The iboga enigma: the chemistry and neuropharmacology of iboga alkaloids and related analogs.

Covering: 2000 up to 2020 Few classes of natural products have inspired as many chemists and biologists as have the iboga alkaloids. This family of monoterpenoid indole alkaloids includes the anti-addictive compound ibogaine as well as catharanthine, a precursor to the chemotherapeutic vinblastine. Despite being known for over 120 years, these small molecules continue to challenge our assumptions about biosynthetic pathways, catalyze our creativity for constructing complex architectures, and embolden new approaches for treating mental illness. This review will cover recent advances in both the biosynthesis and chemical synthesis of iboga alkaloids as well as their use as next-generation neurotherapeutics. Whenever appropriate, we provide historical context for the discoveries of the past decade and indicate areas that have yet to be resolved. While significant progress regarding their chemistry and pharmacology has been made since the 1960s, it is clear that the iboga alkaloids will continue to stoke scientific innovation for years to come.

Synthesis of Tertiary Amines through Extrusive Alkylation of Carbamates.

Basic amines are key elements of many biologically active natural products and pharmaceuticals. Given their inherent reactivity, it is often necessary to protect basic amines during target-directed synthesis, which results in wasteful protection/deprotection sequences. We report a step-economical approach enabling the protection of secondary amines as carbamates prior to their conversion to tertiary amines via the formal extrusion of CO2. This method is applied to the synthesis of iboga alkaloids (±)-conodusine A and (±)-conodusine B.

High-performance and scalable on-chip digital Fourier transform spectroscopy.

On-chip spectrometers have the potential to offer dramatic size, weight, and power advantages over conventional benchtop instruments for many applications such as spectroscopic sensing, optical network performance monitoring, hyperspectral imaging, and radio-frequency spectrum analysis. Existing on-chip spectrometer designs, however, are limited in spectral channel count and signal-to-noise ratio. Here we demonstrate a transformative on-chip digital Fourier transform spectrometer that acquires high-resolution spectra via time-domain modulation of a reconfigurable Mach-Zehnder interferometer. The device, fabricated and packaged using industry-standard silicon photonics technology, claims the multiplex advantage to dramatically boost the signal-to-noise ratio and unprecedented scalability capable of addressing exponentially increasing numbers of spectral channels. We further explore and implement machine learning regularization techniques to spectrum reconstruction. Using an 'elastic-D1' regularized regression method that we develop, we achieved significant noise suppression for both broad (>600 GHz) and narrow (<25 GHz) spectral features, as well as spectral resolution enhancement beyond the classical Rayleigh criterion.