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At least 325 records · Page 18

Global characterization of biosynthetic gene clusters in non-model eukaryotes using domain architectures

Abstract The majority of pharmaceuticals are derived from natural products, bioactive compounds naturally synthesized by organisms to provide evolutionary advantages. Although the rich evolutionary history of eukaryotic algal species implicates a high potential for natural product-based drug discovery, it remains largely untouched. This study investigates 2762 putative biosynthetic gene clusters (BGCs) from 212 eukaryotic algal genomes. To analyze a vast set of structurally diverse BGCs, we employed comparative analysis based on the vectorization of biosynthetic domains, referred to as biosynthetic domain architecture (BDA). By characterizing core biosynthetic machineries through BDA, we identified key BDAs of modular BGCs in diverse eukaryotes and introduced 16 candidate modular BGCs with similar BDAs to previously validated BGCs. This study provides a global characterization of eukaryotic algal BGCs, offering an alternative to laborious manual curation for BGC prioritization.

59 BASIC BIOLOGICAL SCIENCES↗

A polyketide-based biosynthetic platform for diols, amino alcohols and hydroxy acids

Medium- and branched-chain diols and amino alcohols are important industrial solvents, polymer building blocks, cosmetics and pharmaceutical ingredients, yet biosynthetically challenging to produce. Here we present an approach that uses a modular polyketide synthase (PKS) platform for the efficient production of these compounds. This platform takes advantage of a versatile loading module from the rimocidin PKS and nicotinamide adenine dinucleotide phosphate-dependent terminal thioreductases. Reduction of the terminal aldehyde with alcohol dehydrogenases enables the production of diols, oxidation enables the production of hydroxy acids and specific transaminases allow the production of various amino alcohols. Furthermore, replacement of the malonyl-coenzyme A-specific acyltransferase in the extension module with methyl- or ethylmalonyl-coenzyme A-specific acyltransferase enables the production of branched-chain diols, amino alcohols and carboxylic acids in high titres. Use of our PKS platform in Streptomyces albus demonstrated the high tunability and efficiency of the platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing protonation states and tracking substrate in serine hydroxymethyltransferase with room-temperature X-ray and neutron crystallography

Pyridoxal 5’-phosphate (PLP)-dependent enzymes utilize a vitamin B 6 -derived cofactor to perform a myriad of chemical transformations on amino acids and other small molecules. Some PLP-dependent enzymes, such as serine hydroxymethyltransferase (SHMT), are promising drug targets for the design of small-molecule antimicrobials and anticancer therapeutics, while others have been used to synthesize pharmaceutical building blocks. Understanding PLP-dependent catalysis and the reaction specificity is crucial to advance structure-assisted drug design and enzyme engineering. Here we report the direct determination of the protonation states in the active site of Thermus thermophilus SHMT (TthSHMT) in the internal aldimine state using room-temperature joint X-ray/neutron crystallography. Conserved active site architecture of the model enzyme TthSHMT and of human mitochondrial SHMT (hSHMT2) were compared by obtaining a room-temperature X-ray structure of hSHMT2, suggesting identical protonation states in the human enzyme. The amino acid substrate serine pathway through the TthSHMT active site cavity was tracked, revealing the peripheral and cationic binding sites that correspond to the pre-Michaelis and pseudo-Michaelis complexes, respectively. At the peripheral binding site, the substrate is bound in the zwitterionic form. By analyzing the observed protonation states, Glu53, but not His residues, is proposed as the general base catalyst, orchestrating the retro-aldol transformation of L-serine into glycine.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Powder diffraction

Powder diffraction is a non-destructive technique, which is experimentally simple in principle. Because the physics behind diffraction is well understood, an exceptionally large amount of information can be obtained from a single measurement. The positions and relative intensities of the peaks yield a fingerprint that can be used for qualitative phase analysis. Quantitative phase analysis can be obtained by detailed analysis of the intensities. Unit cells can be derived from the peak positions. Crystal structures can be solved using powder diffraction data and refined by the Rietveld method. The peak profiles contain information about crystallite size, strain and nanostructure. Non-idealities in the intensities give information on texture. Abandoning the crystallographic model provides information about local structure, by pair distribution function analysis. For powder diffraction, everything is a sample; the technique is commonly applied to characterize minerals, ceramics, metals and alloys, catalysts, polymers, pharmaceuticals, organic compounds, environmental and forensic samples, among others. The major features of contemporary laboratory powder diffractometers are described. Methods for obtaining suitable powder specimens are summarized. Major applications of qualitative and quantitative phase analysis, structure solution, size/strain/nanostructure analysis using peak profiles, texture analysis and pair distribution function analysis are introduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

60 APPLIED LIFE SCIENCES↗

Structure and dynamics of lipid membranes interacting with antivirulence end-phosphorylated polyethylene glycol block copolymers

The structure and dynamics of lipid membranes in the presence of extracellular macromolecules are critical for cell membrane functions and many pharmaceutical applications. The pathogen virulence-suppressing end-phosphorylated polyethylene glycol (PEG) triblock copolymer (Pi-ABAPEG) markedly changes the interactions with lipid vesicle membranes and prevents PEG-induced vesicle phase separation in contrast to the unphosphorylated copolymer (ABAPEG). Pi-ABAPEG weakly absorbs on the surface of lipid vesicle membranes and slightly changes the structure of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) unilamellar vesicles at 37 °C, as evidenced by small angle neutron scattering. X-ray reflectivity measurements confirm the weak adsorption of Pi-ABAPEG on DMPC monolayer, resulting in a more compact DMPC monolayer structure. Neutron spin-echo results show that the adsorption of Pi-ABAPEG on DMPC vesicle membranes increases the membrane bending modulus $κ$.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Formation of resonances and anionic fragments upon electron attachment to benzaldehyde

Benzaldehyde is a simple aromatic aldehyde and has a wide range of applications in the food, pharmaceutical, and chemical industries. The positive electron affinity of this compound suggests that low-energy electrons can be easily trapped by neutral benzaldehyde. In the present study, we investigated the formation of negative ions following electron attachment to benzaldehyde in the gas-phase. Calculations on elastic electron scattering from benzaldehyde indicate a π* valence bound state of the anion at -0.48 eV and three π* shape resonances (0.78, 2.48 and 5.51 eV). The excited state spectrum of the neutral benzaldehyde is also reported to complement our findings. Using mass spectrometry, we observed the formation of the intact anionic benzaldehyde at ~0 eV. We ascribe the detection of the benzaldehyde anion to stabilization of the π* valence bound state upon dissociative electron attachment to a benzaldehyde dimer. In addition, we report the cross sections for nine fragment anions formed through electron attachment to benzaldehyde. Investigations carried out with partially deuterated benzaldehyde show that the hydrogen loss is site-selective with respect to the incident electron energy. In addition, we propose several dissociation pathways, backed up by quantum chemical calculations on their thermodynamic thresholds. The threshold calculations also support that the resonances formed at higher energies lead to fragment anions observable by mass spectrometry, whereas the resonances at low electron energies decay only by electron autodetachment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymers with advanced architectures as emulsifiers for multi-functional emulsions

Emulsions have wide applications in the food, cosmetics, and pharmaceutical industries. Emulsions stabilized with polymers having different architectures, such as linear diblock and triblock copolymers, branched polymers, star polymers, graft polymers, and densely grafted bottlebrush polymers, have been used for encapsulation, delivery, and as templates for polymerization reactions. Furthermore, stimuli-responsive polymers have been used for on-demand demulsification and emulsion engineering. In this review, we highlight the developments in the past decade that used polymers with advanced architectures as multi-functional emulsifiers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mix and match—a versatile equilibrium approach for hybrid colloidal synthesis

Colloidal synthesis is a powerful bottom-up approach for programmed self-assembly which holds promise for both research and industry. While diverse, each synthetic process is typically restricted to a specific chemistry. Many applications however require composite materials, whereas a chemical equilibrium can typically only match one material but not the other. Here, a scalable general approach is presented, alleviating the dependency on a specific chemical reaction, by resorting to a mechanical equilibrium; an isopycnic density-gradient-step is tailored to form clusters with prescribed composition. Valence control is demonstrated, making dimers, trimers, and tetramers with purity as high as 96%. The measured kinetics shows a scaleable throughput. The density gradient step plays a dual role of both filtering out undesired products and concentrating the target structures. The “Mix-and-Match” approach is general, and applies to a broad range of colloidal matter: diverse material compositions (plastics, glasses, and emulsions); a range of colloidal interactions (van der Waals, Coulomb, and DNA hybridization); and a spectrum of sizes (nanoscale to multiple micrometers). Lastly, the strength of the method is displayed by producing a monodisperse suspension from a highly polydisperse emulsion. The ability to combine colloids into architectures of hybrid materials has applications in pharmaceuticals, cosmetics, and photonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Expanding and quantifying the crystal chemistry of the flexible ligand 15aneN5

Tetraazamacrocycles have been very extensively exploited as transition metal ligands for a variety of purposes, including catalysis, medical imaging, pharmaceuticals, etc. However, the pentaazamacrocycles are much less commonly used for similar purposes because of poor availability, difficulties in their synthesis, and less well-known metal coordination properties. 1,4,7,10,13-pentaazacyclopentadane (15aneN5) was initially synthesized by a published synthetic route, which we simplified and shortened with minimal drop in yield. Eight different transition metal complexes were made using typical complexation methods. X-ray crystallography of multiple novel complexes yielded insight into the flexibility in coordination geometry of this interesting macrocycle as well as the first crystal structures of 15aneN5 with Cr 3+ , Mn 3+ , Fe 3+ , Co 3+ , Cu 2+ , and Ru 2+ . A parameter to quantify the coordination geometry adopted by the ligand was devised and applied to all known crystal structures of its metal complexes. Lastly, oxidation of 15aneN5 to a novel diimine macrocycle was observed during complexation with ruthenium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic modelling of an environmentally friendly carbamazepine synthesis via urea and iminostilbene in batch and continuous processes

Accurate kinetic models for reaction systems allow for improved process understanding and greater quality control, which is particularly beneficial as the pharmaceutical industry shifts from batch to continuous manufacturing (CM). In this work, a first principles kinetic model has been developed for the synthesis of carbamazepine (CBZ) from iminostilbene and urea, starting in a batch reactor and subsequently in a continuous flow reactor. An eco-friendly reaction pathway using urea was selected to avoid the toxic reagents that are typically used for synthesis of CBZ. The kinetic parameters determined from batch reactions were utilized in a MATLAB based kinetic model to simulate the yield for the continuous process. Overall, good agreement between the model prediction and corresponding experimental values was observed for the batch and continuous reaction systems within the full factorial design space. However, the model slightly overpredicted the yield of the continuous reaction system for higher conversion values (>60%) since it did not account for the reverse reaction that can occur at the studied reaction conditions. Here, the use of broken order kinetics was compared with whole number orders, and it was determined that the whole number orders resulted in better agreement at all conversion values for the continuous system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗

Electrochemical hydrogen isotope exchange of amines controlled by alternating current frequency

Here, we report an electrochemical protocol for hydrogen isotope exchange (HIE) at α-C(sp 3 )–H amine sites. Tetrahydroisoquinoline and pyrrolidine are selected as two model substrates because of their different proton transfer (PT) and hydrogen atom transfer (HAT) kinetics at the α-C(sp 3 )–H amine sites, which are utilized to control the HIE reaction outcome at different applied alternating current (AC) frequencies. We found the highest deuterium incorporation for tetrahydroisoquinolines at 0 Hz (i.e., under direct current (DC) electrolysis conditions) and pyrrolidines at 0.5 Hz. Analysis of the product distribution and D isotope incorporation at different frequencies reveals that the HIE of tetrahydroisoquinolines is limited by its slow HAT, whereas the HIE of pyrrolidines is limited by the overoxidation of its α-amino radical intermediates. Here, the AC-frequency-dependent HIE of amines can be potentially used to achieve selective labeling of α-amine sites in one drug molecule, which will significantly impact the pharmaceutical industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactions between fullerene derivatives and biological systems

Attention towards nanoparticles from the pharmaceutical and biomedical fields has significantly increased due to their attractive surface modification, high drug-loading, and improved pharmacokinetics. Fullerenes, an allotrope of carbon, stand out for their molecularly precise structure, potent radical-scavenging activity, photoactivatable reactive-oxygen species generation, and ability to definitively confine metal atoms and clusters. Accordingly, fullerene systems have been applied in various biological contexts, including increased and controlled drug delivery, antioxidative, anti-inflammatory, and photodynamic therapy, and magnetic resonance imaging. Ultimately, the pleiotropic activity of fullerenes, coupled with its precise structure and functionalization, can realize precise and tailorable medicines. Here, different from some excellent reviews focusing on the structure and chemistry of fullerene derivatives and their biomedical applications, this review highlights the interaction of fullerene materials with biological systems, with insights into their structural influence on their interactions with the cellular environment.

36 MATERIALS SCIENCE↗