Electrochemical Synthesis of S-Aryl Dibenzothiophenium Triflates as Precursors for Selective Nucleophilic Aromatic (Radio)fluorination.

A novel electrosynthetic approach to aryl dibenzothiophenium salts, including the direct intramolecular formation of a C-S bond in a metal-free, electrochemical key step under ambient conditions, is reported. The broad applicability of this method is demonstrated with 14 examples, including nitrogen-containing heterocycles in isolated yields up to 72%. The resulting sulfonium salts can be used as precursors for fluorine labeling to give [18F]fluoroarenes as found in PET tracer ligands.

Synthesis of high-molar-activity [18F]6-fluoro-L-DOPA suitable for human use via Cu-mediated fluorination of a BPin precursor.

[18F]6-fluoro-L-DOPA ([18F]FDOPA) is a diagnostic radiopharmaceutical for positron emission tomography (PET) imaging that is used to image Parkinson's disease, brain tumors, and focal hyperinsulinism of infancy. Despite these important applications, [18F]FDOPA PET remains underutilized because of synthetic challenges associated with accessing the radiotracer for clinical use; these stem from the need to radiofluorinate a highly electron-rich catechol ring in the presence of an amino acid. To address this longstanding challenge in the PET radiochemistry community, we have developed a one-pot, two-step synthesis of high-molar-activity [18F]FDOPA by Cu-mediated fluorination of a pinacol boronate (BPin) precursor. The method is fully automated, has been validated to work well at two separate sites (an academic facility with a cyclotron on site and an industry lab purchasing [18F]fluoride from an outside vendor), and provides [18F]FDOPA in reasonable radiochemical yield (2.44 ± 0.70 GBq, 66 ± 19 mCi, 5 ± 1%), excellent radiochemical purity (>98%) and high molar activity (76 ± 30 TBq/mmol, 2,050 ± 804 Ci/mmol), n = 26. Herein we report a detailed protocol for the synthesis of [18F]FDOPA that has been successfully implemented at two sites and validated for production of the radiotracer for human use.

Computational prediction of chemical reactions: current status and outlook.

Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities.