A broadly applicable quantitative relative reactivity model for nucleophilic aromatic substitution (SNAr) using simple descriptors

Unraveling the influence mechanisms of different substituents on the chemical activity of N-heterocyclic phosphines via theoretical calculations

CONTEXT

N-Heterocyclic phosphines (NHP-H) represent a distinctive class of phosphorus-containing heterocycles characterized by "polarity-inverted" P-H bonds. These unique bonds facilitate a wide array of P-H reactions, rendering NHP-H compounds promising candidates for applications in organocatalysis. Although significant advancements have been made in NHP-H research, the experimental quantification of their reactivity parameters poses considerable challenges due to their high reactivity. Furthermore, the influence of various substituents on the chemical activity of NHP-H compounds remains insufficiently understood. This study examines eight NHP-H compounds with varying substituents. The findings indicate that electron-donating substituents decrease the P-H bond order, increase the negative charge on the phosphorus atom, and enhance nucleophilicity. Conversely, electron-withdrawing substituents exhibit opposite effects. Furthermore, substituents influence the local electron attachment energy of the phosphorus atom, thereby affecting reactivity in proton-transfer reactions. According to conceptual density functional theory, electron-donating substituents are associated with lower electrophilicity and higher nucleophilicity indices, whereas electron-withdrawing substituents demonstrate the opposite trend. Charge-transfer spectra suggest that electron-donating substituents reduce the excitation energy of NHP-H, thereby increasing its reactivity. Additionally, IRI analysis indicates that electron-donating substituents weaken the P-H bond, while electron-withdrawing substituents strengthen it, along with alterations in other intramolecular interactions.

METHODS

The study utilized the M06-2X functional in conjunction with the def2-TZVP basis set within the SMD model, employing acetonitrile as the solvent, to perform structural optimization and frequency analysis of NHP-H compounds. Computational analyses were conducted using Gaussian 09 software, with 30 excited states calculated for each compound. Multiwfn software facilitated the determination of atomic dipole moment-corrected Hirshfeld population, local electron attachment energy, the Interaction Region Indicator, and charge-transfer spectrum, which were subsequently visualized using VMD 1.9.3. Additionally, GaussView 6.0.16 software was employed to generate three-dimensional molecular configurations and prepare input files.

A mechanistic continuum of nucleophilic aromatic substitution reactions with azole nucleophiles

Nucleophilic aromatic substitution (SNAr) is a broadly used method for generating structural complexity in pharmaceuticals. Although SNAr reactions were long assumed to be stepwise, recent kinetic isotope effect (KIE) studies have shown that many SNAr reactions are actually concerted. However, it remains unclear how variations in substrate structure affect whether a reaction is stepwise, concerted, or borderline. In this paper, we show that reactions between indole and moderately electron-deficient aryl fluorides proceed by a borderline mechanism and are subject to general base catalysis. These findings are consistent with density functional theory (DFT) calculations, which also predict that borderline mechanisms are operative for a broad range of industrially relevant SNAr reactions involving azole nucleophiles. The predicted transition structures vary smoothly independent of the mechanism, suggesting that these SNAr reactions exist on a mechanistic continuum. The findings of widespread general base catalysis and a mechanistic continuum will guide future efforts to devise general models of SNAr reactivity.

Computational tools for the prediction of site- and regioselectivity of organic reactions

The regio- and site-selectivity of organic reactions is one of the most important aspects when it comes to synthesis planning. Due to that, massive research efforts were invested into computational models for regio- and site-selectivity prediction, and the introduction of machine learning to the chemical sciences within the past decade has added a whole new dimension to these endeavors. This review article walks through the currently available predictive tools for regio- and site-selectivity with a particular focus on machine learning models while being organized along the individual reaction classes of organic chemistry. Respective featurization techniques and model architectures are described and compared to each other; applications of the tools to critical real-world examples are highlighted. This paper aims to serve as an overview of the field's status quo for both the intended users of the tools, that is synthetic chemists, as well as for developers to find potential new research avenues.

Copper-Catalyzed Regioselective and Enantioselective Hydropyridylation of Dienes for the Synthesis of Chiral Diaryl Compounds via Concerted Nucleophilic Aromatic Substitution

The synthesis of chiral 1,1-diaryl compounds, particularly those containing a pyridine moiety, is of significant interest due to their pharmaceutical applications. Here, we report the development of a copper-catalyzed enantioselective 1,4-hydropyridylation of conjugated dienes. Utilizing 2-fluoropyridine as the electrophile, CuOAc, and the chiral ligand Tol-BINAP, we optimized reaction conditions to achieve the desired chiral 1,1-diaryl products containing both a pyridine and a cis-crotyl group. Mechanistic studies and DFT calculations revealed that the 1,2-hydrocupration step is enantio-determining, and the concerted nucleophilic aromatic substitution proceeds via six-membered cyclic transition states.

Nucleophilic Amination of Aryl Halides with an Azanide Surrogate

We report the development of an azanide (-NH2) surrogate which enables the facile conversion of electron-deficient (hetero)aryl halides into primary N-aryl amines under transition-metal-free conditions. The designed amidine reagent is easy to prepare, bench stable, and undergoes facile N-arylation under basic conditions at 40 °C. Intermediate N-aryl amidines are readily cleaved to form N-aryl amines in situ through hydrolysis or base-promoted elimination. The developed surrogate is a safer and more selective alternative to existing anionic N-nucleophiles, such as alkali metal amides or azide salts.

Quantitative Reactivity Models for Oxidative Addition to L2Pd(0): Additional Substrate Classes, Solvents, and Mechanistic Insights

Quantitative molecular structure-reactivity models are useful for generating predictions to guide synthesis design, and in formulating and testing mechanistic hypotheses. We report an expanded multivariate linear regression (MLR) model for the rate of (hetero)aryl (pseudo)halide oxidative addition to L2Pd(0), here exemplified by Pd(PCy3)2. This builds on a prior model from our group, with additional substrate classes (aryl chlorides and iodides) and reaction solvents (THF, toluene, THF/DMF mixture). Overall solvent effects across the entire substrate set are minimal under these conditions, enabling a unified MLR model without introduction of new molecular descriptors beyond the original five. Examining the mechanistic origin of the two molecular electrostatic potential (ESP) descriptors led to generation of a simpler, four descriptor model that is suitable for aryl halides, but not for 2-halopyridines. Using this model we identified a mechanistic outlier, 2-pyridyl triflate, which undergoes a nucleophilic displacement oxidative addition that does not involve the adjacent nitrogen atom. Finally, we discuss the relationship between C-X bond strength and oxidative addition rates, and compare the intrinsic bond strength index (IBSI) to bond dissociation enthalpy (BDE) as a bond strength descriptor.

Synthesis and Rearrangement of New 1,3-Diamino-2,7-naphthyridines and 1-Amino-3-oxo-2,7-naphthyridines

Herein we describe the synthesis and rearrangement of 1,3-diamino-2,7-naphthyridines and 1-amino-3-oxo-2,7-naphthyridines. In the case of 1,3-diamino-2,7-naphthyridines, it was found that the rearrangement reaction was influenced by both the substituent at the 7th position of the 2,7-naphthyridine ring and by the nature of the cyclic amine at the 1st position. The influence was mainly steric. The reaction of 1-amino-3-oxo-2,7-naphthyridines with amines was studied for the first time. It was revealed that for these substrates, the rearrangement occurs faster and without any influence of the alkyl and cyclic amine groups. We also observed the nucleophilic addition of the amine to the carbonyl group of the rearranged product with the formation of a Schiff base. The calculation of the ESP charges on these substrates indicates a considerable increase in the positive charge on the cyano group that suffers the nucleophilic attack during the rearrangement process, possibly explaining its increased tendency to react and to have a higher reaction velocity.

Halogenated Phenylpyridines Possessing Chemo-Selectivity for Diverse Molecular Architectures

Pentafluoropyridine was used as a molecular building block for the installation of aryl bromides, affording a series of multisubstituted halogenated arenes. This operationally simplistic methodology offers precise regioselectivity, ease of scalability, and high purity. 19F Nuclear magnetic resonance (NMR) served as a key diagnostic tool for structural characterization, given the sensitivity with various aryl bromine substitutions on the fluorinated pyridine ring. Furthermore, molecular modeling simulations offered insight into this new class of halogenated phenylpyridines and their unique electronic and reactive properties. This study also demonstrates examples of efficient chemo-selectivity upon either metal-catalyzed aryl-aryl coupling or nucleophilic aromatic substitution of the aryl bromide or fluorinated pyridine scaffold, respectively. A diverse pool of polyarylene structures with high degree of complexity, functionalized linear polymers, and controlled network architectures were achieved from this simple methodology.

Direct C-H Hydroxylation of N-Heteroarenes and Benzenes via Base-Catalyzed Halogen Transfer

Hydroxylated (hetero)arenes are valued in many industries as both key constituents of end products and diversifiable synthetic building blocks. Accordingly, the development of reactions that complement and address the limitations of existing methods for the introduction of aromatic hydroxyl groups is an important goal. To this end, we apply base-catalyzed halogen transfer (X-transfer) to enable the direct C-H hydroxylation of mildly acidic N-heteroarenes and benzenes. This protocol employs an alkoxide base to catalyze X-transfer from sacrificial 2-halothiophene oxidants to aryl substrates, forming SNAr-active intermediates that undergo nucleophilic hydroxylation. Key to this process is the use of 2-phenylethanol as an inexpensive hydroxide surrogate that, after aromatic substitution and rapid elimination, provides the hydroxylated arene and styrene byproduct. Use of simple 2-halothiophenes allows for C-H hydroxylation of 6-membered N-heteroarenes and 1,3-azole derivatives, while a rationally designed 2-halobenzothiophene oxidant extends the scope to electron-deficient benzene substrates. Mechanistic studies indicate that aromatic X-transfer is reversible, suggesting that the deprotonation, halogenation, and substitution steps operate in synergy, manifesting in unique selectivity trends that are not necessarily dependent on the most acidic aryl position. The utility of this method is further demonstrated through streamlined target molecule syntheses, examples of regioselectivity that contrast alternative C-H hydroxylation methods, and the scalable recycling of the thiophene oxidants.

Dataset Design for Building Models of Chemical Reactivity

Models can codify our understanding of chemical reactivity and serve a useful purpose in the development of new synthetic processes via, for example, evaluating hypothetical reaction conditions or in silico substrate tolerance. Perhaps the most determining factor is the composition of the training data and whether it is sufficient to train a model that can make accurate predictions over the full domain of interest. Here, we discuss the design of reaction datasets in ways that are conducive to data-driven modeling, emphasizing the idea that training set diversity and model generalizability rely on the choice of molecular or reaction representation. We additionally discuss the experimental constraints associated with generating common types of chemistry datasets and how these considerations should influence dataset design and model building.

Insights into structural, spectroscopic, and hydrogen bonding interaction patterns of nicotinamide-oxalic acid (form I) salt by using experimental and theoretical approaches

In the present work, nicotinamide-oxalic acid (NIC-OXA, form I) salt was crystallized by slow evaporation of an aqueous solution. To understand the molecular structure and spectroscopic properties of NIC after co-crystallization with OXA, experimental infrared (IR), Raman spectroscopic signatures, X-ray powder diffraction (XRPD), and differential scanning calorimetry (DSC) techniques were used to characterize and validate the salt. The density functional theory (DFT) methodology was adopted to perform all theoretical calculations by using the B3LYP/6-311++G (d, p) functional/basis set. The experimental geometrical parameters were matched in good correlation with the theoretical parameters of the dimer than the monomer, due to the fact of covering the nearest hydrogen bonding interactions present in the crystal structure of the salt. The IR and Raman spectra of the dimer showed the red (downward) shifting and broadening of bands among (N15-H16), (N38-H39), and (C13=O14) bonds of NIC and (C26=O24), (C3=O1), and (C26=O25) groups of OXA, hence involved in the formation of NIC-OXA salt. The atoms in molecules (AIM) analysis revealed that (N8-H9···O24) is the strongest (conventional) intermolecular hydrogen bonding interaction in the dimer model of salt with the maximum value of interaction energy -12.1 kcal mol-1. Furthermore, the natural bond orbital (NBO) analysis of the Fock matrix showed that in the dimer model, the (N8-H9···O24) bond is responsible for the stabilization of the salt with an energy value of 13.44 kcal mol-1. The frontier molecular orbitals (FMOs) analysis showed that NIC-OXA (form I) salt is more reactive and less stable than NIC, as the energy gap of NIC-OXA (form I) salt is less than that of NIC. The global and local reactivity descriptor parameters were calculated for the monomer and dimer models of the salt. The electrophilic, nucleophilic, and neutral reactive sites of NIC, OXA, monomer, and dimer models of salt were visualized by plotting the molecular electrostatic potential (MESP) surface. The study provides valuable insights into combining both experimental and theoretical results that could define the physicochemical properties of molecules.

Rapid planning and analysis of high-throughput experiment arrays for reaction discovery

High-throughput experimentation (HTE) is an increasingly important tool in reaction discovery. While the hardware for running HTE in the chemical laboratory has evolved significantly in recent years, there remains a need for software solutions to navigate data-rich experiments. Here we have developed phactor™, a software that facilitates the performance and analysis of HTE in a chemical laboratory. phactor™ allows experimentalists to rapidly design arrays of chemical reactions or direct-to-biology experiments in 24, 96, 384, or 1,536 wellplates. Users can access online reagent data, such as a chemical inventory, to virtually populate wells with experiments and produce instructions to perform the reaction array manually, or with the assistance of a liquid handling robot. After completion of the reaction array, analytical results can be uploaded for facile evaluation, and to guide the next series of experiments. All chemical data, metadata, and results are stored in machine-readable formats that are readily translatable to various software. We also demonstrate the use of phactor™ in the discovery of several chemistries, including the identification of a low micromolar inhibitor of the SARS-CoV-2 main protease. Furthermore, phactor™ has been made available for free academic use in 24- and 96-well formats via an online interface.

Synthesis, molecular docking, and antioxidant activity of new fluorescent tetrafluoroterphenyl analogues

Nucleophilic aromatic substitution (S_N Ar) chemistry has been applied to develop many functionalized pentafluorobenzene derivatives. Those compounds are highly specific at the para position of the fluorinated ring. Therefore, they are typical adducts for the preparation of antioxidant molecular systems. In this context, we report the use of S_N Ar chemistry as a suitable and simple approach for the synthesis of fluorescent antioxidant perfluorinated materials bearing ether bonds in various para-substituted alkoxy chains and with high purity and excellent yields. The fluoroterphenyl core was prepared via alkylation, Cu(I)-assisted decarboxylation, and cross-coupling using the potassium salt of fluorobenzoate, followed by the reaction with different alcohols. The structures of the synthesized fluoroterphenyl adducts were investigated using FT-IR, ¹ H NMR, ¹³ C NMR, and ¹⁹ F NMR spectroscopy. The emission spectra and absorption spectra showed solvatochromism. The newly prepared tetrafluoroterphenyl analogues were investigated by antioxidant examination using the 2,2-diphenyl-1-picrylhydrazyl assay. Results were compared with ascorbic acid and butylated hydroxytoluene as references, and revealed that the tetrafluoroterphenyl analogues containing a decyl chain had the highest activity, with an IC₅₀ value of 22.36 ± 0.19 g/ml. The produced tetrafluoroterphenyl analogues were used in molecular docking strategies with a Protein Data Bank protein ID 5IKQ. The antioxidant investigations and docking results were convergent.

Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where predictive chemistry models hold the potential to accelerate the deployment, development, and discovery of organic reactions and advance synthetic chemistry.