Automated Synthesis, Quantum Chemistry and NMR in the Identification of Structurally Related Macrolide Natural Products

Synthetic organic chemistry has a huge industrial importance and for many years, chemists have been, and are still, constantly in search for more efficient and robust methods for the construction of organic molecules to meet the high demand. Automation is one strand of a digital chemistry future, which, in combination with machine learning and computer assisted retrosynthesis has the potential to dramatically change how we create molecules. Over the last 10 years, the Aggarwal group have created new reactions and strategies based on boron homologations that is now ripe for transferring to an automation platform. We have shown that combining this homologation chemistry with state-of-the-art quantum chemical calculations and NMR spectroscopy provides a synergy that allows us to design, synthesise and elucidate the structure of 3-dimensionally complex natural products, such as baulamycin A.

Our goal now is to address the structure of an even more complex molecule, the antifungal marine natural product caylobolide A, and to use the power of automation to aid in its synthesis. Only 5 of the 12 stereocentres of caylobolide A have been assigned in the literature using Mosher's ester analysis, with the remainder not being resolvable by this method. Key structural features of the molecule are 1,3- and 1,5-related hydroxyl groups. We have developed methodology to create any isomer of such motifs, solving a long-standing problem in asymmetric synthesis.We have also established NMR+computation procedures that allow us to probe the stereochemistry of flexible compounds, such as caylobolide A, based on quantum chemical (or machine learning) prediction of NMR parameters such as proton and carbon chemical shifts, 3JHH, 3JCH and nuclear Overhauser enhancements. These work very well for -OH substituted stereocentres that are close to each other, but are less effective when the stereocentres are a long distance apart (as in caylobolide A) and we may need to explore the application of NMR techniques that are sensitive to longer-range interactions, such as residual anisotropic NMR parameters.

1. PEOPLE: We will train students with skills that are in demand across a spectrum of industries from pharma/biotech to materials, as well as in academia, law and publishing. The enhanced experience they receive - through interactive brainstorming, problem and dragons' den type business sessions - will equip them with confidence in their own abilities and fast-track their leadership skills. 100% Employment of students from the previous CDT in Chemical Synthesis is indicative of the high demand for the skills we provide, but as start-ups and SMEs become increasingly important in the healthcare, medicine and energy sectors, training in IP, entrepreneurship and commercialisation will stimulate our students to explore their own ventures. Automation and machine learning are set to transform the workplace in the next 20 years, and our students will be in the vanguard of those primed to make best use of these shifts in work patterns. Our graduates will have an open and entrepreneurial mindset, willing to seek solution to problems that cross disciplines and require non-traditional approaches to scientific challenges.

2. ECONOMY: Built on the country's long history of scientific ingenuity and creativity, the >£50bn turnover and annual trade surplus of £5 bn makes the British chemical sector one of the most important creators of wealth for the national economy. Our proposal to integrate training in chemical synthesis with emerging fields such as automation/AI/ML will ensure that the UK maintains this position of economic strength in the face of rapidly developing competition. With the field of drug development desperately looking for innovative new directions, we will disseminate, through our proposed extensive industrial stakeholders, smarter and more efficient ways of designing and implementing molecular synthesis using automation, machine learning and virtual reality interfaces. This will give the UK the chance to take a world-leading position in establishing how molecules may be made more rapidly and economically, how compound libraries may be made broader in scope and accessed more efficiently, and how processes may be optimized more quickly and to a higher standard of resilience. Chemical science underpins an estimated 21% of the economy (>£25bn sales; 6 million people), so these innovations have the potential for far-reaching transformative impact.

3. SCIENCE: The science emerging from our CDT will continue to be at the highest academic level by international standards, as judged by an outstanding publication record. Incorporating automation, machine learning, and virtual reality into the standard toolkit of chemical synthesis would initiate a fundamental change in the way molecules are made. Automated methods for making limited classes of molecules (eg peptides) have transformed related biological fields, and extending those techniques to allow a wide range of small molecules to be synthesized will stimulate not only chemistry but also related pivotal fields in the bio- and materials sciences. Synthesis of the molecular starting points is often the rate-limiting step in innovation. Removing this hurdle will allow selection of molecules according to optimal function, not ease of synthesis, and will accelerate scientific progress in many sectors.

4. SOCIETY: Health benefits will emerge from the ability of both academia and the pharmaceutical industry to generate drug targets more rapidly and innovatively. Optimisation of processes opens the way for advances in energy efficiency and resource utilization by avoiding non-renewable, environmentally damaging, or economically volatile feedstocks. The societal impact of automation will extend more widely to the freeing of time to allow more creative working and also recreational pastimes. We thus aim to be among the pioneers in a new automation-led working model, and our students will be trained to think through the broader consequences of automation for society as a whole