Asymmetric Synthesis of Chiral 2-Cyclohexenones with Quaternary Stereocenters via Ene-Reductase Catalyzed Desymmetrization of 2,5-Cyclohexadienones.

Stereoselective synthesis of quaternary stereocenters represents a significant challenge in organic chemistry. Herein, we describe the use of ene-reductases OPR3 and YqjM for the efficient asymmetric synthesis of chiral 4,4-disubstituted 2-cyclohexenones via desymmetrizing hydrogenation of prochiral 4,4-disubstituted 2,5-cyclohexadienones. This transformation breaks the symmetry of the cyclohexadienone substrates, generating valuable quaternary stereocenters with high enantioselectivities (ee, up to >99%). The mechanistic causes for the observed high enantioselectivities were investigated both experimentally (stopped-flow kinetics) as well as theoretically (quantum mechanics/molecular mechanics calculations). The synthetic potential of the resulting chiral enones was demonstrated in several diversification reactions in which the stereochemical integrity of the quaternary stereocenter could be preserved.

Structural investigation of Trypanosoma cruzi Akt-like kinase as drug target against Chagas disease.

According to the World Health Organization, Chagas disease (CD) is the most prevalent poverty-promoting neglected tropical disease. Alarmingly, climate change is accelerating the geographical spreading of CD causative parasite, Trypanosoma cruzi, which additionally increases infection rates. Still, CD treatment remains challenging due to a lack of safe and efficient drugs. In this work, we analyze the viability of T. cruzi Akt-like kinase (TcAkt) as drug target against CD including primary structural and functional information about a parasitic Akt protein. Nuclear Magnetic Resonance derived information in combination with Molecular Dynamics simulations offer detailed insights into structural properties of the pleckstrin homology (PH) domain of TcAkt and its binding to phosphatidylinositol phosphate ligands (PIP). Experimental data combined with Alpha Fold proposes a model for the mechanism of action of TcAkt involving a PIP-induced disruption of the intramolecular interface between the kinase and the PH domain resulting in an open conformation enabling TcAkt kinase activity. Further docking experiments reveal that TcAkt is recognized by human inhibitors PIT-1 and capivasertib, and TcAkt inhibition by UBMC-4 and UBMC-6 is achieved via binding to TcAkt kinase domain. Our in-depth structural analysis of TcAkt reveals potential sites for drug development against CD, located at activity essential regions.

Flattening the curve-How to get better results with small deep-mutational-scanning datasets.

Proteins are used in various biotechnological applications, often requiring the optimization of protein properties by introducing specific amino-acid exchanges. Deep mutational scanning (DMS) is an effective high-throughput method for evaluating the effects of these exchanges on protein function. DMS data can then inform the training of a neural network to predict the impact of mutations. Most approaches use some representation of the protein sequence for training and prediction. As proteins are characterized by complex structures and intricate residue interaction networks, directly providing structural information as input reduces the need to learn these features from the data. We introduce a method for encoding protein structures as stacked 2D contact maps, which capture residue interactions, their evolutionary conservation, and mutation-induced interaction changes. Furthermore, we explored techniques to augment neural network training performance on smaller DMS datasets. To validate our approach, we trained three neural network architectures originally used for image analysis on three DMS datasets, and we compared their performances with networks trained solely on protein sequences. The results confirm the effectiveness of the protein structure encoding in machine learning efforts on DMS data. Using structural representations as direct input to the networks, along with data augmentation and pretraining, significantly reduced demands on training data size and improved prediction performance, especially on smaller datasets, while performance on large datasets was on par with state-of-the-art sequence convolutional neural networks. The methods presented here have the potential to provide the same workflow as DMS without the experimental and financial burden of testing thousands of mutants. Additionally, we present an open-source, user-friendly software tool to make these data analysis techniques accessible, particularly to biotechnology and protein engineering researchers who wish to apply them to their mutagenesis data.

Stability Increase of Phenolic Acid Decarboxylase by a Combination of Protein and Solvent Engineering Unlocks Applications at Elevated Temperatures.

Enzymatic decarboxylation of biobased hydroxycinnamic acids gives access to phenolic styrenes for adhesive production. Phenolic acid decarboxylases are proficient enzymes that have been applied in aqueous systems, organic solvents, biphasic systems, and deep eutectic solvents, which makes stability a key feature. Stabilization of the enzyme would increase the total turnover number and thus reduce the energy consumption and waste accumulation associated with biocatalyst production. In this study, we used ancestral sequence reconstruction to generate thermostable decarboxylases. Investigation of a set of 16 ancestors resulted in the identification of a variant with an unfolding temperature of 78.1 °C and a half-life time of 45 h at 60 °C. Crystal structures were determined for three selected ancestors. Structural attributes were calculated to fit different regression models for predicting the thermal stability of variants that have not yet been experimentally explored. The models rely on hydrophobic clusters, salt bridges, hydrogen bonds, and surface properties and can identify more stable proteins out of a pool of candidates. Further stabilization was achieved by the application of mixtures of natural deep eutectic solvents and buffers. Our approach is a straightforward option for enhancing the industrial application of the decarboxylation process.

Deciphering the Unconventional Reduction of C=N Bonds by Old Yellow Enzymes Using QM/MM.

The reduction of C=X (X = N, O) bonds is a cornerstone in both synthetic organic chemistry and biocatalysis. Conventional reduction mechanisms usually involve a hydride ion targeting the less electronegative carbon atom. In a departure from this paradigm, our investigation into Old Yellow Enzymes (OYEs) reveals a mechanism involving transfer of hydride to the formally more electronegative nitrogen atom within a C=N bond. Beyond their known ability to reduce electronically activated C=C double bonds, e.g., in α, ß-unsaturated ketones, these enzymes have recently been shown to reduce α-oximo-ß-ketoesters to the corresponding amines. It has been proposed that this transformation involves two successive reduction steps and proceeds via imine intermediates formed by the reductive dehydration of the oxime moieties. We employ advanced quantum mechanics/molecular mechanics (QM/MM) simulations, enriched by a two-tiered approach incorporating QM/MM (UB3LYP-6-31G*/OPLS2005) geometry optimization, QM/MM (B3LYP-6-31G*/amberff19sb) steered molecular dynamics simulations, and detailed natural-bond-orbital analyses to decipher the unconventional hydride transfer to nitrogen in both reduction steps and to delineate the role of active site residues as well as of substituents present in the substrates. Our computational results confirm the proposed mechanism and agree well with experimental mutagenesis and enzyme kinetics data. According to our model, the catalysis of OYE involves hydride transfer from the flavin cofactor to the nitrogen atom in oximoketoesters as well as iminoketoesters followed by protonation at the adjacent oxygen or carbon atoms by conserved tyrosine residues and active site water molecules. Two histidine residues play a key role in the polarization and activation of the C=N bond, and conformational changes of the substrate observed along the reaction coordinate underline the crucial importance of dynamic electron delocalization for efficient catalysis.

Unravelling the respiratory health path across the lifespan for survivors of preterm birth.

Many survivors of preterm birth will have abnormal lung development, reduced peak lung function and, potentially, an increased rate of physiological lung function decline, each of which places them at increased risk of chronic obstructive pulmonary disease across the lifespan. Current rates of preterm birth indicate that by the year 2040, around 50 years since the introduction of surfactant therapy, more than 700 million individuals will have been born prematurely-a number that will continue to increase by about 15 million annually. In this Personal View, we describe current understanding of the impact of preterm birth on lung function through the life course, with the aim of putting this emerging health crisis on the radar for the respiratory community. We detail the potential underlying mechanisms of prematurity-associated lung disease and review current approaches to prevention and management. Furthermore, we propose a novel way of considering lung disease after preterm birth, using a multidimensional model to determine individual phenotypes of lung disease-a first step towards optimising management approaches for prematurity-associated lung disease.

AI-assisted structural consensus-proteome prediction of human monkeypox viruses isolated within a year after the 2022 multi-country outbreak.

IMPORTANCE: The 2022 outbreak of the monkeypox virus already involves, by April 2023, 110 countries with 86,956 confirmed cases and 119 deaths. Understanding an emerging disease on a molecular level is essential to study infection processes and eventually guide drug discovery at an early stage. To support this, we provide the so far most comprehensive structural proteome of the monkeypox virus, which includes 210 structural models, each computed with three state-of-the-art structure prediction methods. Instead of building on a single-genome sequence, we generated our models from a consensus of 3,713 high-quality genome sequences sampled from patients within 1 year of the outbreak. Therefore, we present an average structural proteome of the currently isolated viruses, including mutational analyses with a special focus on drug-binding sites. Continuing dynamic mutation monitoring within the structural proteome presented here is essential to timely predict possible physiological changes in the evolving virus.

Ligand-Directed Chemistry on Glycoside Hydrolases - A Proof of Concept Study.

Selective covalent labelling of enzymes using small molecule probes has advanced the scopes of protein profiling. The covalent bond formation to a specific target is the key step of activity-based protein profiling (ABPP), a method which has become an indispensable tool for measuring enzyme activity in complex matrices. With respect to carbohydrate processing enzymes, strategies for ABPP so far involve labelling the active site of the enzyme, which results in permanent loss of activity. Here, we report in a proof of concept study the use of ligand-directed chemistry (LDC) for labelling glycoside hydrolases near - but not in - the active site. During the labelling process, the competitive inhibitor is cleaved from the probe, departs the active site and the enzyme maintains its catalytic activity. To this end, we designed a building block synthetic concept for small molecule probes containing iminosugar-based reversible inhibitors for labelling of two model ß-glucosidases. The results indicate that the LDC approach can be adaptable for covalent proximity labelling of glycoside hydrolases.

A Cold-Active Flavin-Dependent Monooxygenase from Janthinobacterium svalbardensis Unlocks Applications of Baeyer-Villiger Monooxygenases at Low Temperature.

Cold-active enzymes maintain a large part of their optimal activity at low temperatures. Therefore, they can be used to avoid side reactions and preserve heat-sensitive compounds. Baeyer-Villiger monooxygenases (BVMO) utilize molecular oxygen as a co-substrate to catalyze reactions widely employed for steroid, agrochemical, antibiotic, and pheromone production. Oxygen has been described as the rate-limiting factor for some BVMO applications, thereby hindering their efficient utilization. Considering that oxygen solubility in water increases by 40% when the temperature is decreased from 30 to 10 °C, we set out to identify and characterize a cold-active BVMO. Using genome mining in the Antarctic organism Janthinobacterium svalbardensis, a cold-active type II flavin-dependent monooxygenase (FMO) was discovered. The enzyme shows promiscuity toward NADH and NADPH and high activity between 5 and 25 °C. The enzyme catalyzes the monooxygenation and sulfoxidation of a wide range of ketones and thioesters. The high enantioselectivity in the oxidation of norcamphor (eeS = 56%, eeP > 99%, E > 200) demonstrates that the generally higher flexibility observed in the active sites of cold-active enzymes, which compensates for the lower motion at cold temperatures, does not necessarily reduce the selectivity of these enzymes. To gain a better understanding of the unique mechanistic features of type II FMOs, we determined the structure of the dimeric enzyme at 2.5 Å resolution. While the unusual N-terminal domain has been related to the catalytic properties of type II FMOs, the structure shows a SnoaL-like N-terminal domain that is not interacting directly with the active site. The active site of the enzyme is accessible only through a tunnel, with Tyr-458, Asp-217, and His-216 as catalytic residues, a combination not observed before in FMOs and BVMOs.

Mechanistic Insights into the Ene-Reductase-Catalyzed Promiscuous Reduction of Oximes to Amines.

The biocatalytic reduction of the oxime moiety to the corresponding amine group has only recently been found to be a promiscuous activity of ene-reductases transforming α-oximo ß-keto esters. However, the reaction pathway of this two-step reduction remained elusive. By studying the crystal structures of enzyme oxime complexes, analyzing molecular dynamics simulations, and investigating biocatalytic cascades and possible intermediates, we obtained evidence that the reaction proceeds via an imine intermediate and not via the hydroxylamine intermediate. The imine is reduced further by the ene-reductase to the amine product. Remarkably, a non-canonical tyrosine residue was found to contribute to the catalytic activity of the ene-reductase OPR3, protonating the hydroxyl group of the oxime in the first reduction step.

A chromosome-level genome assembly for Erianthus fulvus provides insights into its biofuel potential and facilitates breeding for improvement of sugarcane.

Erianthus produces substantial biomass, exhibits a good Brix value, and shows wide environmental adaptability, making it a potential biofuel plant. In contrast to closely related sorghum and sugarcane, Erianthus can grow in degraded soils, thus releasing pressure on agricultural lands used for biofuel production. However, the lack of genomic resources for Erianthus hinders its genetic improvement, thus limiting its potential for biofuel production. In the present study, we generated a chromosome-scale reference genome for Erianthus fulvus Nees. The genome size estimated by flow cytometry was 937 Mb, and the assembled genome size was 902 Mb, covering 96.26% of the estimated genome size. A total of 35 065 protein-coding genes were predicted, and 67.89% of the genome was found to be repetitive. A recent whole-genome duplication occurred approximately 74.10 million years ago in the E. fulvus genome. Phylogenetic analysis showed that E. fulvus is evolutionarily closer to S. spontaneum and diverged after S. bicolor. Three of the 10 chromosomes of E. fulvus formed through rearrangements of ancestral chromosomes. Phylogenetic reconstruction of the Saccharum complex revealed a polyphyletic origin of the complex and a sister relationship of E. fulvus with Saccharum sp., excluding S. arundinaceum. On the basis of the four amino acid residues that provide substrate specificity, the E. fulvus SWEET proteins were classified as mono- and disaccharide sugar transporters. Ortho-QTL genes identified for 10 biofuel-related traits may aid in the rapid screening of E. fulvus populations to enhance breeding programs for improved biofuel production. The results of this study provide valuable insights for breeding programs aimed at improving biofuel production in E. fulvus and enhancing sugarcane introgression programs.

Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations.

Treatment of COVID-19 with a soluble version of ACE2 that binds to SARS-CoV-2 virions before they enter host cells is a promising approach, however it needs to be optimized and adapted to emerging viral variants. The computational workflow presented here consists of molecular dynamics simulations for spike RBD-hACE2 binding affinity assessments of multiple spike RBD/hACE2 variants and a novel convolutional neural network architecture working on pairs of voxelized force-fields for efficient search-space reduction. We identified hACE2-Fc K31W and multi-mutation variants as high-affinity candidates, which we validated in vitro with virus neutralization assays. We evaluated binding affinities of these ACE2 variants with the RBDs of Omicron BA.3, Omicron BA.4/BA.5, and Omicron BA.2.75 in silico. In addition, candidates produced in Nicotiana benthamiana, an expression organism for potential large-scale production, showed a 4.6-fold reduction in half-maximal inhibitory concentration (IC50) compared with the same variant produced in CHO cells and an almost six-fold IC50 reduction compared with wild-type hACE2-Fc.

Structural bioinformatics analysis of SARS-CoV-2 variants reveals higher hACE2 receptor binding affinity for Omicron B.1.1.529 spike RBD compared to wild type reference.

To date, more than 263 million people have been infected with SARS-CoV-2 during the COVID-19 pandemic. In many countries, the global spread occurred in multiple pandemic waves characterized by the emergence of new SARS-CoV-2 variants. Here we report a sequence and structural-bioinformatics analysis to estimate the effects of amino acid substitutions on the affinity of the SARS-CoV-2 spike receptor binding domain (RBD) to the human receptor hACE2. This is done through qualitative electrostatics and hydrophobicity analysis as well as molecular dynamics simulations used to develop a high-precision empirical scoring function (ESF) closely related to the linear interaction energy method and calibrated on a large set of experimental binding energies. For the latest variant of concern (VOC), B.1.1.529 Omicron, our Halo difference point cloud studies reveal the largest impact on the RBD binding interface compared to all other VOC. Moreover, according to our ESF model, Omicron achieves a much higher ACE2 binding affinity than the wild type and, in particular, the highest among all VOCs except Alpha and thus requires special attention and monitoring.

Structure-Based Demystification of Radical Catalysis by a Coenzyme B12 Dependent Enzyme-Crystallographic Study of Glutamate Mutase with Cofactor Homologues.

Catalysis by radical enzymes dependent on coenzyme B12 (AdoCbl) relies on the reactive primary 5'-deoxy-5'adenosyl radical, which originates from reversible Co-C bond homolysis of AdoCbl. This bond homolysis is accelerated roughly 1012 -fold upon binding the enzyme substrate. The structural basis for this activation is still strikingly enigmatic. As revealed here, a displaced firm adenosine binding cavity in substrate-loaded glutamate mutase (GM) causes a structural misfit for intact AdoCbl that is relieved by the homolytic Co-C bond cleavage. Strategically interacting adjacent adenosine- and substrate-binding protein cavities provide a tight caged radical reaction space, controlling the entire radical path. The GM active site is perfectly structured for promoting radical catalysis, including "negative catalysis", a paradigm for AdoCbl-dependent mutases.

Small-Molecule Inhibitors Targeting Lipolysis in Human Adipocytes.

Chronically elevated circulating fatty acid levels promote lipid accumulation in nonadipose tissues and cause lipotoxicity. Adipose triglyceride lipase (ATGL) critically determines the release of fatty acids from white adipose tissue, and accumulating evidence suggests that inactivation of ATGL has beneficial effects on lipotoxicity-driven disorders including insulin resistance, steatohepatitis, and heart disease, classifying ATGL as a promising drug target. Here, we report on the development and biological characterization of the first small-molecule inhibitor of human ATGL. This inhibitor, designated NG-497, selectively inactivates human and nonhuman primate ATGL but not structurally and functionally related lipid hydrolases. We demonstrate that NG-497 abolishes lipolysis in human adipocytes in a dose-dependent and reversible manner. The combined analysis of mouse- and human-selective inhibitors, chimeric ATGL proteins, and homology models revealed detailed insights into enzyme-inhibitor interactions. NG-497 binds ATGL within a hydrophobic cavity near the active site. Therein, three amino acid residues determine inhibitor efficacy and species selectivity and thus provide the molecular scaffold for selective inhibition.

Residue-Specific Incorporation of the Non-Canonical Amino Acid Norleucine Improves Lipase Activity on Synthetic Polyesters.

Environmentally friendly functionalization and recycling processes for synthetic polymers have recently gained momentum, and enzymes play a central role in these procedures. However, natural enzymes must be engineered to accept synthetic polymers as substrates. To enhance the activity on synthetic polyesters, the canonical amino acid methionine in Thermoanaerobacter thermohydrosulfuricus lipase (TTL) was exchanged by the residue-specific incorporation method for the more hydrophobic non-canonical norleucine (Nle). Strutural modelling of TTL revealed that residues Met-114 and Met-142 are in close vicinity of the active site and their replacement by the norleucine could modulate the catalytic activity of the enzyme. Indeed, hydrolysis of the polyethylene terephthalate model substrate by the Nle variant resulted in significantly higher amounts of release products than the Met variant. A similar trend was observed for an ionic phthalic polyester containing a short alkyl diol (C5). Interestingly, a 50% increased activity was found for TTL [Nle] towards ionic phthalic polyesters containing different ether diols compared to the parent enzyme TTL [Met]. These findings clearly demonstrate the high potential of non-canonical amino acids for enzyme engineering.

Recent changes in the mutational dynamics of the SARS-CoV-2 main protease substantiate the danger of emerging resistance to antiviral drugs.

Introduction: The current coronavirus pandemic is being combated worldwide by nontherapeutic measures and massive vaccination programs. Nevertheless, therapeutic options such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main-protease (Mpro) inhibitors are essential due to the ongoing evolution toward escape from natural or induced immunity. While antiviral strategies are vulnerable to the effects of viral mutation, the relatively conserved Mpro makes an attractive drug target: Nirmatrelvir, an antiviral targeting its active site, has been authorized for conditional or emergency use in several countries since December 2021, and a number of other inhibitors are under clinical evaluation. We analyzed recent SARS-CoV-2 genomic data, since early detection of potential resistances supports a timely counteraction in drug development and deployment, and discovered accelerated mutational dynamics of Mpro since early December 2021. Methods: We performed a comparative analysis of 10.5 million SARS-CoV-2 genome sequences available by June 2022 at GISAID to the NCBI reference genome sequence NC_045512.2. Amino-acid exchanges within high-quality regions in 69,878 unique Mpro sequences were identified and time- and in-depth sequence analyses including a structural representation of mutational dynamics were performed using in-house software. Results: The analysis showed a significant recent event of mutational dynamics in Mpro. We report a remarkable increase in mutational variability in an eight-residue long consecutive region (R188-G195) near the active site since December 2021. Discussion: The increased mutational variability in close proximity to an antiviral-drug binding site as described herein may suggest the onset of the development of antiviral resistance. This emerging diversity urgently needs to be further monitored and considered in ongoing drug development and lead optimization.