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.

Mechanism to model: a physical organic chemistry approach to reaction prediction

The application of mechanistic generalizations is at the core of chemical reaction development and application. These strategies are rooted in physical organic chemistry where mechanistic understandings can be derived from one reaction and applied to explain another. Over time these techniques have evolved from rationalizing observed outcomes to leading experimental design through reaction prediction. In parallel, significant progression in asymmetric organocatalysis has expanded the reach of chiral transfer to new reactions with increased efficiency. However, the complex and diverse catalyst structures applied in this arena have rendered the generalization of asymmetric catalytic processes to be exceptionally challenging. Recognizing this, a portion of our research has been focused on understanding the transferability of chemical observations between similar reactions and exploiting this phenomenon as a platform for prediction. Through these experiences, we have relied on a working knowledge of reaction mechanism to guide the development and application of our models which have been advanced from simple qualitative rules to large statistical models for quantitative predictions. In this feature article, we describe the models acquired to generalize organocatalytic reaction mechanisms and demonstrate their use as a powerful approach for accelerating enantioselective synthesis.

OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

The automated construction of datasets has become increasingly relevant in computational chemistry. While transition-metal catalysis has greatly benefitted from bottom-up or top-down strategies for the curation of organometallic complexes libraries, the field of organocatalysis is mostly dominated by case-by-case studies, with a lack of transferable data-driven tools that facilitate both the exploration of a wider range of catalyst space and the optimization of reaction properties. For these reasons, we introduce OSCAR, a repository of 4000 experimentally derived organocatalysts along with their corresponding building blocks and combinatorially enriched structures. We outline the fragment-based approach used for database generation and showcase the chemical diversity, in terms of functions and molecular properties, covered in OSCAR. The structures and corresponding stereoelectronic properties are publicly available (https://archive.materialscloud.org/record/2022.106) and constitute the starting point to build generative and predictive models for organocatalyst performance.

An overview of the applications of chiral phosphoric acid organocatalysts in enantioselective additions to CO and CN bonds

Since 2004, chiral phosphoric acids (CPAs) have emerged as highyl efficient organocatalysts, providing excellent results in a wide reaction scope. In this review, the applications of CPA for enantioselective additions to CO and CN bonds are covered.

N-Triflylphosphoramides: highly acidic catalysts for asymmetric transformations

N-Triflylphosphoramides (NTPA), have become increasingly popular catalysts in the development of enantioselective transformations as they are stronger Brønsted acids than the corresponding phosphoric acids (PA). Their highly acidic, asymmetric active site can activate difficult, unreactive substrates. In this review, we present an account of asymmetric transformations using this type of catalyst that have been reported in the past ten years and we classify these reactions using the enantio-determining step as the key criterion. This compendium of NTPA-catalysed reactions is organised into the following categories: (1) cycloadditions, (2) electrocyclisations, polyene and related cyclisations, (3) addition reactions to imines, (4) electrophilic aromatic substitutions, (5) addition reactions to carbocations, (6) aldol and related reactions, (7) addition reactions to double bonds, and (8) rearrangements and desymmetrisations. We highlight the use of NTPA in total synthesis and suggest mnemonics which account for their enantioselectivity.

Development of a Computer-Guided Workflow for Catalyst Optimization. Descriptor Validation, Subset Selection, and Training Set Analysis

Modern, enantioselective catalyst development is driven largely by empiricism. Although this approach has fostered the introduction of most of the existing synthetic methods, it is inherently limited by the skill, creativity, and chemical intuition of the practitioner. Herein, we present a complementary approach to catalyst optimization in which statistical methods are used at each stage to streamline development. To construct the optimization informatics workflow, a number of critical components had to be subjected to rigorous validation. First, the critically important molecular descriptors were validated in two case studies to establish the importance of conformation-dependent molecular representations. Next, with a large data set available, it was possible to investigate the amount of data necessary to make predictive models with different modeling methods. Given the commercial availability of many catalyst structures, it was possible to compare models generated with algorithmically selected training sets and commercially available training sets. Finally, the augmentation of limited data sets is demonstrated in a method informed by unsupervised learning to restore the accuracy of the generated models.

Brønsted acid catalysis - the effect of 3,3'-substituents on the structural space and the stabilization of imine/phosphoric acid complexes

BINOL derived chiral phosphoric acids (CPAs) are widely known for their high selectivity. Numerous 3,3'-substituents are used for a variety of stereoselective reactions and theoretical models of their effects are provided. However, experimental data about the structural space of CPA complexes in solution is extremely rare and so far restricted to NMR investigations of binary TRIP/imine complexes featuring two E- and two Z-imine conformations. Therefore, in this paper the structural space of 16 CPA/imine binary complexes is screened and 8 of them are investigated in detail by NMR. For the first time dimers of CPA/imine complexes in solution were experimentally identified, which show an imine position similar to the transition state in transfer hydrogenations. Furthermore, our experimental and computational data revealed an astonishing invariance of the four core structures regardless of the different steric and electronic properties of the 3,3'-substituent. However, a significant variation of E/Z-ratios is observed, demonstrating a strong influence of the 3,3'-substituents on the stabilization of the imine in the complexes. These experimental E/Z-ratios cannot be reproduced by calculations commonly applied for mechanistic studies, despite extensive conformational scans and treatment of the electronic structure at a high level of theory with various implicit solvent corrections. Thus, these first detailed experimental data about the structural space and influence of the 3,3'-substituent on the energetics of CPA/imine complexes can serve as basis to validate and improve theoretical predictive models.