general organic electro-synthesis.

John PC, Kim S, Paton RS. Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Machine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken before model selection, and the development of new ways to quantitatively encode molecules is an active area of research. In this Account, we highlight the application and suitability of different representations, from expert-guided "engineered" descriptors to automatically "learned" features, in different prediction tasks relevant to organic and organometallic chemistry, where differing amounts of training data are available. These tasks include statistical models of stereo- and enantioselectivity, thermochemistry, and kinetics developed using experimental and quantum chemical data.The use of expert-guided molecular descriptors provides an opportunity to incorporate chemical knowledge, domain expertise, and physical constraints into statistical modeling. In applications to stereoselective organic and organometallic catalysis, where data sets may be relatively small and 3D-geometries and conformations play an important role, mechanistically informed features can be used successfully to obtain predictive statistical models that are also chemically interpretable. We provide an overview of several recent applications of this approach to obtain quantitative models for reactivity and selectivity, where topological descriptors, quantum mechanical calculations of electronic and steric properties, along with conformational ensembles, all feature as essential ingredients of the molecular representations used.Alternatively, more flexible, general-purpose molecular representations such as attributed molecular graphs can be used with machine learning approaches to learn the complex relationship between a structure and prediction target. This approach has the potential to out-perform more traditional representation methods such as "hand-crafted" molecular descriptors, particularly as data set sizes grow. One area where this is particularly relevant is in the use of large sets of quantum mechanical data to train quantitative structure-property relationships. A general approach toward curating useful data sets and training highly accurate graph neural network models is discussed in the context of organic bond dissociation enthalpies, where this strategy outperforms regression using precomputed descriptors.Finally, we describe how graph neural network predictions can be incorporated into mechanistically informed statistical models of chemical reactivity and selectivity. Once trained, this approach avoids the expensive computational overhead associated with quantum mechanical calculations, while maintaining chemical interpretability. We illustrate examples for which fast predictions of bond dissociation enthalpy and of the identities of radicals formed through cleavage of a molecule's weakest bond are used in simple physical models of site-selectivity and reactivity.

Transition Metal-Catalyzed Selective Carbon-Carbon Bond Cleavage of Vinylcyclopropanes in Cycloaddition Reactions

In this review, transition metal-catalyzed methodologies and applications that exploit C-C bond cleavage of vinylcyclopropanes (VCPs) are summarized with a focus on cycloaddition and related addition reactions. Transition metals, including palladium, nickel, iron, ruthenium, rhodium, cobalt, and iridium, can catalyze the cleavage of C-C bonds in activated or nonactivated VCPs. Additionally, these bond-breaking reactions can occur as intra- or intermolecular processes. The properties of activated and nonactivated VCPs are discussed in the Introduction. Various transition metal-catalyzed cycloaddition and addition reactions involving the cleavage of C-C bonds in activated VCPs are then discussed in the next chapter. The transition metal-catalyzed cycloadditions involving the cleavage of C-C in nonactivated VCPs are summarized in the following chapter. Finally, challenges and potential opportunities are outlined in the last chapter.

Cycloaddition of cyclopropanes for the elaboration of medium-sized carbocycles

The stereocontrolled formation of medium-sized carbocycles is a major goal in modern organic chemistry due to their widespread occurrence in natural products and pharmaceutically active ingredients. One approach consists in the use of cycloaddition reactions which notably results in high selectivities and atom-economy. To this end, cyclopropanes are ideal substrates since they can provide readily functionalized three- or five-carbon synthons. Herein we report advances made in cycloaddition reactions of cyclopropanes towards the synthesis of medium-sized carbocycles via transition metal catalysis or Lewis acid catalysis.

Regio- and enantioselective ring-opening reaction of vinylcyclopropanes with indoles under cooperative catalysis

The title reaction has been established under the cooperative bimetallic catalysis of iridium and copper catalysts, which afforded indole C3-allylation products with branched selectivity in moderate yields and good enantioselectivities.

Silver-catalyzed desulfurizative annulation of 1,2-benzisothiazoles with ynamides to construct multi-substituted isoquinolines

An unprecedented silver-catalyzed desulfurizative annulation of 1,2-benzisothiazoles with ynamides to access multi-substituted isoquinoline derivatives is disclosed.

Photoredox-catalyzed chemoselective aerobic Cα–H oxidation of propargylamines: synthesis of substituted 2-ynamide and oxazolo[2,3-a]isoquinolinone derivatives

Visible light-initiated chemoselective aerobic Cα–H oxidation of propargylamines.

Asymmetric synthesis with ynamides: unique reaction control, chemical diversity and applications

Ynamides are among the most powerful building blocks in organic synthesis and have become invaluable starting materials for the construction of multifunctional compounds and challenging architectures that would be difficult to prepare otherwise. The rapidly growing popularity originates from the unique reactivity and ease of manipulation of the polarized ynamide triple bond, the advance of practical methods for making them, and the simplicity of storage and handling. These attractive features and the demonstration of numerous synthetic applications have spurred the development of intriguing asymmetric reaction strategies during the last decade. An impressive variety of chemo-, regio- and stereoselective carbon-carbon and carbon-heteroatom bond forming reactions with ynamides have been developed and now significantly enrich the toolbox of synthetic chemists. This review provides a comprehensive overview of asymmetric ynamide chemistry since 2010 with a focus on the general scope, current limitations, stereochemical reaction control and mechanistic aspects.

Generating transition states of isomerization reactions with deep learning

Lack of quality data and difficulty generating these data hinder quantitative understanding of reaction kinetics. Specifically, conventional methods to generate transition state structures are deficient in speed, accuracy, or scope. We describe a novel method to generate three-dimensional transition state structures for isomerization reactions using reactant and product geometries. Our approach relies on a graph neural network to predict the transition state distance matrix and a least squares optimization to reconstruct the coordinates based on which entries of the distance matrix the model perceives to be important. We feed the structures generated by our algorithm through a rigorous quantum mechanics workflow to ensure the predicted transition state corresponds to the ground truth reactant and product. In both generating viable geometries and predicting accurate transition states, our method achieves excellent results. We envision workflows like this, which combine neural networks and quantum chemistry calculations, will become the preferred methods for computing chemical reactions.

Open access in silico tools to predict the ADMET profiling of drug candidates

INTRODUCTION

We are in an era of bioinformatics and cheminformatics where we can predict data in the fields of medicine, the environment, engineering and public health. Approaches with open access in silico tools have revolutionized disease management due to early prediction of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles of the chemically designed and eco-friendly next-generation drugs.

AREAS COVERED

This review meticulously encompasses the fundamental functions of open access in silico prediction tools (webservers and standalone software) and advocates their use in drug discovery research for the safety and reliability of any candidate-drug. This review also aims to help support new researchers in the field of drug design.

EXPERT OPINION

The choice of in silico tools is critically important for drug discovery and the accuracy of ADMET prediction. The accuracy largely depends on the types of dataset, the algorithm used, the quality of the model, the available endpoints for prediction, and user requirement. The key is to use multiple in silico tools for predictions and comparing the results, followed by the identification of the most probable prediction.

Organocatalytic Enantioselective Conia-Ene-Type Carbocyclization of Ynamide Cyclohexanones: Regiodivergent Synthesis of Morphans and Normorphans

Described herein is an organocatalytic enantioselective desymmetrizing cycloisomerization of arylsulfonyl-protected ynamide cyclohexanones, representing the first metal-free asymmetric Conia-ene-type carbocyclization. This method allows the highly efficient and atom-economical construction of a range of valuable morphans with wide substrate scope and excellent enantioselectivity (up to 97 % ee). In addition, such a cycloisomerization of alkylsulfonyl-protected ynamide cyclohexanones can lead to the divergent synthesis of normorphans as the main products with high enantioselectivity (up to 90 % ee). Moreover, theoretical calculations are employed to elucidate the origins of regioselectivity and enantioselectivity.

Mechanistic Insights into the Ru(II)-Catalyzed Intramolecular Formal [3 + 2] Cycloaddition of (E)-1,6-Enynes

Design of a unique reaction pathway in transition-metal-catalyzed 1,6-enynes cyclization to construct valuable synthetic motifs is a significant challenge in organic chemistry. Herein, we report a Ru(II)-catalyzed formal [3 + 2] cycloaddition as an efficient method to prepare unprecedented bicyclo[3.3.0]octenes from readily available (E)-1,6-enynes. Mechanistic studies based on the deuterium labeling experiments and the DFT calculation disclose a reasonable mechanistic pathway, where a ruthenacyclopentene generated by an ene-yne oxidative cyclization undergoes a sequential ß-hydride elimination and intramolecular hydroruthenation to form a ruthenacyclohexene, producing the desirable bicyclo[3.3.0]octenes.

Retooling Asymmetric Conjugate Additions for Sterically Demanding Substrates with an Iterative Data-Driven Approach

The development of catalytic enantioselective methods is routinely carried out using easily accessible and prototypical substrates. This approach to reaction development often yields asymmetric methods that perform poorly using substrates that are sterically or electronically dissimilar to those used during the reaction optimization campaign. Consequently, expanding the scope of previously optimized catalytic asymmetric reactions to include more challenging substrates is decidedly nontrivial. Here, we address this challenge through the development of a systematic workflow to broaden the applicability and reliability of asymmetric conjugate additions to substrates conventionally regarded as sterically and electronically demanding. The copper-catalyzed asymmetric conjugate addition of alkylzirconium nucleophiles to form tertiary centers, although successful for linear alkyl chains, fails for more sterically demanding linear α,β-unsaturated ketones. Key to adapting this method to obtain high enantioselectivity was the synthesis of modified phosphoramidite ligands, designed using quantitative structure–selectivity relationships (QSSRs). Iterative rounds of model construction and ligand synthesis were executed in parallel to evaluate the performance of 20 chiral ligands. The copper-catalyzed asymmetric addition is now more broadly applicable, even tolerating linear enones bearing tert-butyl β-substituents. The presence of common functional groups is tolerated in both nucleophiles and electrophiles, giving up to 99% yield and 95% ee across 20 examples.

The importance of synthetic chemistry in the pharmaceutical industry

Innovations in synthetic chemistry have enabled the discovery of many breakthrough therapies that have improved human health over the past century. In the face of increasing challenges in the pharmaceutical sector, continued innovation in chemistry is required to drive the discovery of the next wave of medicines. Novel synthetic methods not only unlock access to previously unattainable chemical matter, but also inspire new concepts as to how we design and build chemical matter. We identify some of the most important recent advances in synthetic chemistry as well as opportunities at the interface with partner disciplines that are poised to transform the practice of drug discovery and development.

A Facile Enantioselective Alkynylation of Chromones

The first catalytic enantioselective alkynylation of chromones is reported. In this process, chromones are silylated to form silyloxybenzopyrylium ions that lead to silyl enol ethers after Cu-catalyzed alkyne addition using StackPhos as a ligand. The outcome of the reaction is impacted by distal ligand substituents with differing electronic character and it was found that successful reactions could be achieved with different ligand congeners by using different solvents. This sequence enables access to different products by protonation or further functionalization, thus increasing complexity in a divergent manner. The transformation is high yielding over a broad scope to provide a variety of useful chromanones in high enantioselectivity.

Mechanistically Guided Predictive Models for Ligand and Initiator Effects in Copper-Catalyzed Atom Transfer Radical Polymerization (Cu-ATRP)

Copper-catalyzed atom transfer radical polymerization (Cu-ATRP) is one of the most widely used controlled radical polymerization techniques. Notwithstanding the extensive mechanistic studies in the literature, the transition states of the activation/deactivation of the growing polymer chain, a key equilibrium in Cu-ATRP, have not been investigated computationally. Therefore, the understanding of the origin of ligand and initiator effects on the rates of activation/deactivation is still limited. Here, we present the first computational analysis of Cu-ATRP activation transition states to reveal factors that affect the rates of activation and deactivation. The Br atom transfer between the polymer chain and the Cu catalyst occurs through an unusual bent geometry that involves pronounced interactions between the polymer chain end and the ancillary ligand on the Cu catalyst. Therefore, the rates of activation/deactivation are determined by both the electronic properties of the Cu catalyst and the ligand-initiator steric repulsions. In addition, our calculations revealed the important role of ligand backbone flexibility on the activation. These theoretical analyses led to the identification of three chemically meaningful descriptors, namely HOMO energy of the catalyst ( EHOMO), percent buried volume ( Vbur%), and distortion energy of the catalyst (Δ Edist), to describe the electronic, steric, and flexibility effects on reactivity, respectively. A robust and simple predictive model for ligand effect on reactivity is thereby established by correlating these three descriptors with experimental activation rate constants using multivariate linear regression. Validation using a structurally diverse set of ligands revealed the average error is less than ±2 kcal/mol compared to the experimentally derived activation energies. The same approach was also applied to develop a predictive model for reactivity of different alkyl halide initiators using R-X bond dissociation energy (BDE) and Cu-X halogenophilicity as descriptors.

Theoretical Study of the Addition of Cu-Carbenes to Acetylenes to Form Chiral Allenes

Terminal alkynes have become one of the most versatile building blocks for C-C bond construction in the past few decades, and they are usually considered to convert to acetylides before further transformations. In this study, a novel direct nucleophilic addition mode for Cu(I)-catalyzed cross-coupling of terminal alkynes and N-tosylhydrazones to synthesize chiral allenes is proposed, and it was investigated by density functional theory with the M11-L density functional. Three different reaction pathways were considered and investigated. The computational results show that the proposed reaction pathway, which includes direct nucleophilic attack of protonated acetylene, deprotonation of the vinyl cation, and catalyst regeneration, is the most favorable pathway. Another possible deprotonation-carbenation-insertion pathway is shown to be unfavorable. The direct nucleophilic addition step is the rate- and enantioselectivity-determining step in the catalytic cycle. Noncovalent interaction analysis shows that the steric effect between the methyl group of the carbene moiety and the naphthalyl group of the bisoxazoline ligand is important to control the enantioselectivity. In addition, calculation of a series of chiral bisoxazoline ligands shows that a bulky group on the oxazoline ring is favorable for high enantioselectivity, which agrees with experimental observations. Moreover, copper acetylides are stable, and their generation is a favorable pathway in the absence of chiral bisoxazoline ligands.