Facile Protocol for Water-Tolerant “Frustrated Lewis Pair”-Catalyzed Hydrogenation

Despite rapid advances in the field of metal-free, “frustrated Lewis pair” (FLP)-catalyzed hydrogenation, the need for strictly anhydrous reaction conditions has hampered wide-scale uptake of this methodology. Herein, we report that, despite the generally perceived moisture sensitivity of FLPs, 1,4-dioxane solutions of B(C6F5)3 actually show appreciable moisture tolerance and can catalyze hydrogenation of a range of weakly basic substrates without the need for rigorously inert conditions. In particular, reactions can be performed directly in commercially available nonanhydrous solvents without subsequent drying or use of internal desiccants

Thermodynamics of ligand binding to histone deacetylase like amidohydrolase from Bordetella/Alcaligenes

Thermodynamic studies on ligand–protein binding have become increasingly important in the process of drug design. In combination with structural data and molecular dynamics simulations, thermodynamic studies provide relevant information about the mode of interaction between compounds and their target proteins and therefore build a sound basis for further drug optimization. Using the example of histone deacetylases (HDACs), particularly the histone deacetylase like amidohydrolase (HDAH) from Bordetella/Alcaligenes, a novel sensitive competitive fluorescence resonance energy transfer-based binding assay was developed and the thermodynamics of interaction of both fluorescent ligands and inhibitors to histone deacetylase like amidohydrolase were investigated. The assay consumes only small amounts of valuable target proteins and is suitable for fast kinetic and mechanistic studies as well as high throughput screening applications. Binding affinity increased with increasing length of aliphatic spacers (n?=?4–7) between the hydroxamate moiety and the dansyl head group of ligand probes. Van't Hoff plots revealed an optimum in enthalpy contribution to the free energy of binding for the dansyl-ligand with hexyl spacer. The selectivity in the series of dansyl-ligands against human class I HDAC1 but not class II HDACs 4 and 6 increased with the ratio of deltaH0/deltaG0. The data clearly emphasize the importance of thermodynamic signatures as useful general guidance for the optimization of ligands or rational drug design

Chiroptical studies on brevianamide B : vibrational and electronic circular dichroism confronted

Chiroptical spectroscopy, such as electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) are highly sensitive techniques to probe molecular conformation, configuration, solvation and aggregation. Here we report the application of these techniques to study the fungal metabolite brevianamide B. Comparison of the experimental ECD and VCD spectra with the density functional theory (DFT) simulated counterparts establishes that VCD is the more reliable technique to assign absolute configuration due to the larger functional and dispersion dependence of computed ECD spectra. Despite a low amount of available material, and a relatively unusual example of using VCD carbonyl multiplets, the absolute configuration could be reliably predicted, strengthening the case for application of VCD in the study of complex natural products. Spectral and crystallographic evidence for or against the formation of a dimeric aggregate is discussed; in solution the VCD spectra strongly suggest only monomeric species are present

Theory of apparent circular dichroism in a magnetic field

We present a microscopic theory of apparent circular dichroism in chiral thin films, cast explicitly in terms of molecular property tensors. Our theory provides a general foundation for ab initio calculations and reveals that the films should exhibit an interesting magnetochiral apparent circular dichroism and other novel effects when subjected to a static magnetic field

The antimalarial screening landscape-looking beyond the asexual blood stage.

In recent years, the research agenda to tackle global morbidity and mortality from malaria disease has shifted towards innovation, in the hope that efforts at the frontiers of scientific research may re-invigorate gains made towards eradication. Discovery of new antimalarial drugs with novel chemotypes or modes of action lie at the heart of these efforts. There is a particular interest in drug candidates that target stages of the malaria parasite lifecycle beyond the symptomatic asexual blood stages. This is especially important given the spectre of emerging drug resistance to all current frontline antimalarials. One approach gaining increased interest is the potential of designing novel drugs that target parasite passage from infected individual to feeding mosquito and back again. Action of such therapeutics is geared much more at the population level rather than just concerned with the infected individual. The search for novel drugs active against these stages has been helped by improvements to in vitro culture of transmission and pre-erythrocytic parasite lifecycle stages, robotic automation and high content imaging, methodologies that permit the high-throughput screening (HTS) of compound libraries for drug discovery. Here, we review recent advances in the antimalarial screening landscape, focussed on transmission blocking as a key aim for drug-treatment campaigns of the future

Data-driven discovery of molecular photoswitches with multioutput Gaussian processes

Photoswitchable molecules display two or more isomeric forms that may be accessed using light. Separating the electronic absorption bands of these isomers is key to selectively addressing a specific isomer and achieving high photostationary states whilst overall red-shifting the absorption bands serves to limit material damage due to UV-exposure and increases penetration depth in photopharmacological applications. Engineering these properties into a system through synthetic design however, remains a challenge. Here, we present a data-driven discovery pipeline for molecular photoswitches underpinned by dataset curation and multitask learning with Gaussian processes. In the prediction of electronic transition wavelengths, we demonstrate that a multioutput Gaussian process (MOGP) trained using labels from four photoswitch transition wavelengths yields the strongest predictive performance relative to single-task models as well as operationally outperforming time-dependent density functional theory (TD-DFT) in terms of the wall-clock time for prediction. We validate our proposed approach experimentally by screening a library of commercially available photoswitchable molecules. Through this screen, we identified several motifs that displayed separated electronic absorption bands of their isomers, exhibited red-shifted absorptions, and are suited for information transfer and photopharmacological applications. Our curated dataset, code, as well as all models are made available at https://github.com/Ryan-Rhys/The-Photoswitch-Dataset