Predicting relative efficiency of amide bond formation using multivariate linear regression.

Amides are ubiquitous in biologically active natural products and commercial drugs. The most common strategy for introducing this functional group is the coupling of a carboxylic acid with an amine, which requires the use of a coupling reagent to facilitate elimination of water. However, the optimal reaction conditions often appear rather arbitrary to the specific reaction. Herein, we report the development of statistical models correlating measured rates to physical organic descriptors to enable the prediction of reaction rates for untested carboxylic acid/amine pairs. The key to the success of this endeavor was the development of an end-to-end data science­based workflow to select a set of coupling partners that are appropriately distributed in chemical space to facilitate statistical model development. By using a parameterization, dimensionality reduction, and clustering protocol, a training set was identified. Reaction rates for a range of carboxylic acid and primary alkyl amine couplings utilizing carbonyldiimidazole (CDI) as the coupling reagent were measured. The collected rates span five orders of magnitude, confirming that the designed training set encompasses a wide range of chemical space necessary for effective model development. Regressing these rates with high-level density functional theory (DFT) descriptors allowed for identification of a statistical model wherein the molecular features of the carboxylic acid are primarily responsible for the observed rates. Finally, out-of-sample amide couplings are used to determine the limitations and effectiveness of the model.

From Bulk to Single Molecules: Surface-Enhanced Raman Scattering of Cytochrome C Using Plasmonic DNA Origami Nanoantennas.

Cytochrome C, an evolutionarily conserved protein, plays pivotal roles in cellular respiration and apoptosis. Understanding its molecular intricacies is essential for both academic inquiry and potential biomedical applications. This study introduces an advanced single-molecule surface-enhanced Raman scattering (SM-SERS) system based on DNA origami nanoantennas (DONAs), optimized to provide unparalleled insights into protein structure and interactions. Our system effectively detects shifts in the Amide III band, thereby elucidating protein dynamics and conformational changes. Additionally, the system permits concurrent observations of oxidation processes and Amide bands, offering an integrated view of protein structural and chemical modifications. Notably, our approach diverges from traditional SM-SERS techniques by de-emphasizing resonance conditions for SERS excitation, aiming to mitigate challenges like peak oversaturation. Our findings underscore the capability of our DONAs to illuminate single-molecule behaviors, even within aggregate systems, providing clarity on molecular interactions and behaviors.

A fluorogenic substrate for the detection of lipid amidases in intact cells.

Lipid amidases of therapeutic relevance include acid ceramidase (AC), N-acylethanolamine-hydrolyzing acid amidase, and fatty acid amide hydrolase (FAAH). Although fluorogenic substrates have been developed for the three enzymes and high-throughput methods for screening have been reported, a platform for the specific detection of these enzyme activities in intact cells is lacking. In this article, we report on the coumarinic 1-deoxydihydroceramide RBM1-151, a 1-deoxy derivative and vinilog of RBM14-C12, as a novel substrate of amidases. This compound is hydrolyzed by AC (appKm = 7.0 µM; appVmax = 99.3 nM/min), N-acylethanolamine-hydrolyzing acid amidase (appKm = 0.73 µM; appVmax = 0.24 nM/min), and FAAH (appKm = 3.6 µM; appVmax = 7.6 nM/min) but not by other ceramidases. We provide proof of concept that the use of RBM1-151 in combination with reported irreversible inhibitors of AC and FAAH allows the determination in parallel of the three amidase activities in single experiments in intact cells.

Molecular identification of a laccase that catalyzes the oxidative coupling of a hydroxycinnamic acid amide for hordatine biosynthesis in barley.

Plants produce dimerized phenolic compounds as secondary metabolites. Hordatine A (HA), a dehydrodimer of p-coumaroylagmatine (pCA), is an antifungal compound accumulated at high levels in young barley (Hordeum vulgare) seedlings. The enzyme responsible for the oxidative dimerization of pCA, which is the final step of the hordatine biosynthetic pathway, has not been identified. In this study, we first verified the presence of this enzyme activity in the crude extract of barley seedlings. Because the enzyme activity was not dependent on H2 O2 , the responsible enzyme was not peroxidase, which was previously implicated in HA biosynthesis. The analysis of the dissection lines of wheat (Triticum aestivum) carrying aberrant barley 2H chromosomes detected HA in the wheat lines carrying the distal part of the 2H short arm. This chromosomal region contains two laccase genes (HvLAC1 and HvLAC2) that are highly expressed at the seedling stage and may encode enzymes that oxidize pCA during the formation of HA. Changes in the HvLAC transcript levels coincided with the changes in the HA biosynthesis-related enzyme activities in the crude extract and the HA content in barley seedlings. Moreover, HvLAC genes were heterologously expressed in Nicotiana benthamiana leaves and in bamboo (Phyllostachys nigra) suspension cells and HA biosynthetic activities were detected in the crude extract of transformed N. benthamiana leaves and bamboo suspension cells. The HA formed by the enzymatic reaction had the same stereo-configuration as the naturally occurring HA. These results demonstrate that HvLAC enzymes mediate the oxidative coupling of pCA during HA biosynthesis.

Thiophenpiperazine amide derivatives as new dual MOR and σ1R ligands for the treatment of pain.

A new series of thiophenpiperazine amide derivatives as potent dual ligands for the µ-opioid (MOR) and sigma-1 (σ1R) receptors are reported. Compound 23 exhibited good affinity to σ1R (Ki = 44.7 ± 7.05 nM) and high selectivity to σ2R. Furthermore, Compound 23 exerted MOR agonism and σ1R antagonism and potent analgesic activity in animal moldes (the abdominal constriction test (ED50 = 3.83 mg/kg) and carrageenan-induced inflammatory hyperalgesia model (ED50 = 5.23 mg/kg)). We obtained new dual ligands that might serve as starting points for preparing targeted tools. Furthermore, 23 may be a useful chemical probe for understanding more fully analgesic effects associated with MOR agonism and σ1R antagonism.

Robust Amide-Linked Fluorinated Covalent Organic Framework for Long-Term Oxygen Reduction Reaction Electrocatalysis.

The high energy demand of the evolving world opens the door to develop more sustainable and environmentally friendly energy sources. Oxygen reduction reaction (ORR) is a promising candidate, being the 2e- pathway of great interest for the green production of hydrogen peroxide. Metal-free covalent organic frameworks (COFs) electrocatalysts present a suitable alternative to substitute the noble-metals more commonly employed in this application. However, the lability of the linkages building up the framework raises an issue for their long-term use and application in aggressive media. Herein, a stable amide-linked COF is reported through post-synthetic modification of a previously reported imine-linked COF proven to be effective as an electrocatalyst, enhancing its chemical stability and electrochemical response. It is found that after the linkage transformation, the new electrocatalyst displays a higher selectivity toward the H2O2 production (98.5%) and an enhanced turnover frequency of 0.155 s-1, which is among the bests reported to date for metal-free and COF based electrocatalysts. The results represent a promising step forward for metal-free non pyrolyzed electrocatalysts, improving their properties through post-synthetic linkage modification for long-term operation.

Revitalization of Diluent Amide-Based Electrolyte for Building High-Voltage Lithium-Metal Batteries.

Hitherto, highly concentrated electrolyte is the overarching strategy for revitalizing the usage of amide - in lithium-metal batteries (LMBs), which simultaneously mitigates the reactivity of amide toward Li and regulates uniform Li deposition via forming anion-solvated coordinate structure. However, it is undeniable that this would bring the cost burden for practical electrolyte preparation, which stimulates further electrolyte design toward tailoring anion-abundant Li+ solvation structure in stable amide electrolytes under a low salt content. Herein, a distinct method is conceived to design anions-enriched Li+ solvation structure in dilute amide-electrolyte (1 m Li-salt concentration) with the aid of integrating perfluoropolyethers (PFPE-MC) with anion-solvating ability and B/F-involved additives. The optimized electrolyte based on N,N-Dimethyltrifluoroacetamide (FDMAC) exhibits outstanding compatibility with Li and NCM622 cathode, facilitates uniform Li deposition along with robust solid electrolyte interphase (SEI) formation. Accordingly, both the lab-level LMB coin cell and practical pouch cell based on this dilute FDMAC electrolyte deliver remarkable performances with improved capacity and cyclability. This work pioneers the feasibility of diluted amide as electrolyte in LMB, and provides an innovative strategy for highly stable Li deposition via manipulating solvation structure within diluent electrolyte, impelling the electrolyte engineering development for practical high-energy LMBs.

Enzymatic Strategies for the Biosynthesis of N-Acyl Amino Acid Amides.

Amide bond-containing biomolecules are functionally significant and useful compounds with diverse applications. For example, N-acyl amino acids (NAAAs) are an important class of lipoamino acid amides with extensive use in food, cosmetic and pharmaceutical industries. Their conventional chemical synthesis involves the use of toxic chlorinating agents for carboxylic acid activation. Enzyme-catalyzed biotransformation for the green synthesis of these amides is therefore highly desirable. Here, we review a range of enzymes suitable for the synthesis of NAAA amides and their strategies adopted in carboxylic acid activation. Generally, ATP-dependent enzymes for NAAA biosynthesis are acyl-adenylating enzymes that couple the hydrolysis of phosphoanhydride bond in ATP with the formation of an acyl-adenylate intermediate. In contrast, ATP-independent enzymes involve hydrolases such as lipases or aminoacylases, which rely on the transient activation of the carboxylic acid. This occurs either through an acyl-enzyme intermediate or by favorable interactions with surrounding residues to anchor the acyl donor in a suitable orientation for the incoming amine nucleophile. Recently, the development of an alternative pathway involving ester-amide interconversion has unraveled another possible strategy for amide formation through esterification-aminolysis cascade reactions, potentially expanding the substrate scope for enzymes to catalyze the synthesis of a diverse range of NAAA amides.

Dual contrast CEST MRI for pH-weighted imaging in stroke.

PURPOSE: pH enhanced (pHenh ) CEST imaging combines the pH sensitivity from amide and guanidino signals, but the saturation parameters have not been optimized. We propose pHdual as a variant of pHenh that suppresses background signal variations, while enhancing pH sensitivity and potential for imaging ischemic brain injury of stroke. METHODS: Simulation and in vivo rodent stroke experiments of pHenh MRI were performed with varied RF saturation powers for both amide and guanidino protons to optimize the contrast between lesion/normal tissues, while simultaneously minimizing signal variations across different types of normal tissues. In acute stroke, contrast and volume ratio measured by pHdual imaging were compared with an amide-CEST approach, and perfusion and diffusion MRI. RESULTS: Simulation experiments indicated that amide and guanidino CEST signals exhibit unique sensitivities across different pH ranges, with pHenh producing greater sensitivity over a broader pH regime. The pHenh data of rodent stroke brain demonstrated that the lesion/normal tissue contrast was maximized for an RF saturation power pair of 0.5 µT at 2.0 ppm and 1.0 µT at 3.6 ppm, whereas an optimal contrast-to-variation ratio (CVR) was obtained with a 0.7 µT saturation at 2.0 ppm and 0.8 µT at 3.6 ppm. In acute stroke, CVR optimized pHenh (i.e., pHdual ) achieved a higher sensitivity than the three-point amide-CEST approach, and distinct patterns of lesion tissue compared to diffusion and perfusion MRI. CONCLUSION: pHdual MRI improves the sensitivity of pH-weighted imaging and will be a valuable tool for assessing tissue viability in stroke.

Machine learning-based amide proton transfer imaging using partially synthetic training data.

PURPOSE: Machine learning (ML) has been increasingly used to quantify CEST effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, whereas training with fully simulated data may introduce bias because of limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect. METHODS: Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9 L tumors. RESULTS: Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data. CONCLUSION: Partially synthetic CEST data can address the challenges in conventional ML methods.

Evaluation of the molecular origin of amide proton transfer-weighted imaging.

PURPOSE: To evaluate the assumption in amide proton transfer weighted (APTw) imaging that the APT dominates over the relayed nuclear Overhauser enhancement (rNOE) and other CEST effects such as those from amines/guanidines, thereby providing imaging of mobile proteins/peptides. METHODS: We introduced two auxiliary asymmetric analysis metrics that can vary the relative contributions from amine/guanidinium CEST and other effects. By comparing these metrics with the conventional asymmetric analysis metric on healthy rat brains, we can approximately assess the contribution from amines/guanidines to APTw and determine whether the APT dominates over the rNOE effect. To further investigate the molecular origin of APTw, we used samples of dialyzed tissue homogenates to eliminate small metabolites and supernatants of homogenates to separate lipids from other components. RESULTS: When the APTw signal is positive using high saturation amplitudes (e.g., 2-3 µT), the contributions from amines/guanidines are significant and cannot be ignored. The APTw signal from the dialyzed homogenates and the controls has negligible changes, indicating that it primarily originates from macromolecules rather than small metabolites. Additionally, the APTw signals with low saturation amplitudes (e.g., 1 µT) were negative in tissue homogenates but positive in their supernatants, suggesting that proteins contribute positively to APTw signals, whereas lipids contribute negatively to it. CONCLUSION: The positive APTw signal using high saturation amplitudes could have significant contributions from soluble proteins through CEST, including amide/amine/guanidine proton transfer effects. In contrast, the negative APTw signal using low saturation amplitudes has significant contribution from lipids through rNOE.

B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T.

PURPOSE: CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model. METHODS: Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 µT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/ B 1 2 $$ {B}_1^2 $$ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach. RESULTS: B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices. CONCLUSION: The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

Quasi-steady-state (QUASS) reconstruction enhances T1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T1 correction in quantitative CEST MRI of rodent brain tumor models.

PURPOSE: The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions. THEORY AND METHODS: Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction. RESULTS: Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other. CONCLUSIONS: AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.

Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods. METHOD: The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of one-dimensional convolutions, nonlinearity applications, and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis-processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric. RESULTS: In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirm the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared with other methods. Although no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings. CONCLUSION: The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared with other methods.

AlgU mediates hyperosmotic tolerance in Pseudomonas protegens SN15-2 by regulating membrane stability, ROS scavenging, and osmolyte synthesis.

Pseudomonas protegens can serve as an agricultural biocontrol agent. P. protegens often encounters hyperosmotic stress during industrial production and field application. The ability of P. protegens to withstand hyperosmotic stress is important for its application as a biocontrol agent. AlgU is a global regulator responsible for stress response and biocontrol ability. However, the specific regulatory role of AlgU in the hyperosmotic adaptation of P. protegens is poorly understood. In this study, we found that the AlgU mutation disrupted the hyperosmotic tolerance of P. protegens. Many genes and metabolites related to cell envelope formation were significantly downregulated in ΔalgU compared with that in the wild-type (WT) strain under hyperosmotic conditions, and we found that the algU mutation caused membrane integrity to be compromised and increased membrane permeability. Further experiments revealed that the cell envelope integrity protein TolA, which is regulated by AlgU, contributes to cell membrane stability and osmotic tolerance in P. protegens. In addition, several genes related to oxidative stress response were significantly downregulated in ΔalgU, and higher levels of intracellular reactive oxygen species were found in ΔalgU. Furthermore, we found that the synthesis of N-acetyl glutaminyl glutamine amide is directly regulated by AlgU and contributes to the hyperosmotic adaptation of P. protegens. This study revealed the mechanisms of AlgU's participation in osmotic tolerance in P. protegens, and it provides potential molecular targets for research on the hyperosmotic adaptation of P. protegens.IMPORTANCEIn this study, we found that the extracytoplasmic function sigma factor AlgU is essential for the survival of P. protegens under hyperosmotic conditions. We provided evidence supporting the roles of AlgU in influencing cell membrane stability, intracellular reactive oxygen species (ROS) accumulation, and dipeptide N-acetylglutaminylglutamine amide (NAGGN) synthesis in P. protegens under hyperosmotic conditions. Our findings revealed the mechanisms of AlgU's participation in hyperosmotic stress tolerance in P. protegens, and they provide potential molecular targets for research on the hyperosmotic adaptation of P. protegens, which is of value in improving the biocontrol ability of P. protegens.

A bioinspired approach for the modulation of electroosmotic flow and protein-surface interactions in capillary electrophoresis using silylated amino-amides blocks and covalent grafting.

We explore a bioinspired approach to design tailored functionalized capillary electrophoresis (CE) surfaces based on covalent grafting for biomolecules analysis. First, the approach aims to overcome well-known common obstacles in CE protein analysis affecting considerably the CE performance (asymmetry, resolution, and repeatability) such as the unspecific adsorption on fused silica surface and the lack of control of electroosmotic flow (EOF). Then, our approach, which relies on new amino-amide mimic hybrid precursors synthesized by silylation of amino-amides (Si-AA) derivatives with 3-isocyanatopropyltriethoxysilane, aims to recapitulate the diversity of protein-protein interactions (π-π stacking, ionic, Van der Waals…) found in physiological condition (bioinspired approach) to improve the performance of CE protein analysis (electrochromatography). As a proof of concept, these silylated Si-AA (tyrosinamide silylation, serinamide silylation, argininamide silylation, leucinamide silylation, and isoglutamine silylation acid) have been covalently grafted in physiological conditions in different amount on bare fused silica capillary giving rise to a biomimetic coating and allowing both the modulation of EOF and protein-surface interactions. The analytical performances of amino-amide functionalized capillaries were assessed using lysozyme, cytochrome C and ribonuclease A and compared to traditional capillary coatings poly(ethylene oxide), poly(diallyldimethylammonium chloride), and sodium poly(styrenesulfonate). EOF, protein adsorption rate, protein retention factor k, and selectivity were determined for each coating. All results obtained showed this approach allowed to modulate the EOF, reduce unspecific adsorption, and generate specific interactions with proteins by varying the nature and the amount of Si-AA in the functionalization mixture.

Amide proton transfer weighted imaging in pediatric neuro-oncology: initial experience.

Amide proton transfer weighted (APTw) imaging enables in vivo assessment of tissue-bound mobile proteins and peptides through the detection of chemical exchange saturation transfer. Promising applications of APTw imaging have been shown in adult brain tumors. As pediatric brain tumors differ from their adult counterparts, we investigate the radiological appearance of pediatric brain tumors on APTw imaging. APTw imaging was conducted at 3 T. APTw maps were calculated using magnetization transfer ratio asymmetry at 3.5 ppm. First, the repeatability of APTw imaging was assessed in a phantom and in five healthy volunteers by calculating the within-subject coefficient of variation (wCV). APTw images of pediatric brain tumor patients were analyzed retrospectively. APTw levels were compared between solid tumor tissue and normal-appearing white matter (NAWM) and between pediatric high-grade glioma (pHGG) and pediatric low-grade glioma (pLGG) using t-tests. APTw maps were repeatable in supratentorial and infratentorial brain regions (wCV ranged from 11% to 39%), except those from the pontine region (wCV between 39% and 50%). APTw images of 23 children with brain tumor were analyzed (mean age 12 years ± 5, 12 male). Significantly higher APTw values are present in tumor compared with NAWM for both pHGG and pLGG (p < 0.05). APTw values were higher in pLGG subtype pilocytic astrocytoma compared with other pLGG subtypes (p < 0.05). Non-invasive characterization of pediatric brain tumor biology with APTw imaging could aid the radiologist in clinical decision-making.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Photoredox Catalytic Access to N,O-Acetals from Enamides by Means of Electron-Poor Perylene Bisimides.

N,O-acetals are found as structural motifs in natural products and are important synthetic precursors for N-acylimines as building blocks in organic synthesis for C-C-bond formation and amines. For the synthesis of N,O-acetals, an acid-, base- and metal-free catalytic method is reported applying N,N-di-(2,6-diisopropyl)-1,7-dicyano-perylen-3,4,9,10-tetracarboxylic acid imide and N,N-di-(2,6-diisopropyl)-1,6,7,12-tetrabromo-2,5,8,11-tetracyano-perylen-3,4,9,10-tetracarboxylic acid imide as extremely electron-deficient photocatalysts. The first perylene bisimide highly selectively photocatalyzes the formation of the N,O-acetals as products in high yields, and the second and more electron-deficient perylene bisimide allows these reactions without thiophenol as an H-atom transfer reagent. Calculated electron density maps support this. The reaction scope comprises different substituents at the nitrogen of the enamides and different alcohols as starting material. Dehydroalanines are converted to non-natural amino acids which shows the usefulness of this method for organic and medicinal chemistry.

Contemporary Applications of Thioamides and Methods for Their Synthesis.

Thioamides are naturally occurring isosteres of amide bonds in which the chalcogen atom of the carbonyl is changed from oxygen to sulfur. This substitution gives rise to altered nucleophilicity and hydrogen bonding properties with importance for both chemical reactivity and non-covalent interactions. As such, thioamides have been introduced into biologically active compounds to achieve improved target affinity and/or stability towards hydrolytic enzymes but have also been applied as probes of protein and peptide folding and dynamics. Recently, a series of new methods have been developed for the synthesis of thioamides as well as their utilization in peptide chemistry. Further, novel strategies for the incorporation of thioamides into proteins have been developed, enabling both structural and functional studies to be performed. In this Review, we highlight the recent developments in the preparation of thioamides and their applications for peptide modification and study of protein function.