R.B. Leveson-Gower

We introduce the Python package rxnutils that can be used to manipulate chemical reactions, reaction templates and reaction datasets. The package is built entirely on open-source software such as RDKit and is designed with robustness, extendibility, and reproducibility in mind. Currently, it consists of three sub-packages one for working with chemical entities, one provides pipelining capabilities, and one provides an end-to-end pipeline for preparing the US patent reaction dataset for modelling. In this software research note we discuss the design of the package and provide some code examples. The project is open-source with a Apache 2.0 license and available at GitHub: https://github.com/MolecularAI/rxnutils

Nature, Published online: 13 July 2022; doi:10.1038/d41586-022-01900-y

Science is riddled with stories of getting scooped, data glitches and funding crises. Five researchers share stories of how they rallied.

Nature, Published online: 13 July 2022; doi:10.1038/d41586-022-01934-2

UKRI’s proposed stipend increase for 2022–23 falls far short of rise in UK cost of living.

A mild C-H activation of protected L-tryptophan catalyzed by palladium bionanohybrids was developed. Several Pd-biohybrids were synthesized and the influence of temperature or different enzymes as scaffolds were investigated. The reaction efficiency of Pd hybrids was also tested in combination with CuNPs-biohybrids.

AnchoisFert and AnchoiOil are a new organic fertilizer and a new whole fish oil obtained via the circular economy “LimoFish” process based on extraction of the oil from anchovy fillet leftovers with agro-solvent limonene followed by mild drying of the solid residue. We apply the Life Cycle Assessment methodology to evaluate the environmental burdens associated to production of AnchoisFert and AnchoisOil via the aforementioned process at laboratory and industrial scale. Furthermore, we compare the environmental sustainability of AnchoiFert production with conversion of the solid residue into biomethane to produce electricity. The study fills a gap in the literature concerning the environmental soundness of this new circular economy process. Its outcomes will be instrumental to inform its broad evaluation en route to scale-up and industrialization.

The crystal structure of the diterpene synthase CyS was solved, providing the structural basis for cattleyene biosynthesis. A CyS^C59A mutant generated diterpenes with novel carbon skeletons. The remarkable cyclization mechanism of one of these products was characterized by isotopic labeling experiments.

Abstract

The crystal structures of cattleyene synthase (apo-CyS), and CyS complexed with geranylgeranyl pyrophosphate (GGPP) were solved. The CyS^C59A variant exhibited an increased production of cattleyene and other diterpenes with diverse skeletons. Its structure showed a widened active site cavity explaining the relaxed selectivity. Isotopic labeling experiments revealed a remarkable cyclization mechanism involving several skeletal rearrangements for one of the novel diterpenes.

Nature Chemical Biology, Published online: 11 July 2022; doi:10.1038/s41589-022-01070-y

A combination of engineering a fluorine-selective trans-acyltransferase and manipulation of the fluorinated extender unit pool in Escherichia coli enables the production of site-selectively fluorinated erythromycin precursors in vitro in vitroin vitro and in vivo.

Nature, Published online: 11 July 2022; doi:10.1038/d41586-022-01894-7

The UK government must stop picking fights with universities and reset the country’s relationship with the European Union.

Stapling of peptides renders them ideal drug candidates. The individual characteristics of synthetic staple moities impact directly on the peptide’s final properties. We report a bioinspired ketenamine-based peptide staple resembling the natural metabolite lanthionine ketenamine. The strategy is orthogonal to most canonical amino acids, proceeds in water and allows for tailored linkers.

Nature, Published online: 07 July 2022; doi:10.1038/d41586-022-01878-7

Maya Gosztyla decided to rethink her approach to research papers after she had trouble keeping track of the published literature.

Directed evolution is an enzyme engineering approach based on the generation and screening of large mutagenesis libraries, with a view to discovering enzymes with improved properties such as activity, specificity or stability. Recently, droplet-based microfluidics has emerged as a powerful technology enabling ultra-high throughput screening of enzyme libraries and the effective identification and isolation of novel, improved enzyme variants, outperforming conventional enzyme screening platforms by several orders of magnitude in terms of speed and chemical consumption. When using droplet-based platforms fluorescence remains the predominant choice for detection of enzymatic activity due to its high sensitivity and low limits of detection. However, this approach often requires the use of labeled, non-natural substrates, which are typically not commercially available. In addition, fluorescence detection is only suitable for a few enzyme classes such as hydrolases or oxidases, whose reactions can often lead to a fluorescent signal. Herein, we describe an assay that enables fluorescence detection of enzymatic activity through a reaction cascade for the industrially important enzyme subclass of dehydrogenases. By applying a hydrogen peroxide-forming NADH oxidase coupled with peroxidase-catalyzed fluorescence generation, quantification of NADH and dehydrogenase activity becomes possible. We explored the utility of this assay in the evolution of a low performing alcohol dehydrogenase from Sphingomonas species A1 (SpsADH). A fluorescence-activated droplet sorting (FADS) platform was utilized for the screening of a 50,000 variant SpsADH library towards the non-native substrate L-guluronate, a primary component of macroalgae, with the potential to serve as raw material for the bio-based production of chemicals. Significantly, we found an enzyme variant with a 2.6-fold improvement in catalytic efficiency kcat/Km towards the non-native substrate, with only a single round of mutagenesis. The screening of SpsADH libraries confirms the ability of the developed method to enrich active enzyme variants.

Halohydrin dehalogenases are promiscuous biocatalysts, which enable asymmetric ring opening reactions of epoxides with various anionic nucleophiles. However, despite the increasing interest in such asymmetric transformations, the substrate scope of G-type halohydrin dehalogenases toward cyclic epoxides has remained largely unexplored, even though this family is the only one known to display activity with these sterically demanding substrates. Herein, we report on the exploration of the substrate scope of the two G-type halohydrin dehalogenases HheG and HheG2 and a newly identified, more thermostable member of the family, HheG3, with a variety of sterically demanding cyclic epoxides and anionic nucleophiles. This work shows that, in addition to azide and cyanide, these enzymes facilitate ring-opening reactions with cyanate, thiocyanate, formate, and nitrite, significantly expanding the known repertoire of accessible transformations.

Computational approaches to organocatalysis: This review is focused on the different computational approaches that have been applied within the organocatalysis field. A huge effort from the theoretical chemistry field has been made in order to prove that de novo design of effective catalysts for different types of reactions is a long-term target, yet a palpable phenomenon.

Abstract

It is clear that the field of organocatalysis is continuously expanding during the last decades. With increasing computational capacity and new techniques, computational methods have provided a more economic approach to explore different chemical systems. This review offers a broad yet concise overview of current state-of-the-art studies that have employed novel strategies for catalyst design. The evolution of the all different theoretical approaches most commonly used within organocatalysis is discussed, from the traditional approach, manual-driven, to the most recent one, machine-driven.

A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still needs to design the goal, expressed as a scoring function for the molecules that captures the designer’s implicit knowledge about the optimization task. Little support for this task exists and, consequently, a chemist usually resorts to iteratively building the objective function of multi-parameter optimization (MPO) in de novo design. We propose a principled approach to use human-in-the-loop machine learning to help the chemist to adapt the MPO scoring function to better match their goal. An advantage is that the method can learn the scoring function directly from the user’s feedback while they browse the output of the molecule generator, instead of the current manual tuning of the scoring function with trial and error. The proposed method uses a probabilistic model that captures the user’s idea and uncertainty about the scoring function, and it uses active learning to interact with the user. We present two case studies for this: In the first use-case, the parameters of an MPO are learned, and in the second use-case a non-parametric component of the scoring function to capture human domain knowledge is developed. The results show the effectiveness of the methods in two simulated example cases with an oracle, achieving significant improvement in less than 200 feedback queries, for the goals of a high QED score and identifying potent molecules for the DRD2 receptor, respectively. We further demonstrate the performance gains with a medicinal chemist interacting with the system.

Nature, Published online: 30 June 2022; doi:10.1038/d41586-022-01764-2

Two viruses that cause tropical diseases manipulate their hosts into emitting more of a mosquito-attracting molecule.

Of the different classes of halogenases characterized to date, flavin dependent halogenases (FDHs) are most commonly associated with site-selective halogenation of electron rich arenes and enol(ate) moieties in the biosynthesis of halogenated natural products. This capability has made them attractive biocatalysts, and extensive efforts have been devoted to both discovering and engineering these enzymes for different applications. We have established that engineered FDHs can catalyze different enantioselective halogenation processes, including halolactonization of simple alkenes with a tethered carboxylate nucleophile. In this study, we expand the scope of this reaction to include alcohol nucleophiles and a greater diversity of alkene substitution patterns to access a variety of chiral tetrahydrofurans. We also demonstrate that FDHs can be interfaced with ketoreductases to enable halocyclization using ketone substrates in one-pot cascade reactions and that the halocyclization products can undergo subsequent rearrangements to form novel hydroxylated and halogenated products. Together, these advances expand the utility of FDHs for enantio- and diastereoselective olefin functionalization.

Nature, Published online: 29 June 2022; doi:10.1038/d41586-022-01792-y

Scientists in Thailand have established that a tabby passed SARS-CoV-2 to a veterinary surgeon — although such cases of cat-to-human transmission are probably rare.