ChloroCat - Unlocking metal-chloride bonds for data-driven stereoselective catalysis

The ability of chemists to invent new reactions is at the heart of our modern society, as novel methods to forge bonds with increased precision and selectivity enable the more efficient preparation of the medicines, agrochemicals, fine chemicals and materials necessary for our world. Catalysis is a powerful tool to devise new reactions and render the existing ones more selective, thus contributing to a more sustainable use of natural resources. The importance of catalytic reactions to create new C-C bonds, for instance, has been recently recognised by the 2005 and 2010 Nobel prizes in Chemistry. Despite these incredible advances in catalytic reactions, control over their selectivity still remains very limited, especially when it comes to assembling molecules that not only have the desired connectivity (i.e. sequence of bonds), but also the required arrangements of atoms in space. This challenge is particularly evident in the preparation of chiral molecules. These are compounds that exist as mirror-image twins of each other, and -despite their similarity- often have wildly different biological properties, because they interact differently with the chiral receptors inside living beings. Chiral molecules are widely employed as pharmaceuticals, food additives, agrochemicals, and fine chemicals. More than half of the medicines currently in use are chiral. However, obtaining them as a single mirror-image is costly, difficult and time-consuming, as it requires the ad-hoc preparation of catalysts often specific for each target, and lengthy optimisation or separation campaigns. The present proposal seeks to address this problem by developing a general strategy for the rapid and cost-effective synthesis of chiral molecules from inexpensive starting materials, enabled by a new paradigm in catalyst design. The key idea is predicated on combining chiral "designer" additives to existing metal-based catalytic systems in order to improve their performance, enhance the reaction rate and impart user-defined selectivity to the resulting products. These new additives will replace the expensive and sensitive silver-based compounds currently used. Automation and data science will be integrated into our workflows, in order to speed up the discovery and optimisation of several C-C-bond forming transformations of vital importance in the pharmaceutical, agrochemical, fragrance and polymer industries, sectors which combined are worth approximately £80 billion to the UK economy. As part of this project, we will establish a highly automated, specialised facility for reaction optimisation that will be open to academic and business users, enabling us to translate our cutting-edge scientific results into industrial innovation over the course of the fellowship.