Development of a novel photocatalytic system for direct deoxyfunctionalization of alcohols involving machine learning

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Project Summary Development of general and efficient methods for functionalization of alcohols is highly warranted due to the ubiquity and prominence of this functional group in natural products. Such methods would allow for late-stage diversification of complex molecules and, consequently, could have a broad impact in natural product synthesis and preparation of relevant pharmaceutical materials. However, owing to the chemical inertness of alcohols, most methods typically require installation of activating groups for functionalization, making them unattractive from an atom- and step-economical perspective. Nonetheless, many advances have been made. In particular, the Barton-McCombie reaction has become an indispensable tool for reductive functionalization of alcohols. Unfortunately, this transformation requires pre- functionalization of the alcohol substrate, employs highly toxic tin reagents, and invokes the use high reaction temperatures or harmful UV light for initiation of radical intermediates. Furthermore, the overall transformation is limited to H-atom incorporation or reductive coupling with alkenes. Lastly, only a few deoxygenation methods exist that are amenable for late-stage and site-selective deoxygenation in complex systems. Moreover, physical organic chemistry tools available to facilitate the selection of a set of conditions or parameters to afford site-selectivity are limited. In this proposal, we will develop a mild and practical photocatalytic deoxygenation of alcohols. Our strategy will focus on solving the inherent limitation of the Barton McCombie reaction by 1) avoiding the use of toxic tin reagents, 2) obviating the need for pre-functionalization of the alcohol substrate, and 3) allowing for modular coupling of formed alkyl radicals via Ni-catalysis. Specific aim 1 explores the development of a novel photoredox-catalyzed deoxygenation of alcohols. In addition, we outline a general protocol for deoxyfunctionalization of alcohols via inception of the alkyl radical intermediate, formed via β-scission, with various radical electrophiles. Moreover, we highlight an innovative method for the direct cross-coupling of alcohols via metallophotoredox catalysis in both racemic and enantioselective fashion. Specific aim 2 addresses the design strategy for implementing physical chemistry techniques such as Machine Learning in order to facilitate optimization and prediction of reaction performance in multi-dimensional chemical space. Also, we outline applying this strategy to identify a set of optimal conditions to confer site-selective functionalization in complex polyols.