Chiral Brønsted Acid-Catalyzed Enantioselective α-Amidoalkylation Reactions: A Joint Experimental and Predictive Study

MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products

The enantioselective Brønsted acid-catalyzed α-amidoalkylation reaction is a useful procedure is for the production of new drugs and natural products. In this context, Chiral Phosphoric Acid (CPA) catalysts are versatile catalysts for this type of reactions. The selection and design of new CPA catalysts for different enantioselective reactions has a dual interest because new CPA catalysts (tools) and chiral drugs or materials (products) can be obtained. However, this process is difficult and time consuming if approached from an experimental trial and error perspective. In this work, an Heuristic Perturbation-Theory and Machine Learning (HPTML) algorithm was used to seek a predictive model for CPA catalysts performance in terms of enantioselectivity in α-amidoalkylation reactions with R2 = 0.96 overall for training and validation series. It involved a Monte Carlo sampling of > 100,000 pairs of query and reference reactions. In addition, the computational and experimental investigation of a new set of intermolecular α-amidoalkylation reactions using BINOL-derived N-triflylphosphoramides as CPA catalysts is reported as a case of study. The model was implemented in a web server called MATEO: InterMolecular Amidoalkylation Theoretical Enantioselectivity Optimization, available online at: https://cptmltool.rnasa-imedir.com/CPTMLTools-Web/mateo . This new user-friendly online computational tool would enable sustainable optimization of reaction conditions that could lead to the design of new CPA catalysts along with new organic synthesis products.

Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors

Catalyst optimization processes typically rely on inductive and qualitative assumptions of chemists based on screening data. While machine learning models using molecular properties or calculated 3D structures enable quantitative data evaluation, costly quantum chemical calculations are often required. In contrast, readily available binary fingerprint descriptors are time- and cost-efficient, but their predictive performance remains insufficient. Here, we describe a machine learning model based on fragment descriptors, which are fine-tuned for asymmetric catalysis and represent cyclic or polyaromatic hydrocarbons, enabling robust and efficient virtual screening. Using training data with only moderate selectivities, we designed theoretically and validated experimentally new catalysts showing higher selectivities in a challenging asymmetric tetrahydropyran synthesis.

Enantioselective Construction of Tetrasubstituted Carbon Stereocenters via Chiral Phosphoric Acid-Catalyzed Friedel-Craft Alkylation of Indoles with 5-Substituted Hydroxybutyrolactams

The first intermolecular organocatalytic enantioselective addition of indoles to prochiral 5-membered cyclic N-acyliminium ions, generated from 5-hydroxy-α,β-unsaturated pyrrolidin-2-ones, is reported hereinafter. The reaction proceeds smoothly with a range of 5-hydroxy-5-substituted-α,β-unsaturated pyrrolidin-2-ones and indoles using BINOL-derived phosphoric acid catalyst to afford α,β-unsaturated lactams embedding a tetrasubstituted stereogenic center in high yields and enantioselectivities.

1-Aminoalkylphosphonium Derivatives: Smart Synthetic Equivalents of N-Acyliminium-Type Cations, and Maybe Something More: A Review

N-acyliminium-type cations are examples of highly reactive intermediates that are willingly used in organic synthesis in intra- or intermolecular α-amidoalkylation reactions. They are usually generated in situ from their corresponding precursors in the presence of acidic catalysts (Brønsted or Lewis acids). In this context, 1-aminoalkyltriarylphosphonium derivatives deserve particular attention. The positively charged phosphonium moiety located in the immediate vicinity of the N-acyl group significantly facilitates C_α-P⁺ bond breaking, even without the use of catalyst. Moreover, minor structural modifications of 1-aminoalkyltriarylphosphonium derivatives make it possible to modulate their reactivity in a simple way. Therefore, these types of compounds can be considered as smart synthetic equivalents of N-acyliminium-type cations. This review intends to familiarize a wide audience with the unique properties of 1-aminoalkyltriarylphosphonium derivatives and encourage their wider use in organic synthesis. Hence, the most important methods for the preparation of 1-aminoalkyltriarylphosphonium salts, as well as the area of their potential synthetic utilization, are demonstrated. In particular, the structure–reactivity correlations for the phosphonium salts are discussed. It was shown that 1-aminoalkyltriarylphosphonium salts are not only an interesting alternative to other α-amidoalkylating agents but also can be used in such important transformations as the Wittig reaction or heterocyclizations. Finally, the prospects and limitations of their further applications in synthesis and medicinal chemistry were considered.

Amide-Type Substrates in the Synthesis of N-Protected 1-Aminomethylphosphonium Salts

Herein we describe the development and optimization of a two-step procedure for the synthesis of N-protected 1-aminomethylphosphonium salts from imides, amides, carbamates, or lactams. Our “step-by-step” methodology involves the transformation of amide-type substrates to the corresponding hydroxymethyl derivatives, followed by the substitution of the hydroxyl group with a phosphonium moiety. The first step of the described synthesis was conducted based on well-known protocols for hydroxymethylation with formaldehyde or paraformaldehyde. In turn, the second (substitution) stage required optimization studies. In general, reactions of amide, carbamate, and lactam derivatives occurred at a temperature of 70 °C in a relatively short time (1 h). On the other hand, N-hydroxymethylimides reacted with triarylphosphonium salts at a much higher temperature (135 °C) and over longer reaction times (as much as 30 h). However, the proposed strategy is very efficient, especially when NaBr is used as a catalyst. Moreover, a simple work-up procedure involving only crystallization afforded good to excellent yields (up to 99%).

Quantitative Structure-Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future

The dawn of the 21st century has brought with it a surge of research related to computer-guided approaches to catalyst design. In the past two decades, chemoinformatics, the application of informatics to solve problems in chemistry, has increasingly influenced prediction of activity and mechanistic investigations of organic reactions. The advent of advanced statistical and machine learning methods, as well as dramatic increases in computational speed and memory, has contributed to this emerging field of study. This review summarizes strategies to employ quantitative structure-selectivity relationships (QSSR) in asymmetric catalytic reactions. The coverage is structured by initially introducing the basic features of these methods. Subsequent topics are discussed according to increasing complexity of molecular representations. As the most applied subfield of QSSR in enantioselective catalysis, the application of local parametrization approaches and linear free energy relationships (LFERs) along with multivariate modeling techniques is described first. This section is followed by a description of global parametrization methods, the first of which is continuous chirality measures (CCM) because it is a single parameter derived from the global structure of a molecule. Chirality codes, global, multivariate descriptors, are then introduced followed by molecular interaction fields (MIFs), a global descriptor class that typically has the highest dimensionality. To highlight the current reach of QSSR in enantioselective transformations, a comprehensive collection of examples is presented. When combined with traditional experimental approaches, chemoinformatics holds great promise to predict new catalyst structures, rationalize mechanistic behavior, and profoundly change the way chemists discover and optimize reactions.

MCDCalc: Markov Chain Molecular Descriptors Calculator for Medicinal Chemistry

AIMS

Cheminformatics models are able to predict different outputs (activity, property, chemical reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis, metabolic reactions, nanoparticles, etc.).

BACKGROUND

Cheminformatics models are able to predict different outputs (activity, property, chemical reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis, metabolic reactions, nanoparticles, etc.).

OBJECTIVE

Cheminformatics prediction of complex catalytic enantioselective reactions is a major goal in organic synthesis research and chemical industry. Markov Chain Molecular Descriptors (MCDs) have been largely used to solve Cheminformatics problems. There are different types of Markov chain descriptors such as Markov-Shannon entropies (Shk), Markov Means (Mk), Markov Moments (πk), etc. However, there are other possible MCDs that have not been used before. In addition, the calculation of MCDs is done very often using specific software not always available for general users and there is not an R library public available for the calculation of MCDs. This fact, limits the availability of MCMDbased Cheminformatics procedures.

METHODS

We studied the enantiomeric excess ee(%)[Rcat] for 324 α-amidoalkylation reactions. These reactions have a complex mechanism depending on various factors. The model includes MCDs of the substrate, solvent, chiral catalyst, product along with values of time of reaction, temperature, load of catalyst, etc. We tested several Machine Learning regression algorithms. The Random Forest regression model has R2 > 0.90 in training and test. Secondly, the biological activity of 5644 compounds against colorectal cancer was studied.

RESULTS

We developed very interesting model able to predict with Specificity and Sensitivity 70-82% the cases of preclinical assays in both training and validation series.

CONCLUSION

The work shows the potential of the new tool for computational studies in organic and medicinal chemistry.

1-(N-Acylamino)alkyltriarylphosphonium Salts with Weakened Cα-P⁺ Bond Strength-Synthetic Applications

The α-amidoalkylating properties of 1-(N-acylamino)alkyltriarylphosphonium salts with weakened Cα-P⁺ bond strength are discussed and examined. It is demonstrated that such type of phosphonium salts reacts smoothly with a diverse array of carbon- and heteroatom-based nucleophiles, including 1-morpholinocyclohexene, 1,3-dicarbonyl compounds, benzotriazole sodium salt, p-toluenesulfinate sodium salt, benzylamine, triarylphosphines, and other P-nucleophiles. Reactions are conducted at room temperature, in a short time (5⁻15 min) and mostly without catalysts. Simple work-up procedures result in good or very good yields of products. The structures of known compounds were established by spectroscopic methods and all new compounds have been fully characterized using ¹H-, 13C-, 31P-NMR, IR spectroscopy, and high-resolution mass spectrometry. Mechanistic aspects of described transformations are also performed and discussed. It was demonstrated that unique properties make 1-(N-acylamino)alkyl-triarylphosphonium salts with weakened Cα-P⁺ bond strength interesting building blocks with great potential, especially in α-amidoalkylation reactions.

Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies

Machine learning (ML) algorithms are gaining importance in the processing of chemical information and modeling of chemical reactivity problems. In this work, we have developed a perturbation-theory and machine learning (PTML) model combining perturbation theory (PT) and ML algorithms for predicting the yield of a given reaction. For this purpose, we have selected Parham cyclization, which is a general and powerful tool for the synthesis of heterocyclic and carbocyclic compounds. This reaction has both structural (substitution pattern on the substrate, internal electrophile, ring size, etc.) and operational variables (organolithium reagent, solvent, temperature, time, etc.), so predicting the effect of changes on substrate design (internal elelctrophile, halide, etc.) or reaction conditions on the yield is an important task that could help to optimize the reaction design. The PTML model developed uses PT operators to account for perturbations under experimental conditions and/or structural variables of all the molecules involved in a query reaction, compared to a reaction of reference. Thus, a dataset of >100 reactions has been collected for different substrates and internal electrophiles, under different reaction conditions, with a wide range of yields (0-98%). The best PTML model found using General Linear Regression (GLR) has R = 0.88 in training and R = 0.83 in external validation series for 10 000 pairs of query and reference reactions. The PTML model has a final R = 0.95 for all reactions using multiple reactions of reference. We also report a comparative study of linear versus nonlinear PTML models based on artificial neural network (ANN) algorithms. PTML-ANN models (LNN, MLP, RBF) with R ≈ 0.1-0.8 do not outperform the first PMTL model. This result confirms the validity of the linearity of the model. Next, we carried out an experimental and theoretical study of nonreported Parham reactions to illustrate the practical use of the PTML model. A 500 000-point simulation and a Hammett analysis of the reactivity space of Parham reactions are also reported.

1-Imidoalkylphosphonium salts with modulated Cα-P+ bond strength: synthesis and application as new active α-imidoalkylating agents

An effective synthesis of the hitherto unknown 1-imidoalkylphosphonium salts has been developed in the reported study. The crucial step in the method included the decarboxylative α-methoxylation of N-phthaloyl- or N-succinylamino acids to the corresponding N-(1-methoxyalkyl)imides, followed by the displacement of the methoxy group by the triarylphosphonium group through melting of the imide derivative with triarylphosphonium tetrafluoroborate. The imidoalkylating properties of the obtained 1-imidoalkylphosphonium salts were tested using the Tscherniac-Einhorn-type reaction with aromatic hydrocarbons as a model reaction. It was found that the C_α-P⁺ bond strength can be considerably reduced and the imidoalkylation of arenes can be markedly facilitated using 1-imidoalkylphosphonium salts derived from triarylphosphines with electron-withdrawing substituents such as tris(m-chorophenyl)phosphine, tris(p-chlorophenyl)phosphine and tris[p-(trifluoromethyl)phenyl]phosphine. Microwave irradiation also considerably facilitates the cleavage of the highly polar C_α-P⁺ bond.

Phenolic Activation in Chiral Brønsted Acid-Catalyzed Intramolecular α-Amidoalkylation Reactions for the Synthesis of Fused Isoquinolines

An organolithium addition-intramolecular α-amidoalkylation sequence on N-phenethylimides has been developed for the synthesis of fused tetrahydroisoquinoline systems using 1,1'-bi-2-naphthol (binol)-derived Brønsted acids. This transformation is the first in which activated benzene derivatives are used as internal nucleophiles, instead of electron-rich heteroaromatics, generating a quaternary stereocenter. Phenolic substitution on the aromatic ring of the phenethylamino moiety and the use of binol-derived N-triflylphosphoramides as catalysts are determinants to achieve reasonable levels of enantioselection, that is, up to 75% enantiomeric excess, in the α-amidoalkylation step. The procedure is complementary to the intermolecular α-amidoalkylation process, as opposite enantiomers are formed, and to the Pictet-Spengler cyclization, which allows the formation of tertiary stereocenters.

Chiral Brønsted Acid-Catalyzed Enantioselective α-Amidoalkylation Reactions: A Joint Experimental and Predictive Study

Enamides with a free NH group have been evaluated as nucleophiles in chiral Brønsted acid-catalyzed enantioselective α-amidoalkylation reactions of bicyclic hydroxylactams for the generation of quaternary stereocenters. A quantitative structure-reactivity relationship (QSRR) method has been developed to find a useful tool to rationalize the enantioselectivity in this and related processes and to orient the catalyst choice. This correlative perturbation theory (PT)-QSRR approach has been used to predict the effect of the structure of the substrate, nucleophile, and catalyst, as well as the experimental conditions, on the enantioselectivity. In this way, trends to improve the experimental results could be found without engaging in a long-term empirical investigation.