Self-Promoted Glycosylation of Carbamoylated Peptides on Solid Phase

Self-promoted glycosylations with trichloroacetimidate glycosyl donors are demonstrated on solid-phase-anchored peptides orthogonally deprotected and tosylcarbamoylated on the side-chains of cysteine and serine, respectively. The donor scope included glucosyl as well as mannosyl trichloroacetimidates, carrying benzyl, acetyl, or isopropylidene protecting groups. Isopropylidene groups were found to be removed under the acidic conditions used for release of the neoglycopeptides from the solid support, yielding neoglycopeptides with unprotected hydroxyl groups. Glycosylation of a peptide containing a carbamoylated tyrosine was attempted as well, but the desired neoglycopeptide could not be synthesized due to thermal instability of the carbamate.

Substrate specific closed-loop optimization of carbohydrate protective group chemistry using Bayesian optimization and transfer learning

A new way of performing reaction optimization within carbohydrate chemistry is presented. This is done by performing closed-loop optimization of regioselective benzoylation of unprotected glycosides using Bayesian optimization. Both 6-O-monobenzoylations and 3,6-O-dibenzoylations of three different monosaccharides are optimized. A novel transfer learning approach, where data from previous optimizations of different substrates is used to speed up the optimizations, has also been developed. The optimal conditions found by the Bayesian optimization algorithm provide new insight into substrate specificity, as the conditions found are significantly different. In most cases, the optimal conditions include Et₃N and benzoic anhydride, a new reagent combination for these reactions, discovered by the algorithm, demonstrating the power of this concept to widen the chemical space. Further, the developed procedures include ambient conditions and short reaction times.