Computation and Experiment: A Powerful Combination to Understand and Predict Reactivities

Automated exploration of the conformational degrees of freedom along reaction profiles - driving a FASTCAR

This publication aims at presenting a Python-based workflow designed to enable a fully automatised and exhaustive exploration of the conformational degrees of freedom within the calculation of reaction paths in molecular systems. The proposed strategy focuses on effectively representing the lowest energy conformers for intricate, highly rotatable, and non-intuitive transition states, reagents and products, using existing computational tools. The article presents a workflow that is demonstrated through the application of five chemical reactions, chosen to be representative of the diversity and complexity of actual experimental studies, and which often prove to be challenging to study "by hand". The proposed methodology is expected to be of a great help in the modelling of state-of-the art organic chemistry reactions, whose complexity is ever increasing.

Assessment of the similarity-transformed equation of motion (STEOM) for open-shell organic and transition metal molecules

This study benchmarks the newly re-implemented single-reference excited-state methods, IP-EOM-CCSD, EA-EOM-CCSD, and STEOM-CCSD, in ORCA6.0, with a focus on open-shell systems. We compare STEOM against EOM-CCSD, CC3, and CCSDT across a range of systems, including small organic radicals, hydrated transition metal (TM) ions, and TM diatomic systems with both closed and open-shell configurations. For organic radicals, STEOM and EOM-CCSD show comparable performance, aligning closely with CC3 and CCSDT results. In the case of hydrated TM ions, IP-EOM closely matches DLPNO-CCSD results, while deviations from DLPNO-CCSD(T) are consistent. For open-shell TM systems, IP-EOM exhibits a blueshift relative to both the DLPNO-CCSD methods, while EA-EOM-CCSD shows better agreement. When comparing STEOM and CC3 to CCSDT, STEOM shows slightly larger deviations in closed-shell systems but shows excellent agreement in open-shell systems. Computational efficiency is also assessed, revealing a significant speedup in ORCA 6.0 compared to ORCA 5.0, with optimizations improving computation times. This study provides valuable insights into the performance and efficiency of STEOM in various chemical environments, highlighting its strengths and limitations.

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.

Mechanism of Z-Selective Allylic Functionalization via Thianthrenium Salts

A detailed mechanistic study of the Z-selective allylic functionalization via thianthrenium salts is presented. Kinetic analyses, deuterium labeling experiments, and computational methods are used to rationalize the observed reactivity and selectivity. We find that the reaction proceeds via a rate-determining and stereodetermining allylic deprotonation of an alkenylthianthrenium species. The Z-configuration of the resultant allylic ylide is translated into the Z-allylic amine product through a sequence of subsequent fast and irreversible steps: protonation to form a Z-allylic thianthrenium electrophile and then regioselective substitution by the nucleophile. In the stereodetermining deprotonation step, computational studies identified a series of stabilizing nonbonding interactions in the Z-alkene-forming transition state that contribute to the stereoselectivity.

Analysing the stability of He-filled hydrates: how many He atoms fit in the sII crystal?

Clathrate hydrates have the ability to encapsulate atoms and molecules within their cavities, and thus they could be potentially large storage capacity materials. The present work studies the multiple cage occupancy effects in the recently discovered He@sII crystal. On the basis of previous theoretical and experimental findings, the stability of He(1/1)@sII, He(1/4)@sII and He(2/4)@sII crystals was analysed in terms of structural, mechanical and energetic properties. For this purpose, first-principles DFT/DFT-D computations were performed by using both semi-local and non-local functionals, not only to elucidate which configuration is the most energetically favoured, but also to scrutinize the relevance of the long-range dispersion interactions in these kinds of compounds. We have encountered that dispersion interactions play a fundamental role in describing the underlying interactions, and different tendencies were observed depending on the choice of the functional. We found that PW86PBE-XDM shows the best performance, while the non-local functionals tested here were not able to correctly account for them. The present results reveal that the most stable configuration is the one presenting singly occupied D cages and tetrahedrally occupied H cages (He(1/4)@sII) in line with the experimental observation.

DFT-Guided Mechanistic Insights into Chemodivergence: A Mixed Explicit-Implicit Solvent Description to Dictate the Chemoselectivity

Herein we report a density functional theory (DFT)-guided mechanistic investigation of the nitrile reduction reaction, which exhibits a solvent-dependent chemodivergence. This study reveals an interesting mechanistic picture, highlighting the exact role of a protic solvent, isopropanol, in regulating the reaction outcome. The explicit solvent effect involving polar protic isopropanol favors imine metathesis by proton hopping through stepwise addition and elimination steps and thus produces a secondary amine as the final product. In contrast, the nonpolar solvent n-hexane is incapable of facilitating the proton migration and stops the solvent-assisted imine metathesis. As a result, only primary amines are obtained as the final product. This DFT study provides a recipe for the choice of solvents that can dictate chemoselectivity in product formation.

Reference Vertical Excitation Energies for Transition Metal Compounds

To enrich and enhance the diversity of the quest database of highly accurate excitation energies [Véril, M.; et al. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2021, 11, e1517], we report vertical transition energies in transition metal compounds. Eleven diatomic molecules with a singlet or doublet ground state containing a fourth-row transition metal (CuCl, CuF, CuH, ScF, ScH, ScO, ScS, TiN, ZnH, ZnO, and ZnS) are considered, and the corresponding excitation energies are computed using high-level coupled-cluster (CC) methods, namely, CC3, CCSDT, CC4, and CCSDTQ, as well as multiconfigurational methods such as CASPT2 and NEVPT2. In many cases, to provide more comprehensive benchmark data, we also provide full configuration interaction estimates computed with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. Based on these calculations, theoretical best estimates of the transition energies are established in both the aug-cc-pVDZ and aug-cc-pVTZ basis sets. This allows us to accurately assess the performance of the CC and multiconfigurational methods for this specific set of challenging transitions. Furthermore, comparisons with experimental data and previous theoretical results are also reported.

Quantum chemical calculations for reaction prediction in the development of synthetic methodologies

Quantum chemical calculations have been used in the development of synthetic methodologies to analyze the reaction mechanisms of the developed reactions. Their ability to estimate chemical reaction pathways, including transition state energies and connected equilibria, has led researchers to embrace their use in predicting unknown reactions. This perspective highlights strategies that leverage quantum chemical calculations for the prediction of reactions in the discovery of new methodologies. Selected examples demonstrate how computation has driven the development of unknown reactions, catalyst design, and the exploration of synthetic routes to complex molecules prior to often laborious, costly, and time-consuming experimental investigations.

A substrate descriptor based approach for the prediction and understanding of the regioselectivity in caged catalyzed hydroformylation

The use of data driven tools to predict the selectivity of homogeneous catalysts has received considerable attention in the past years. In these studies often the catalyst structure is varied, but the use of substrate descriptors to rationalize the catalytic outcome is relatively unexplored. To study whether this may be an effective tool, we investigated both an encapsulated and a non-encapsulated rhodium based catalyst in the hydroformylation reaction of 41 terminal alkenes. For the non-encapsulated catalyst, CAT2, the regioselectivity of the acquired substrate scope could be predicted with high accuracy using the Δ13C NMR shift of the alkene carbon atoms as a descriptor (R2 = 0.74) and when combined with a computed intensity of the CC stretch vibration (ICC stretch) the accuracy increased further (R2 = 0.86). In contrast, a substrate descriptor approach with an encapsulated catalyst, CAT1, appeared more challenging indicating a confined space effect. We investigated Sterimol parameters of the substrates as well as computer-aided drug design descriptors of the substrates, but these parameters did not result in a predictive formula. The most accurate substrate descriptor based prediction was made with the Δ13C NMR shift and ICC stretch (R2 = 0.52), suggestive of the involvement of CH-π interactions. To further understand the confined space effect of CAT1, we focused on the subset of 21 allylbenzene derivatives to investigate predictive parameters unique for this subset. These results showed the inclusion of a charge parameter of the aryl ring improved the regioselectivity predictions, which is in agreement with our assessment that noncovalent interactions between the phenyl ring of the cage and the aryl ring of the substrate are relevant for the regioselectivity outcome. However, the correlation is still weak (R2 = 0.36) and as such we are investigating novel parameters that should improve the overall regioselectivity outcome.

Emerging Metabolic Profiles of Sulfonamide Antibiotics by Cytochromes P450: A Computational-Experimental Synergy Study on Emerging Pollutants

Metabolism, especially by CYP450 enzymes, is the main reason for mediating the toxification and detoxification of xenobiotics in humans, while some uncommon metabolic pathways, especially for emerging pollutants, probably causing idiosyncratic toxicity are easily overlooked. The pollution of sulfonamide antibiotics in aqueous system has attracted increasing public attention. Hydroxylation of the central amine group can trigger a series of metabolic processes of sulfonamide antibiotics in humans; however, this work parallelly reported the coupling and fragmenting initiated by amino H-abstraction of sulfamethoxazole (SMX) catalyzed by human CYP450 enzymes. Elucidation of the emerging metabolic profiles was mapped via a multistep synergy between computations and experiments, involving preliminary DFT computations and in vitro and in vivo assays, profiling adverse effects, and rationalizing the fundamental factors via targeted computations. Especially, the confirmed SMX dimer was shown to potentially act as a metabolism disruptor in humans, while spin aromatic delocalization resulting in the low electron donor ability of amino radicals was revealed as the fundamental factor to enable coupling of sulfonamide antibiotics by CYP450 through the nonconventional nonrebound pathway. This work may further strengthen the synergistic use of computations prior to experiments to avoid wasteful experimental screening efforts in environmental chemistry and toxicology.

Experimental and Computational Investigation of Facial Selectivity Switching in Nickel-Diamine-Acetate-Catalyzed Michael Reactions

Chiral Ni complexes have revolutionized both asymmetric acid-base and redox catalysis. However, the coordination isomerism of Ni complexes and their open-shell property still often hinder the elucidation of the origin of their observed stereoselectivity. Here, we report our experimental and computational investigations to clarify the mechanism of β-nitrostyrene facial selectivity switching in Ni(II)-diamine-(OAc)₂-catalyzed asymmetric Michael reactions. In the reaction with a dimethyl malonate, the Evans transition state (TS), in which the enolate binds in the same plane with the diamine ligand, is identified as the lowest-energy TS to promote C-C bond formation from the Si face in β-nitrostyrene. In contrast, a detailed survey of the multiple potential pathways in the reaction with α-keto esters points to a clear preference for our proposed C-C bond-forming TS, in which the enolate coordinates to the Ni(II) center in apical-equatorial positions relative to the diamine ligand, thereby promoting Re face addition in β-nitrostyrene. The N-H group plays a key orientational role in minimizing steric repulsion.

Further Develop 1,3,4-Thiadiazole Based Probe to Effectively Detect 2,4,6-Trinitrophenol with the Help of DFT Calculations

Four fluorimetric probes had been developed to rapidly detect 2,4,6-trinitrophenol (TNP). They were designed and synthesized on the basis of 1,3,4-thiadiazole framework combining calculation with experiment. Among them, SK-1 displayed strong blue emission with fluorescence quantum yield as high as 63.6% in solution. Further evaluation demonstrated that SK-1 displays good selectivity and high sensitivity for rapid and visual detection of TNP. It brought significant changes in both colour and fluorescence emission spectrum. The detection limit was as low as 38 nM. Quenching mechanism was confirmed as photo-induced electron transfer (PET) by nuclear magnetic titration and DFT calculations. What's more, application in real water samples and solid phase paper tests illustrated the practical significance of detection of TNP in both vapor and solution.

Mechanisms, Challenges, and Opportunities of Dual Ni/Photoredox-Catalyzed C(sp2)-C(sp3) Cross-Couplings

The merging of photoredox and nickel catalysis has revolutionized the field of C-C cross-coupling. However, in comparison to the development of synthetic methods, detailed mechanistic investigations of these catalytic systems are lagging. To improve the mechanistic understanding, computational tools have emerged as powerful tools to elucidate the factors controlling reactivity and selectivity in these complex catalytic transformations. Based on the reported computational studies, it appears that the mechanistic picture of catalytic systems is not generally applicable, but is rather dependent on the specific choice of substrate, ligands, photocatalysts, etc. Given the complexity of these systems, the need for more accurate computational methods, readily available and user-friendly dynamics simulation tools, and data-driven approaches is clear in order to understand at the molecular level the mechanisms of these transformations. In particular, we anticipate that such improvement of theoretical methods will become crucial to advance the understanding of excited-state properties and dynamics of key species, as well as to enable faster and unbiased exploration of reaction pathways. Further, with greater collaboration between computational, experimental, and spectroscopic communities, the mechanistic investigation of photoredox/Ni dual-catalytic reactions is expected to thrive quickly, facilitating the design of novel catalytic systems and promoting our understanding of the reaction selectivity.

New Insights and Predictions into Complex Homogeneous Reactions Enabled by Computational Chemistry in Synergy with Experiments: Isotopes and Mechanisms

Homogeneous catalysis and biocatalysis have been widely applied in synthetic, medicinal, and energy chemistry as well as synthetic biology. Driven by developments of new computational chemistry methods and better computer hardware, computational chemistry has become an essentially indispensable mechanistic "instrument" to help understand structures and decipher reaction mechanisms in catalysis. In addition, synergy between computational and experimental chemistry deepens our mechanistic understanding, which further promotes the rational design of new catalysts. In this Account, we summarize new or deeper mechanistic insights (including isotope, dispersion, and dynamical effects) into several complex homogeneous reactions from our systematic computational studies along with subsequent experimental studies by different groups. Apart from uncovering new mechanisms in some reactions, a few computational predictions (such as excited-state heavy-atom tunneling, steric-controlled enantioswitching, and a new geminal addition mechanism) based on our mechanistic insights were further verified by ensuing experiments.The Zimmerman group developed a photoinduced triplet di-π-methane rearrangement to form cyclopropane derivatives. Recently, our computational study predicted the first excited-state heavy-atom (carbon) quantum tunneling in one triplet di-π-methane rearrangement, in which the reaction rates and ¹²C/¹³C kinetic isotope effects (KIEs) can be enhanced by quantum tunneling at low temperatures. This unprecedented excited-state heavy-atom tunneling in a photoinduced reaction has recently been verified by an experimental ¹²C/¹³C KIE study by the Singleton group. Such combined computational and experimental studies should open up opportunities to discover more rare excited-state heavy-atom tunneling in other photoinduced reactions. In addition, we found unexpectedly large secondary KIE values in the five-coordinate Fe(III)-catalyzed hetero-Diels-Alder pathway, even with substantial C-C bond formation, due to the non-negligible equilibrium isotope effect (EIE) derived from altered metal coordination. Therefore, these KIE values cannot reliably reflect transition-state structures for the five-coordinate metal pathway. Furthermore, our density functional theory (DFT) quasi-classical molecular dynamics (MD) simulations demonstrated that the coordination mode and/or spin state of the iron metal as well as an electric field can affect the dynamics of this reaction (e.g., the dynamically stepwise process, the entrance/exit reaction channels).Moreover, we unveiled a new reaction mechanism to account for the uncommon Ru(II)-catalyzed geminal-addition semihydrogenation and hydroboration of silyl alkynes. Our proposed key gem-Ru(II)-carbene intermediates derived from double migrations on the same alkyne carbon were verified by crossover experiments. Additionally, our DFT MD simulations suggested that the first hydrogen migration transition-state structures may directly and quickly form the key gem-Ru-carbene structures, thereby "bypassing" the second migration step. Furthermore, our extensive study revealed the origin of the enantioselectivity of the Cu(I)-catalyzed 1,3-dipolar cycloaddition of azomethine ylides with β-substituted alkenyl bicyclic heteroarenes enabled by dual coordination of both substrates. Such mechanistic insights promoted our computational predictions of the enantioselectivity reversal for the corresponding monocyclic heteroarene substrates and the regiospecific addition to the less reactive internal C═C bond of one diene substrate. These predictions were proven by our experimental collaborators. Finally, our mechanistic insights into a few other reactions are also presented. Overall, we hope that these interactive computational and experimental studies enrich our mechanistic understanding and aid in reaction development.

Accurately selected 1,3,4-thiadiazole and coumarin unit to construct fluorescent probes that effectively detect 2,4,6-trinitrophenol

Two remarkablely fluorimetric probes were developed to rapidly detect 2,4,6-trinitrophenol (TNP). With the help of density functional theory (DFT) calculations, we confirmed that using 1,3,4-thiadiazole skeleton as recognition group and coumarin unit as fluorophore would show excellent application prospects in terms of TNP detection. The probes LK-1 and LK-2 displayed green and orange emission with fluorescence quenching yield as high as 83.7% and 75.1% in solution. Further evaluation demonstrated that they display outstanding selectivity and sensitivity for rapid and visual detection of TNP. Both fluorescent color and fluorescence emission spectrum had significant changes and these phenomena could easily observe via naked-eye and analytical instrument. The detection limits of them were 97 nM and 71 nM. What's more, application in real water samples and solid phase paper tests illustrated the practical significance of detection of TNP.

Mechanism and Stereochemistry of Rhodium-Catalyzed [5 + 2 + 1] Cycloaddition of Ene-Vinylcyclopropanes and Carbon Monoxide Revealed by Visual Kinetic Analysis and Quantum Chemical Calculations

Previously, we developed a rhodium-catalyzed [5 + 2 + 1] cycloaddition of ene-vinylcyclopropanes (ene-VCPs) and carbon monoxide to synthesize eight-membered carbocycles. The efficiency of this reaction can be appreciated from its application in the synthesis of several natural products. Herein we report the results of a 15-year investigation into the mechanism of the [5 + 2 + 1] cycloaddition by applying visual kinetic analysis and high-level quantum chemical calculations at the DLPNO-CCSD(T)//BMK level. According to the kinetic measurements, the resting state of the catalyst possesses a dimeric structure (with two rhodium centers) whereas the active catalytic species is monomeric (with one rhodium center). The catalytic cycle consists of cyclopropane cleavage (the turnover-limiting step), alkene insertion, CO insertion, reductive elimination, and catalyst transfer steps. Other reaction pathways have also been considered but then have been ruled out. The steric origin of the diastereoselectivity (cis versus trans) was revealed by comparing the alkene insertion transition states. In addition, how the double-bond configuration of the VCPs (Z versus E) affects the substrate reactivity and the origins of chemoselectivity ([5 + 2 + 1] versus [5 + 2]) were also investigated. The present study will provide assistance in understanding other carbonylative annulations catalyzed by transition metals.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

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SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11244-021-01543-9.

VCD spectroscopy distinguishes the enamine and iminium ion of a 1,1’-binaphthyl azepine

We present a VCD spectroscopic characterization of a chiral 1,1’-binaphthyl azepine catalyst and show that the VCD spectra of an in-situ generated enamine and an ex-situ prepared iminium ion are...

Feeding sequence-regulated divergent (4 + 1 + 1’) annulations of α-bromo carbonyls and 1-azadienes via computational calculations-based mechanism elucidation

By investigating the mechanism of our previously reported (4 + 1 + 1) annulations of α-bromo carbonyls and 1-azadienes via density functional theory (DFT) calculations, the formation of a carbon...

Theoretical mechanistic study of 4CzIPN/Ni0-metallaphotoredox catalyzed enantioselective desymmetrization of cyclic meso-anhydrides

Visible-light-induced inexpensive photocatalyst and transition metal dual catalytic cross-coupling has attracted much attention for efficiently constructing various chemical bonds. The 4CzIPN/Ni⁰-metallaphotoredox catalyzed enantioselective desymmetrization of cyclic meso-anhydrides with benzyl trifluoroborates has been systematically investigated using density functional theory (DFT) calculations. A radical mechanism merging reductive quenching (PC-*PC-PC^--PC) and nickel catalytic cycles (Ni⁰-Ni^II-Ni^III-Ni^I-Ni⁰) is favourable. It consists of seven major processes: single-electron reduction of *PC by benzyl trifluoroborates to generate benzyl radical, ligand exchange, oxidative addition, radical addition, reductive elimination, reduction of Ni^I by PC^- complex via single-electron transfer (SET) process to obtain ground-state PC, and the ion exchange to afford the desired product enantio-enriched keto-acids and regenerate Ni⁰ catalyst. The oxidative addition is not only the enantio-determining step but also the rate-determining step of the catalytic cycle. In addition, we tried to disclose the origin of high enantioselectivity from both the steric and electronic effects and explain the origin of diastereoselectivity based on the proposed mechanism. Meanwhile, the difference of catalytic activity between Ni⁰ and Ni^II as the initial catalysts is caused by the different activation energy barriers based on their respective favourable reaction pathways. This study will hopefully benefit the future understanding of such photoredox-mediated dual catalyzed asymmetric synthesis.

Precision Biotransformation of Emerging Pollutants by Human Cytochrome P450 Using Computational-Experimental Synergy: A Case Study of Tris(1,3-dichloro-2-propyl) Phosphate

Precision biotransformation is an envisioned strategy offering detailed insights into biotransformation pathways in real environmental settings using experimentally guided high-accuracy quantum chemistry. Emerging pollutants, whose metabolites are easily overlooked but may cause idiosyncratic toxicity, are important targets of such a strategy. We demonstrate here that complex metabolic reactions of tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) catalyzed by human CYP450 enzymes can be mapped via a three-step synergy strategy: (i) screening the possible metabolites via high-throughout (moderate-accuracy) computations; (ii) analyzing the proposed metabolites in vitro by human liver microsomes and recombinant human CYP450 enzymes; and (iii) rationalizing the experimental data via precise mechanisms using high-level targeted computations. Through the bilateral dialogues from qualitative to semi-quantitative to quantitative levels, we show how TDCIPP metabolism especially by CYP3A4 generates bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) as an O-dealkylation metabolite and bis(1,3-dichloro-2-propyl) 3-chloro-1-hydroxy-2-propyl phosphate (alcohol_β-dehalogen) as a dehalogenation/reduction metabolite via the initial rate-determining H-abstraction from αC- and βC-positions. The relative yield ratio [dehalogenation/reduction]/[O-dealkylation] is derived from the relative barriers of H-abstraction at the βC- and αC-positions by CYP3A4, estimated as 0.002 to 0.23, viz., an in vitro measured ratio of 0.04. Importantly, alcohol_β-dehalogen formation points to a new mechanism involving successive oxidation and reduction functions of CYP450, with its precursor aldehyde_β-dehalogen being a key intermediate detected by trapping assays and rationalized by computations. We conclude that the proposed three-step synergy strategy may meet the increasing challenge of elucidating biotransformation mechanisms of substantial synthesized organic compounds in the future.

Melding of Experiment and Theory Illuminates Mechanisms of Metal-Catalyzed Rearrangements: Computational Approaches and Caveats

This review summarizes approaches and caveats in computational modeling of transition-metal-catalyzed sigmatropic rearrangements involving carbene transfer. We highlight contemporary examples of combined synthetic and theoretical investigations that showcase the synergy achievable by integrating experiment and theory.

1 Introduction

2 Mechanistic Models

3 Theoretical Approaches and Caveats

3.1 Recommended Computational Tools

3.2 Choice of Functional and Basis Set

3.3 Conformations and Ligand-Binding Modes

3.4 Solvation

4 Synergy of Experiment and Theory – Case Studies

4.1 Metal-Bound or Free Ylides?

4.2 Conformations and Ligand-Binding Modes of Paddlewheel Complexes

4.3 No Metal, Just Light

4.4 How To ‘Cope’ with Nonstatistical Dynamic Effects

5 Outlook

Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning

Transition-metal complexes are attractive targets for the design of catalysts and functional materials. The behavior of the metal-organic bond, while very tunable for achieving target properties, is challenging to predict and necessitates searching a wide and complex space to identify needles in haystacks for target applications. This review will focus on the techniques that make high-throughput search of transition-metal chemical space feasible for the discovery of complexes with desirable properties. The review will cover the development, promise, and limitations of "traditional" computational chemistry (i.e., force field, semiempirical, and density functional theory methods) as it pertains to data generation for inorganic molecular discovery. The review will also discuss the opportunities and limitations in leveraging experimental data sources. We will focus on how advances in statistical modeling, artificial intelligence, multiobjective optimization, and automation accelerate discovery of lead compounds and design rules. The overall objective of this review is to showcase how bringing together advances from diverse areas of computational chemistry and computer science have enabled the rapid uncovering of structure-property relationships in transition-metal chemistry. We aim to highlight how unique considerations in motifs of metal-organic bonding (e.g., variable spin and oxidation state, and bonding strength/nature) set them and their discovery apart from more commonly considered organic molecules. We will also highlight how uncertainty and relative data scarcity in transition-metal chemistry motivate specific developments in machine learning representations, model training, and in computational chemistry. Finally, we will conclude with an outlook of areas of opportunity for the accelerated discovery of transition-metal complexes.

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.

Potent cyclometallated Pd(II) antitumor complexes bearing α-amino acids: synthesis, structural characterization, DNA/BSA binding, cytotoxicity and molecular dynamics simulation

A rational approach was adopted to design high-potential metal-based antitumor agents. A series of organometallic Pd(ii) complexes with a general formula of [Pd{κ2(C,C)-[(C6H4-2)PPh2]CH(CO)C6H4Ph-4}{κ2(N,O)}] (N,O = alanine (Pd-A), valine (Pd-V), leucine (Pd-L), l-isoleucine (Pd-I) and phenylalanine (Pd-F)) were prepared by cyclopalladation of the phosphorus ylide, bridge cleavage reaction and subsequent chelation of natural α-amino acids. The complexes were fully identified using IR and multinuclear 1H, 13C, 31P NMR spectroscopic methods. X-ray crystallography exhibited that the Pd(ii) atom is located in a slightly distorted square-planar environment surrounded by C,C-orthometallated phosphorus ylide as well as NO-pendant amino acid functionality. In vitro cytotoxicity evaluation of new cyclometallated Pd(ii) complexes toward a human leukemia (K562) cancer cell line indicated promising results. The highest cytotoxic activity was discovered in the case of phenylalanine (CH2C6H5). IC50 values of this complex on a panel of human tumor cell lines representative of liver (HepG2), breast (SKBR-3), and ovarian (A2780-Resistance/Sensitive) cancers also indicated promising antitumor effects in comparison with standard cisplatin. The binding interaction ability of the phenylalanine-containing orthopalladated complex, as the most efficient compound, with calf-thymus deoxyribonucleic acid (CT-DNA) and bovine serum albumin (BSA) was investigated. UV-Vis spectroscopy, competitive emission titration, and circular dichroism (CD) techniques demonstrated the intercalative binding of the Pd(ii) complex with DNA. Molecular docking studies also fully agreed with the experimental data. Examination of the reactivity towards the protein BSA revealed that the static quenching mechanism of BSA intrinsic fluorescence by the Pd(ii) complex with a binding constant (Kb) of ∼105 is indicative of the high affinity of the complex. The competitive binding experiment using site markers with definite binding sites demonstrated that the hydrophobic cavities of site I (subdomain IIA) are responsible for the bimolecular interaction between protein BSA and the complex. Molecular docking studies effectively confirmed the significance of hydrophobic interactions in Pd(ii)-BSA binding. The results of this study could greatly contribute to exploring new potent metal-based anticancer drugs.

Dynamics in Catalytic Asymmetric Diastereoconvergent (3 + 2) Cycloadditions with Isomerizable Nitrones and α-Keto Ester Enolates

Reaction design in asymmetric catalysis has traditionally been predicated on a structurally robust scaffold in both substrates and catalysts, to reduce the number of possible diastereomeric transition states. Herein, we present the stereochemical dynamics in the Ni(II)-catalyzed diastereoconvergent (3 + 2) cycloadditions of isomerizable nitrile-conjugated nitrones with α-keto ester enolates. Even in the presence of multiple equilibrating species, the catalytic protocol displays a wide substrate scope to access a range of CN-containing building blocks bearing adjacent stereocenters with high enantio- and diastereoselectivities. Our computational investigations suggest that the enantioselectivity is governed in the deprotonation process to form (Z)-Ni-enolates, while the unique syn addition is mainly controlled by weak noncovalent bonding interactions between the nitrone and ligand.

Predicting Dinitrogen Activation via Transition-Metal-Involved [4+2] Cycloaddition Reaction

As the strongest triple bond in nature, the N≡N triple bond activation has always been a challenging project in chemistry. On the other hand, since the award of the Nobel Prize in Chemistry in 1950, the Diels-Alder reaction has served as a powerful and widely applied tool in the synthesis of natural products and new materials. However, the application of the Diels-Alder reaction to dinitrogen activation remains less developed. Here we first demonstrate that a transition-metal-involved [4+2] Diels-Alder cycloaddition reaction could be used to activate dinitrogen without an additional reductant by density functional theory calculations. Further study reveals that such a dinitrogen activation by 1-metalla-1,3-dienes screened out from a series of transition metal complexes (38 species) according to the effects of metal center, ligand, and substituents can become favorable both thermodynamically (with an exergonicity of 28.2 kcal mol^-1 ) and kinetically (with an activation energy as low as 13.8 kcal mol^-1 ). Our findings highlight an important application of the Diels-Alder reaction in dinitrogen activation, inviting experimental chemists' verification.

A dynamic picture of the halolactonization reaction through a combination of ab initio metadynamics and experimental investigations

The halolactonization reaction is one of the most common electrophilic addition reactions to alkenes. The mechanism is generally viewed as a two-step pathway, which involves the formation of an ionic intermediate, in most cases a haliranium ion. Recently, an alternative concerted mechanism was proposed, in which the nucleophile of the reaction played a key role in the rate determining step by forming a pre-polarized complex with the alkene. This pathway was coined the nucleophile-assisted alkene activation (NAAA) mechanism. Metadynamics simulations on a series of model halolactonization reactions were used to obtain the full dynamic trajectory from reactant to product and investigate the explicit role of the halogen source and solvent molecules in the mechanism. The results in this work ratify the occasional preference of a concerted mechanism over the classic two-step transformation under specific reaction conditions. Nevertheless, as the stability of both the generated substrate cation and counter-anion increase, a transition towards the classic two-step mechanism was observed. NCI analyses on the transition states revealed that the activating role of the nucleophile is independent of the formation and stability of the intermediate. Additionally, the dynamic insights obtained from the metadynamics simulations and NCI analyses employed in this work, unveiled the presence of syn-directing noncovalent interactions, such as hydrogen bonding, between the alkenoic acid and the halogen source, which rationalized the experimentally observed diastereoselectivities. Explicit noncovalent interactions between the reactants and a protic solvent or basic additive are able to disrupt these syn-directing noncovalent interactions, affecting the diastereoselective outcome of the reaction.

Base-Free Cross-Couplings of Aryl Diazonium Salts in Methanol: PdII -Alkoxy as Reactivity-Controlling Intermediate

Pd-catalyzed cross-coupling reactions of aryl diazonium salts are generally assumed to proceed via cationic Pd^II intermediates which in turn would be highly reactive in the subsequent transmetalation step. Contrary to this belief, we herein report our observation and rationalization of opposing reactivities of ArN₂ ⁺ in Suzuki (=effective) and Stille (=ineffective) cross-couplings in MeOH. Our systematic experimental and computational studies on the roles of transmetalating agent, solvent, base and the likely involvement of in situ formed diazoether derivatives challenge the currently accepted mechanism. Our data suggest that the observed solvent dichotomy is primarily due to Pd^II -methoxy intermediates being formed, which are unreactive with arylstannanes, but highly reactive with arylboronic acids, complementing the Suzuki "Pd-oxy" mechanism with the direct demonstration of transmetalation of a Pd^II -alkoxy complex. Lewis acids were found to circumvent this reactivity divergence, promoting efficient couplings regardless of the employed conditions or coupling partners.

An invocation for computational evaluation of isomerization transforms: cationic skeletal reorganizations as a case study

Covering: 2010 to 2020This review article describes how cationic rearrangement reactions have been used in natural product total synthesis over the last decade as a case study for the many productive ways by which isomerization reactions are enabling for synthesis. This review argues that isomerization reactions in particular are well suited for computational evaluation, as relatively simple calculations can provide significant insight.

Theoretical study on conformational energies of transition metal complexes

Conformational energies are an important chemical property for which a performance assessment of theoretical methods is mandatory. Existing benchmark sets are often limited to biochemical or main group element containing molecules, while organometallic systems are generally less studied. A key problem herein is to routinely generate conformers for these molecules due to their complexity and manifold of possible coordination patterns. In this study we used our recently published CREST protocol [Pracht et al., Phys. Chem. Chem. Phys., 2020, 22, 7169-7192] to generate conformer ensembles for a variety of 40 challenging transition metal containing molecules, which were then used to form a comprehensive conformational energy benchmark set termed TMCONF40. Several low-cost semiempirical, density functional theory (DFT) and force-field methods were compared to high level DLPNO-CCSD(T1) and double-hybrid DFT reference values. Close attention was paid to the energetic ordering of the conformers in the statistical evaluation. With respect to the double-hybrid references, both tested low-cost composite DFT methods produce high Pearson correlation coefficients of rp,mean,B97-3c//B97-3c = 0.922 and rp,mean,PBEh-3c//B97-3c = 0.890, with mean absolute deviations close to or below 1 kcal mol-1. This good performance also holds for a comparison to DLPNO-CCSD(T1) reference energies for a smaller subset termed TMCONF5. Based on DFT geometries, the GFNn-xTB methods yield reasonable Pearson correlation coefficients of rp,mean,GFN1-xTB//B97-3c = 0.617 (MADmean = 2.15 kcal mol-1) and rp,mean,GFN2-xTB//B97-3c = 0.567 (MADmean = 2.68 kcal mol-1), outperforming the widely used PMx methods on the TMCONF40 test set. Employing the low-cost composite DFT method B97-3c on GFN2-xTB geometries yields an slightly improved correlation of rp,mean,B97-3c//GFN2-xTB = 0.632. Furthermore, for 68% of the investigated complexes at least one low-energy conformer was found that is more stable than the respective crystal structure conformation, which signals the importance of conformational studies. General recommendations for the application of the CREST protocol and DFT methods for transition metal conformational energies are given.

Theoretical insight into the origins of chemo- and diastereo-selectivity in the palladium-catalysed (3 + 2) cyclisation of 5-alkenyl thiazolones

The mechanism of the palladium-catalysed (3 + 2) cyclisation of 5-alkenyl thiazolones and VECs has been investigated from a computational perspective, and the origins of unique chemoselectivity and excellent diastereoselectivity have been disclosed.

Flow synthesis kinetics for lomustine, an anti-cancer active pharmaceutical ingredient

An original reaction mechanism and kinetic parameter estimation has been achieved for lomustine, an anti-cancer active pharmaceutical ingredient (API).

On the Mechanism of Cross-Dehydrogenative Couplings between N-aryl Glycinates and Indoles: A Computational Study

Despite the widespread use of cross-dehydrogenative couplings in modern organic synthesis, mechanistic studies are still rare in the literature and those applied to α-amino carbonyl compounds remain virtually unexplored. Herein, the mechanism of Co-catalyzed cross-dehydrogenative couplings of N-aryl glycinates with indoles is described. Density functional theory studies supported the formation of an imine-type intermediate as the more plausible transient electrophilic species. Likewise, key information regarding the role of the N-aryl group and free NH motif within the reaction outcome has been gained, which may set the stage for further developments in this field of expertise.

Quantum-mechanical transition-state model combined with machine learning provides catalyst design features for selective Cr olefin oligomerization

The use of data science tools to provide the emergence of non-trivial chemical features for catalyst design is an important goal in catalysis science. Additionally, there is currently no general strategy for computational homogeneous, molecular catalyst design. Here, we report the unique combination of an experimentally verified DFT-transition-state model with a random forest machine learning model in a campaign to design new molecular Cr phosphine imine (Cr(P,N)) catalysts for selective ethylene oligomerization, specifically to increase 1-octene selectivity. This involved the calculation of 1-hexene : 1-octene transition-state selectivity for 105 (P,N) ligands and the harvesting of 14 descriptors, which were then used to build a random forest regression model. This model showed the emergence of several key design features, such as Cr-N distance, Cr-α distance, and Cr distance out of pocket, which were then used to rapidly design a new generation of Cr(P,N) catalyst ligands that are predicted to give >95% selectivity for 1-octene.