Development of novel enantioselective catalytic reactions

The inverse electron demand Diels-Alder reaction between 2-pyrone-3-carboxylic acid and various vinyl ethers has been performed to attain the respective products with very high diastereoselectivity, which can be used for the synthesis of cycloheixenyl nucleosides (Scheme 1). [diagram]. Scheme 1. Highly diastereoselective Inverse Electron Demand Diels-Alder reaction Primary amino alcohols derived from natural amino acids have been found to be efficient organocatalysts for the cross-aldol reaction between acetone and activated ketones, affording the respective products with high enantioselectivity (Scheme 2). [diagram]. Scheme 2. The enantioselective cross-aldol reaction catalysed by leucinol A practical, highly stereoselective, two-step protocol for the alpha-allylation of aldehydes, starting from allyltrichlorosilanes, has been developed. As a result of the kinetic resolution in each step, virtually enantio- and geometrically pure linear homoallylic alcohols were obtained in high yield from the technical grade aliyltrichlorosilanes by using only 5 mol% of a chiral catalyst (Scheme 3). [diagram]. Scheme 3. The highly enantioselective alpha-allylation of aldehydes

In silico rationalisation of selectivity and reactivity in Pd-catalysed C-H activation reactions.

A computational approach has been developed to automatically generate and analyse the structures of the intermediates of palladium-catalysed carbon-hydrogen (C-H) activation reactions as well as to predict the final products. Implemented as a high-performance computing cluster tool, it has been shown to correctly choose the mechanism and rationalise regioselectivity of chosen examples from open literature reports. The developed methodology is capable of predicting reactivity of various substrates by differentiation between two major mechanisms - proton abstraction and electrophilic aromatic substitution. An attempt has been made to predict new C-H activation reactions. This methodology can also be used for the automated reaction planning, as well as a starting point for microkinetic modelling.EPSRC grant EP/K009494/1 (MK and SL) and the National Research Foundation, Prime Minister’s Office, Singapore under its CREATE programme, project “Cambridge Centre for Carbon Reduction in Chemical Technology” (LC and AL)

Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation

Many computational chemistry and molecular simulation workflows can be expressed as graphs. This abstraction is useful to modularize and potentially reuse existing components, as well as provide parallelization and ease reproducibility. Existing tools represent the computation as a directed acyclic graph (DAG), thus allowing efficient execution by parallelization of concurrent branches. These systems can, however, generally not express cyclic and conditional workflows. We therefore developed Maize, a workflow manager for cyclic and conditional graphs based on the principles of flow-based programming. By running each node of the graph concurrently in separate processes and allowing communication at any time through dedicated inter-node channels, arbitrary graph structures can be executed. We demonstrate the effectiveness of the tool on a dynamic active learning task in computational drug design, involving the use of a small molecule generative model and an associated scoring system

Catalytic asymmetric crotylation of aldehydes: application in total synthesis of (−)‐elisabethadione

A new, highly efficient Lewis base catalyst for a practical enantio- and diastereoselective crotylation of unsaturated aldehydes with E- and Z-crotyltrichlorosilanes has been developed. The method was employed as a key step in a novel asymmetric synthesis of bioactive serrulatane diterpene (À)-elisabethadione. Other strategic reactions for setting up the stereogenic centers included anionic oxy-Cope rearrangement and cationic cyclization. The synthetic route relies on simple, high yielding reactions and avoids use of protecting groups or chiral auxiliaries

Catalytic asymmetric crotylation of aldehydes: application in total synthesis of (−)‐elisabethadione

A new, highly efficient Lewis base catalyst for a practical enantio- and diastereoselective crotylation of unsaturated aldehydes with E- and Z-crotyltrichlorosilanes has been developed. The method was employed as a key step in a novel asymmetric synthesis of bioactive serrulatane diterpene (À)-elisabethadione. Other strategic reactions for setting up the stereogenic centers included anionic oxy-Cope rearrangement and cationic cyclization. The synthetic route relies on simple, high yielding reactions and avoids use of protecting groups or chiral auxiliaries

Asymmetric total synthesis of (-)-erogorgiaene and its C11 epimer and investigation of their antimycobacterial activity

A short, nine-step, highly enantioselective synthesis of (−)-erogorgiaene and its C-11 epimer is reported. The key stereochemistry controlling steps involve catalytic asymmetric crotylation, anionic oxy-Cope rearrangement and cationic cyclisation. (−)-Erogorgiaene exhibited promising antitubercular activity against multidrug-resistant strains of Mycobacterium tuberculosis

In Silico Rationalisation of Selectivity and Reactivity in Pd-Catalysed C-H Activation Reactions

A computational approach has been developed to automatically generate and analyse the structures of the intermediates of palladium catalysed carbon-hydrogen (C-H) activation reactions as well as to predict the final products. Implemented as a high-performance computing cluster tool, it has been shown to correctly choose the mechanism and rationalise regioselectivity of chosen examples from open literature reports. The developed methodology is capable of predicting reactivity of various substrates by differentiation between two major mechanisms - proton abstraction and the electrophilic aromatic substitution. An attempt has been made to predict new C-H activation reactions. This methodology can also be used for the automated reaction planning, as well as a starting point for microkinetic modelling.</p

QSARtuna: an automated QSAR modelling platform for molecular property prediction in drug design

Machine-learning (ML) and Deep-Learning (DL) approaches to predict the molecular properties of small molecules are increasingly deployed within the design-make-test-analyse (DMTA) drug design cycle to predict molecular properties of interest. Despite this uptake, there are only a few automated packages to aid their development and deployment that also support uncertainty estimation, model explainability and other key aspects of model usage. This represents a key unmet need within the field and the large number of molecular representations and algorithms (and associated parameters) means it is non-trivial to robustly optimise, evaluate, reproduce, and deploy models. Here we present QSARtuna, a molecule property prediction modelling pipeline, written in Python and utilising the Optuna, Scikit-learn, RDKit and ChemProp packages, which enables the efficient and automated comparison between molecular representations and machine learning models. The platform was developed considering the increasingly important aspect of model uncertainty quantification and explainability by design. We provide details for our framework and provide illustrative examples to demonstrate the capability of the software when applied to simple molecular property, reaction/reactivity prediction and DNA encoded library enrichment analyses. We hope that the release of QSARtuna will further spur innovation in automatic ML modelling and provide a platform for education of best practises in molecular property modelling. The code to the Qptuna framework is made freely available via GitHub

When yield prediction does not yield prediction: an overview of the current challenges

Machine Learning techniques face significant challenges when predicting advanced chemical properties, such as yield, feasibility of chemical synthesis, and optimal reaction conditions. These challenges stem from the high-dimensional nature of the prediction task and the myriad essential variables involved, ranging from reactants and reagents to catalysts, temperature, and purification processes. Successfully developing a reliable predictive model not only holds potential for optimizing High-Throughput experiments but can also elevate existing retrosynthetic predictive approaches and bolster a plethora of applications within the field. In this review, we systematically evaluate the efficacy of current ML methodologies in chemoinformatics, shedding light on their milestones and inherent limitations. Additionally, a detailed examination of a representative case study provides insights into prevailing issues related to data availability and transferability in the discipline

Organic &amp; Biomolecular Chemistry Direct preparation of thiazoles, imidazoles, imidazopyridines and thiazolidines from alkenes †

A range of heterocycles, namely thiazoles, imidazoles, imidazopyridines, thiazolidines and dimethoxyindoles, have been synthesised directly from alkenes via a two-step ketoidoination/ cyclisation protocol. The alkene starting materials are themselves readily accessible using many different and well-established approaches, and allow access to a variety of heterocycles with excellent yields and regioselectivity