Esther Lete

Axially chiral biaryl scaffolds are privileged structures used in organic synthesis as ligands or chiral catalysts, but also present in natural and synthetic compounds with relevant biological properties. However, the enantioselective synthesis of atropoisomers through C─H activation reactions remains challenging, with few approaches described that rely on de novo construction of a (hetero)arene with the chirality being installed by simultaneous ring formation. We herein disclose a Pd(II)‐catalyzed intramolecular C─H alkenylation of cinnamides for the atroposelective synthesis of 4‐arylquinolones by the chiral–ligand‐controlled generation of a chiral axis. The solvent (HFIP) and the substitution on the N atom of the cinnamide have an important impact on the enantioselectivity obtained. DFT studies have provided insight into the mechanism, showing that the reaction proceeds via prior activation of the alkene, and the enantioselectivity is determined during the β‐hydride elimination step.

Axially chiral biaryl scaffolds are privileged structures used in organic synthesis as ligands or chiral catalysts, but also present in natural and synthetic compounds with relevant biological properties. However, the enantioselective synthesis of atropoisomers through C-H activation reactions remains a challenge, with few approaches described that rely on de novo construction of an (hetero)arene with the chirality being installed by simultaneous ring formation. We herein disclose a Pd(II)-catalysed intramolecular C-H alkenylation of cinnamides for the atroposelective synthesis 4-arylquinolones by the chiral ligand controlled generation of a chiral axis. A chiral quinoline-oxazoline (Quinox) ligand was identified as a superior ligand for this transformation. The key for achievement of excellent enantioselectivity (up to 94% ee) was substitution on the N atom of the cinnamide (metoxycarbonyl group) and the solvent (HFIP). DFT studies have provided insight on the mechanism, showing that the reaction proceeds via prior activation of the alkene, and the enantioselectivity is determined during the beta-hydride elimination step.

Recently, numerous models have been developed to predict drug interactions with molecules. However, integrating diverse data sources and improving the accuracy of biological activity predictions remains a challenge. This work proposes a novel solution that addresses these limitations. Here, we have developed a machine learning model to predict the efficacy of different assays and drugs for diseases related to calmodulin. To achieve this, we have compiled a comprehensive data set including commercialized drugs and experimental compounds targeting CaM complexes. The IFPTML-XGB model achieved high predictive performance, with a test accuracy of 89.1% and a sensitivity of 89.0%, demonstrating its robustness for assay efficacy prediction. We have used the IFPTML modeling technique to identify key factors influencing these activities. We have also synthesized novel riluzole derivatives and have tested them both experimentally and computationally. Biological assays and molecular docking studies have been performed to provide a molecular-scale picture of the molecule-CaM interaction. To validate the model's utility, we tested it on these derivatives. We have found that the model correctly predicts which derivatives were the most bioactive, indicating that this framework can be used to identify promising candidates for new drug formulations. This research not only improves our understanding of CaM-related diseases, but also provides an effective framework for developing new treatments based on predictive modeling.

The cobalt( iii )-catalysed C–H aminocarbonylation of thiophenes and benzo[ b ]thiophenes takes place efficiently under MW irradiation. The introduced N -arylamide group can act as directing group in further iterative C–H functionalization reactions.

A mild and efficient cobalt(III)-catalysed C-H aminocarbonylation procedure for thiophenes and benzo[b]thiophenes, using pyridine and pyrimidine directing groups to control site selectivity has been developed under MW assisted conditions. The reaction is effective with aromatic isocyanates with wide substitution patterns, although aliphatic isocyanates showed less reactivity. The introduced amide group can act as directing group in further iterative C-H functionalization reactions, allowing the diversification of the heterocyclic structures. DFT calculations have shed light on the mechanistic course and reactivity patterns

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.

The Cp*Co(III) C−H allylation of (hetero)arenes with allyl aryl ethers has been developed using an amide as directing group (24 examples). DFT calculations have shed light on the mechanistic course and reactivity pattern, showing that strong electron releasing groups favour the reaction by reducing the activation barrier of the rate‐determining C−H activation step. However, the steric strain can increase the energy of the migratory insertion step to the point of completely preventing the reaction, as in the case of the 3,5‐dimethylbenzamide. The obtained allylated compounds have been transformed into a variety of interesting heterocyclic and carbocyclic structures, such as isoquinolones and isochromanones.