Mechanism and reactivity in the Morita-Baylis-Hillman reaction: the challenge of accurate computations

Hybrid Cluster-Continuum Method for Single-Ion Solvation Free Energy in Acetonitrile Solvent

A new hybrid discrete-continuum approach named the cluster-continuum static approximation (CCSA) has been proposed for acetonitrile solvent. The continuum part uses the conductor-like polarizable continuum model for electrostatic and a surface area-dependent term for nonelectrostatic solvation. The CCSA includes only one explicit acetonitrile solvent molecule and a damping function, which makes the CCSA method reduce to pure continuum solvation in the case of weaker potential of mean force for solute-solvent interaction. The performance of the model was tested for 22 anions and 22 cations, including challenge species that cannot be adequately described by pure continuum solvation. A comparison was done with the widely used solvent model density (SMD) model. For anions, the CCSA reduces to pure continuum solvation and the method has the same performance as the SMD model, with a standard deviation of the mean signed error (SD-MSE) of 2.7 kcal mol-1 for both models. However, the CCSA method for cations considerably outperforms the SMD model, with an SD-MSE of 3.3 kcal mol-1 for the former and 8.4 kcal mol-1 for the latter. The method can be automated, and the present study suggests that continuum solvation models could be parameterized taking into account the explicit solvation as proposed in this work.

Thermal Truncation of Heptamethine Cyanine Dyes

Cyanine dyes are a class of organic, usually cationic molecules containing two nitrogen centers linked through conjugated polymethine chains. The synthesis and reactivity of cyanine derivatives have been extensively investigated for decades. Unlike the recently described phototruncation process, the thermal truncation (chain shortening) reaction is a phenomenon that has rarely been reported for these important fluorophores. Here, we present a systematic investigation of the truncation of heptamethine cyanines (Cy7) to pentamethine (Cy5) and trimethine (Cy3) cyanines via homogeneous, acid-base-catalyzed nucleophilic exchange reactions. We demonstrate how different substituents at the C3' and C4' positions of the chain and different heterocyclic end groups, the presence of bases, nucleophiles, and oxygen, solvent properties, and temperature affect the truncation process. The mechanism of chain shortening, studied by various analytical and spectroscopic techniques, was verified by extensive ab initio calculation, implying the necessity to model catalytic reactions by highly correlated wave function-based methods. In this study, we provide critical insight into the reactivity of cyanine polyene chains and elucidate the truncation mechanism and methods to mitigate side processes that can occur during the synthesis of cyanine derivatives. In addition, we offer alternative routes to the preparation of symmetrical and unsymmetrical meso-substituted Cy5 derivatives.

Competing Reaction Mechanisms of Peptide Bond Formation in Water Revealed by Deep Potential Molecular Dynamics and Path Sampling

The formation of an amide bond is an essential step in the synthesis of materials and drugs, and in the assembly of amino acids to form peptides. The mechanism of this reaction has been studied extensively, in particular to understand how it can be catalyzed, but a representation capable of explaining all the experimental data is still lacking. Numerical simulation should provide the necessary molecular description, but the solvent involvement poses a number of challenges. Here, we combine the efficiency and accuracy of neural network potential-based reactive molecular dynamics with the extensive and unbiased exploration of reaction pathways provided by transition path sampling. Using microsecond-scale simulations at the density functional theory level, we show that this method reveals the presence of two competing distinct mechanisms for peptide bond formation between alanine esters in aqueous solution. We describe how both reaction pathways, via a general base catalysis mechanism and via direct cleavage of the tetrahedral intermediate respectively, change with pH. This result contrasts with the conventional mechanism involving a single pathway in which only the barrier heights are affected by pH. We show that this new proposal involving two competing mechanisms is consistent with the experimental data, and we discuss the implications for peptide bond formation under prebiotic conditions and in the ribosome. Our work shows that integrating deep potential molecular dynamics with path sampling provides a powerful approach for exploring complex chemical mechanisms.

Role of Explicit Solvation in Computational Modeling of Chemical Reactions: Mechanism of Cu(I) Transfer Between Thiolate-Based Chelators in Water

Solvation plays important roles in controlling the thermodynamic and kinetic aspects of chemical reactions. The conventional approaches to treat solvation via electronic structure methods are likely to become inadequate, when the reacting solutes have strong electrostatic and hydrogen bonding interactions with the solvent and undergo significant structural changes during the course of the reaction. In this article, we present evidence of such solvent and structural effects in the computational study of the Cu(I) transfer reaction between thiolate-based chelators dithiobutylamine (DTBA) and dithiotheritol (DTT) in water, inspired from biological copper trafficking phenomena. We propose a general solution to the problem by combining classical molecular dynamics (MD) simulations of the bulk system and static quantum chemistry calculations. The fluctuating solvation shell was estimated from MD, and energetics was assessed by averaging QM energies of a series of molecular clusters constructed from the MD snapshots. Applying this approach, we propose a reaction pathway with estimates of relative intermediate stabilities and barriers, which suggest the overall reaction to be reversible in nature and likely to go through both two and three coordinated intermediates, confirming previous studies of similar protein analogues. An interesting fact that emerged from our study was the strong indication that the rate-determining step is the deprotonation of initial thiol bound Cu(I) complex, without involving any Cu(I)-S bonds. The proposed method will lead to a better treatment of solvations, and these mechanistic insights will aid our understanding of biological copper(I) trafficking.

Toward De Novo Catalyst Discovery: Fast Identification of New Catalyst Candidates for Alcohol-Mediated Morita-Baylis-Hillman Reactions

Recently we have demonstrated how a genetic algorithm (GA) starting from random tertiary amines can be used to discover a new and efficient catalyst for the alcohol-mediated Morita-Baylis-Hillman (MBH) reaction. In particular, the discovered catalyst was shown experimentally to be eight times more active than DABCO, commonly used to catalyze the MBH reaction. This represents a breakthrough in using generative models for catalyst optimization. However, the GA procedure, and hence discovery, relied on two important pieces of information; 1) the knowledge that tertiary amines catalyze the reaction and 2) the mechanism and reaction profile for the catalyzed reaction, in particular the transition state structure of the rate-determining step. Thus, truly de novo catalyst discovery must include these steps. Here we present such a method for discovering catalyst candidates for a specific reaction while simultaneously proposing a mechanism for the catalyzed reaction. We show that tertiary amines and phosphines are potential catalysts for the MBH reaction by screening 11 molecular templates representing common functional groups. The method relies on an automated reaction discovery workflow using meta-dynamics calculations. Combining this method for catalyst candidate discovery with our GA-based catalyst optimization method results in an algorithm for truly de novo catalyst discovery.

Acyl Transfer-Driven Rauhut-Currier Dimerization of Morita-Baylis-Hillman Ketones

A serendipitous Rauhut-Currier dimerization of 1,1-disubstituted activated olefins derived from Morita-Baylis-Hillman adducts was observed in the presence of DABCO. The reaction is driven by the migration of an acyl group and produces multifunctionalized enol esters in yields greater than 90% in most cases, without necessitating column chromatographic purification. The acyl transfer is thought to proceed via a transition state typical of a Morita-Baylis-Hillman (MBH) reaction, supported by a brief mechanistic study involving computational calculations.

Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis-Challenges and Opportunities

Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components to calculate or predict catalysis-performance metrics, such as turnover frequency and measurement of stereoselectivity, via computational chemistry. The state-of-the-art tools available to calculate potential energy and, consequently, free energy, together with their caveats, will be discussed via examples from the literature. Through various examples from organocatalysis and phase transfer catalysis, we will highlight the challenges related to the mechanism, transition state theory, and solvation involved in translating calculated barriers to the turnover frequency or a metric of stereoselectivity. Examples in the literature that validated their theoretical models will be showcased. Lastly, the relevance and opportunity afforded by machine learning will be discussed.

Computational discoveries of reaction mechanisms: recent highlights and emerging challenges

This review examines some of the notable advances and trends that have shaped the field of computational elucidation of organic reaction mechanisms over the last 10-15 years. It highlights the types of mechanistic problems that have recently become possible to study and summarizes the methodological developments that have permitted these new advances. Case studies are taken from three representative areas of organic chemistry-asymmetric catalysis, glycosylation reactions, and single electron transfer reactions-which illustrate themes common to the broader field. These include the trend towards modelling systems that are increasingly complex (both structurally and mechanistically), the growing appreciation of the mechanistic roles of non-covalent interactions, and the increasing ability to explore dynamical features of reaction mechanisms. Some interesting new challenges that have emerged in the field are identified.

Effect of Solvents on Proline Modified at the Secondary Sphere: A Multivariate Exploration

The critical influence of solvent effects on proline-catalyzed aldol reactions has been extensively described. Herein, we apply multivariate regression strategies to probe the influence of different solvents on an aldol reaction catalyzed by proline modified at its secondary sphere with boronic acids. In this system, both in situ binding of the boronic acid to proline and the outcome of the aldol reaction are impacted by the solvent-controlled microenvironment. Thus, with the aim of uncovering mechanistic insight and an ancillary aim of identifying methodological improvements, we designed a set of experiments, spanning 15 boronic acids in five different solvents. Based on hypothesized intermediates or interactions that could be responsible for the selectivity in these reactions, we proposed several structural configurations for the library of boronic acids. Subsequently, we compared the statistical models correlating the outcome of the reaction in different solvents with molecular descriptors produced for each of these proposed configurations. The models allude to the importance of different interactions in controlling selectivity in each of the studied solvents. As a proof-of-concept for the practicality of our approach, the models in chloroform ultimately led to lowering the ketone loading to only two equivalents while retaining excellent yield and enantio- and diastereo-selectivity.

Morita-Baylis-Hillman Reaction: How Do Optimal Enzyme Active Sites Compare with Organocatalysts

Morita-Baylis-Hillman reaction attracts significant attention for the synthesis of highly functionalized compounds. It requires multiple catalytic elements for efficient catalysis, making it an appealing target for the design of a...

HFIP Mediates a Direct C-C Coupling between Michael Acceptors and Eschenmoser's salt

A direct C-C coupling process merging Michael acceptors and Eschenmoser's salt is presented. Albeit reminiscent of the Morita-Baylis-Hillman reaction, this process requires no Lewis base catalyst. The underlying mechanism could be unveiled by a combination of kinetic, isotopic labelling experiments as well as computational investigations, showcasing the critical role of HFIP as a superior mediator for proton transfer events as well as the decisive role of the halide counterion.

Beyond Continuum Solvent Models in Computational Homogeneous Catalysis

In homogeneous catalysis solvent is an inherent part of the catalytic system. As such, it must be considered in the computational modeling. The most common approach to include solvent effects in quantum mechanical calculations is by means of continuum solvent models. When they are properly used, average solvent effects are efficiently captured, mainly those related with solvent polarity. However, neglecting atomistic description of solvent molecules has its limitations, and continuum solvent models all alone cannot be applied to whatever situation. In many cases, inclusion of explicit solvent molecules in the quantum mechanical description of the system is mandatory. The purpose of this article is to highlight through selected examples what are the reasons that urge to go beyond the continuum models to the employment of micro-solvated (cluster-continuum) of fully explicit solvent models, in this way setting the limits of continuum solvent models in computational homogeneous catalysis. These examples showcase that inclusion of solvent molecules in the calculation not only can improve the description of already known mechanisms but can yield new mechanistic views of a reaction. With the aim of systematizing the use of explicit solvent models, after discussing the success and limitations of continuum solvent models, issues related with solvent coordination and solvent dynamics, solvent effects in reactions involving small, charged species, as well as reactions in protic solvents and the role of solvent as reagent itself are successively considered.

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.

Nazarov Cyclizations Catalyzed by BINOL Phosphoric Acid Derivatives: Quantum Chemistry Struggles To Predict the Enantioselectivity

Quantum chemical calculations have successfully predicted the stereoselectivities of many BINOL phosphoric acid catalyzed reactions over the past 10-15 years. Herein we report a contrasting example: a reaction for which standard quantum chemistry techniques have proven unexpectedly ineffective at explaining the stereoselectivity. The Nazarov cyclizations of a divinyl ketone catalyzed by a BINOL phosphoric acid or H₈-BINOL dithiophosphoric acid were studied with a conventional contemporary quantum chemical approach, consisting of transition state optimizations with B3LYP-D3(BJ) and single-point calculations with several functionals in implicit solvent. Unexpectedly, different functionals gave widely different predictions of the level of enantioselectivity and were unable even to agree on which enantiomer of the product would predominate. Molecular dynamics simulations with the OPLS-AA force field provided evidence that the transition state geometries optimized with DFT in the gas phase or in implicit solvent are not good representations of the true transition states of these reactions in solution. One possible reason for this, which may also explain the failure of quantum chemical techniques to reliably predict the enantioselectivity, is the fact that the transition states contain ion pairs which are not highly organized and do not contain any strongly directional noncovalent interactions between the substrate and the catalyst.

Access to Metal Centers and Fluxional Hydride Coordination Integral for CO2 Insertion into [Fe3(μ-H)3]3+ Clusters

CO₂ insertion into tri(μ-hydrido)triiron(II) clusters ligated by a tris(β-diketiminate) cyclophane is demonstrated to be balanced by sterics for CO₂ approach and hydride accessibility. Time-resolved NMR and UV-vis spectra for this reaction for a complex in which methoxy groups border the pocket of the hydride donor (Fe₃H₃L², 4) result in a decreased activation barrier and increased kinetic isotope effect consistent with the reduced sterics. For the ethyl congener Fe₃H₃L¹ (2), no correlation is found between rate and reaction solvent or added Lewis acids, implying CO₂ coordination to an Fe center in the mechanism. The estimated hydricity (50 kcal/mol) based on observed H/D exchange with BD₃ requires Fe-O bond formation in the product to offset an endergonic CO₂ insertion. μ₃-hydride coordination is noted to lower the activation barrier for the first CO₂ insertion event in DFT calculations.

Computational Mapping of Dirhodium(II) Catalysts

The chemistry of dirhodium(II) catalysts is highly diverse, and can enable the synthesis of many different molecular classes. A tool to aid in catalyst selection, independent of mechanism and reactivity, would therefore be highly desirable. Here, we describe the development of a database for dirhodium(II) catalysts that is based on the principal component analysis of DFT-calculated parameters capturing their steric and electronic properties. This database maps the relevant catalyst space, and may facilitate exploration of the reactivity landscape for any process catalysed by dirhodium(II) complexes. We have shown that one of the principal components of these catalysts correlates with the outcome (e.g. yield, selectivity) of a transformation used in a molecular discovery project. Furthermore, we envisage that this approach will assist the selection of more effective catalyst screening sets, and, hence, the data-led optimisation of a wide range of rhodium-catalysed transformations.

Towards a converged strategy for including microsolvation in reaction mechanism calculations

A major part of chemical conversions is carried out in the fluid phase, where an accurate modeling of the involved reactions requires to also take into account solvation effects. Implicit solvation models often cover these effects with sufficient accuracy but can fail drastically when specific solvent-solute interactions are important. In those cases, microsolvation, i.e., the explicit inclusion of one or more solvent molecules, is a commonly used strategy. Nevertheless, microsolvation also introduces new challenges-a consistent workflow as well as strategies how to systematically improve prediction performance are not evident. For the COSMO and COSMO-RS solvation models, this work proposes a simple protocol to decide if microsolvation is needed and how the corresponding molecular model has to look like. To demonstrate the improved accuracy of the approach, specific application examples are presented and discussed, i.e., the computation of aqueous pK_a values and a mechanistic study of the methanol mediated Morita-Baylis-Hillman reaction.

Artificial intelligence and automation in computer aided synthesis planning

In this perspective we deal with questions pertaining to the development of synthesis planning technologies over the course of recent years.

Mechanism of the highly effective peptide bond hydrolysis by MOF-808 catalyst under biologically relevant conditions

Efficient and selective hydrolysis of inert peptide bonds is of paramount importance. MOF-808, a metal-organic framework based on Zr₆ nodes, can hydrolyze peptide bonds efficiently under biologically relevant conditions. However, the details of the catalyst structure and of the underlying catalytic reaction mechanism are challenging to establish. By means of DFT calculations we first investigate the speciation of the Zr₆ nodes and identify the nature of ligands that bind to the Zr₆O₈H_4-x core in aqueous conditions. The core is predicted to strongly prefer a Zr₆O₈H₄ protonation state and to be predominantly decorated by bridging formate ligands, giving Zr₆(μ₃-O)₄(μ₃-OH)₄(BTC)₂(HCOO)₆ and Zr₆(μ₃-O)₄(μ₃-OH)₄(BTC)₂(HCOO)₅(OH)(H₂O) as the most favorable structures at physiological pH. The GlyGly peptide can bind MOF in several different ways, with the preferred structure involving coordination through the terminal carboxylate analogously to the binding mode of formate ligand. The pre-reactive binding mode in which the amide carbonyl oxygen coordinates the metal core lies 7 kcal higher in free energy. The preferred reaction pathway is predicted to have two close-lying transition states, either of which could be the rate-determining step: nucleophilic attack on the amide carbon atom and C-N bond breaking, with calculated relative free energies of 31 and 32 kcal mol^-1, respectively. Replacement of formate by water and hydroxide at the Zr₆ node is predicted to be possible, but does not appear to play a role in the hydrolysis mechanism.

First-principles modeling of chemistry in mixed solvents: Where to go from here?

Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.

Direct comparison of safer or sustainable alternative dipolar aprotic solvents for use in carbon–carbon bond formation

Direct comparison of safer dipolar aprotic solvents for use in carbon–carbon bond formation is of vital importance for industrial applications. Cyrene exhibited high initial reaction rates, yields and solvent recovery in the Baylis–Hillman reaction.

Limitations of Ligand-Only Approaches for Predicting the Reactivity of Covalent Inhibitors

Covalent inhibition has undergone a resurgence and is an important modern-day drug design and chemical biology approach. To avoid off-target interactions and to fine-tune reactivity, the ability to accurately predict reactivity is vitally important for the design and development of safer and more effective covalent drugs. Several ligand-only metrics have been proposed that promise quick and simple ways of determining covalent reactivity. In particular, we examine proton affinity and reaction energies calculated with the density functional B3LYP-D3/6-311+G**//B3LYP-D3/6-31G* method to assess the reactivity of a series of α,β-unsaturated carbonyl compounds that form covalent adducts with cysteine. We demonstrate that while these metrics correlate well with experiment for a diverse range of small reactive molecules these approaches fail for predicting the reactivity of drug-like compounds. We conclude that ligand-only metrics such as proton affinity and reaction energies do not capture determinants of reactivity in situ and fail to account for important factors such as conformation, solvation, and intermolecular interactions.

Theoretical prediction of Ni(I)-catalyst for hydrosilylation of pyridine and quinoline

Catalytic synthesis of dihydropyridine by transition-metal complex is one of the important research targets, recently. Density functional theory calculations here demonstrate that nickel(I) hydride complex (bpy)Ni^I H (bpy = 2,2'-bipyridine) 1 is a good catalyst for hydrosilylation of both quinoline and pyridine. Two pathways are possible; in path 1, substrate reacts with 1 to form stable intermediate Int1. After that, N³ ─C¹ bond of substrate inserts into Ni─H bond of 1 via TS1 to afford N-coordinated 1,2-dihydroquinoline Int2 with the Gibbs activation energy (ΔG°^‡ ) of 21.8 kcal mol^-1 . Then, Int2 reacts with hydrosilane to form hydrosilane σ-complex Int3; this is named path 1A. In the other route (path 1B), Int1 reacts with phenylsilane in a concerted manner via hydride-shuttle transition state TS2 to afford Int3. In TS2, Si atom takes hypervalent trigonal bipyramidal structure. Formation of hypervalent structure is crucial for stabilization of TS2 (ΔG°^‡ = 17.3 kcal mol^-1 ). The final step of path 1 is metathesis between Ni─N³ bond of Int3 and Si─H bond of PhSiH₃ to afford N-silylated 1,2-dihydroproduct and regenerate 1 (ΔG°^‡ = 4.5 kcal mol^-1 ). In path 2, 1 reacts with hydrosilane to form Int5, which then forms adduct Int6 with substrate through Si-N interaction between substrate and PhSiH₃ . Then, N-silylated 1,2-dihydroproduct is produced via hydride-shuttle transition state TS5 (ΔG°^‡ = 18.8 kcal mol^-1 ). The absence of N-coordination of substrate to Ni^I in TS5 is the reason why path 2 is less favorable than path 1B. Quinoline hydrosilylation occurs more easily than pyridine because quinoline has the lowest unoccupied molecular orbital at lower energy than that of pyridine. © 2019 Wiley Periodicals, Inc.

Projector-Based Embedding Eliminates Density Functional Dependence for QM/MM Calculations of Reactions in Enzymes and Solution

Combined quantum mechanics/molecular mechanics (QM/MM) methods are increasingly widely utilized in studies of reactions in enzymes and other large systems. Here, we apply a range of QM/MM methods to investigate the Claisen rearrangement of chorismate to prephenate, in solution, and in the enzyme chorismate mutase. Using projector-based embedding in a QM/MM framework, we apply treatments up to the CCSD(T) level. We test a range of density functional QM/MM methods and QM region sizes. The results show that the calculated reaction energetics are significantly more sensitive to the choice of density functional than they are to the size of the QM region in these systems. Projector-based embedding of a wave function method in DFT reduced the 13 kcal/mol spread in barrier heights calculated at the DFT/MM level to a spread of just 0.3 kcal/mol, essentially eliminating dependence on the functional. Projector-based embedding of correlated ab initio methods provides a practical method for achieving high accuracy for energy profiles derived from DFT and DFT/MM calculations for reactions in condensed phases.

Computational Ligand Descriptors for Catalyst Design

Ligands, especially phosphines and carbenes, can play a key role in modifying and controlling homogeneous organometallic catalysts, and they often provide a convenient approach to fine-tuning the performance of known catalysts. The measurable outcomes of such catalyst modifications (yields, rates, selectivity) can be set into context by establishing their relationship to steric and electronic descriptors of ligand properties, and such models can guide the discovery, optimization, and design of catalysts. In this review we present a survey of calculated ligand descriptors, with a particular focus on homogeneous organometallic catalysis. A range of different approaches to calculating steric and electronic parameters are set out and compared, and we have collected descriptors for a range of representative ligand sets, including 30 monodentate phosphorus(III) donor ligands, 23 bidentate P,P-donor ligands, and 30 carbenes, with a view to providing a useful resource for analysis to practitioners. In addition, several case studies of applications of such descriptors, covering both maps and models, have been reviewed, illustrating how descriptor-led studies of catalysis can inform experiments and highlighting good practice for model comparison and evaluation.

Suzuki–Miyaura coupling revisited: an integrated computational study

Computation is used to revisit the mechanism of the Suzuki–Miyaura coupling mechanism.

Stereospecific 1,3-H Transfer of Indenols Proceeds via Persistent Ion-Pairs Anchored by NH···π Interactions

The base-catalyzed rearrangement of arylindenols is a rare example of a suprafacial [1,3]-hydrogen atom transfer. The mechanism has been proposed to proceed via sequential [1,5]-sigmatropic shifts, which occur in a selective sense and avoid an achiral intermediate. A computational analysis using quantum chemistry casts serious doubt on these suggestions: These pathways have enormous activation barriers, and in constrast to what is observed experimentally, they overwhelmingly favor a racemic product. Instead we propose that a suprafacial [1,3]-prototopic shift occurs in a two-step deprotonation/reprotonation sequence. This mechanism is favored by 15 kcal mol^-1 over that previously proposed. Most importantly, this is also consistent with stereospecificity since reprotonation occurs rapidly on the same π-face. We have used explicitly solvated molecular dynamics studies to study the persistence and condensed-phase dynamics of the intermediate ion-pair formed in this reaction. Chirality transfer is the result of a particularly resilient contact ion-pair, held together by electrostatic attraction and a critical NH···π interaction which ensures that this species has an appreciable lifetime even in polar solvents such as DMSO and MeOH.