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A simple but robust strategy of ball milling (20 Hz, 30 Hz for 30 s, 60 s, 120 s, 180 s) was utilized to modify bamboo shoots fiber (BSDF) in shrimp surimi. The water holding capacity, swelling capacity, and oil binding capacity of 30 Hz-60 s milled BSDF exhibited the highest values of 5.61 g/g, 3.13 mL/g, and 6.93 g/g, significantly higher (P < 0.05) than untreated one (3.65 g/g, 2.03 mL/g, 4.57 g/g). Ball-milled BSDF exhibited a small-sized structure with the relative crystallinity decreased from 40.44 % (control) to 11.12 % (30 Hz-180 s). The myosin thermal stability, gelation properties of surimi were significantly enhanced by incorporating 20 Hz-120 s and 30 Hz-60 s BSDF via promoting protein unfolding, covalent hydrophobic interactions, and hydrogen bonding. A matrix-reinforcing and water entrapping effect was observed, exhibiting reinforced networks with down-sized water tunnels. However, BSDF modified at 180 s contributed to over-aggregated networks with fractures and enlarged gaps. Appropriate ball-milled BSDF (20 Hz-120 s, and 30 Hz-60 s) resulted in a significant decrease in α-helix (P < 0.05), accompanied by an increase of ß-sheets and ß-turn. This work could bring some insights into the applications of modified BSDF and its roles in the gelation of surimi-based food.

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In this paper, the objective was to evaluated the impact of germination of chickpea cultivars (Muying1, Y2-514 and YZ-364) on the bioactivity, volatiles and functional properties. The results showed that the Vitamin C content of Muying1, Y2-514 and YZ-364 after germination significantly increased (p < 0.05). Moreover, the germination also caused a significant decrease in lower transition temperatures and enthalpy values in chickpea flours (p < 0.05). After germination treatment, ß-sheet and random coils in protein secondary structures increased and ß-turn decreased in YZ-364; α-helix, ß-sheet and random coil in Y2-514 and Muying1 decreased, while ß-turn increased. The germination significantly enhanced the functional properties of three chickpea flours (p < 0.05). It was proved that the germination significantly enhanced the total phenolic and flavonoids content, antioxidant activity and in vitro protein digestibility. The GC-IMS revealed that the germination could affect the contents of volatile compounds of chickpea flours.

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The application of magnetic fields (MFs) and magnetic particles (MPs) in water treatment has attracted widespread attention due to their stability, strong biological compatibility, and less chemical consumption. This study introduced MPs and MFs to GDM and probed their effects on filtration performance. Predeposited large MPs (P-large) and batch-added little MPs (B-little) intervened biocake layer development, forming more open and porous structures, they also reduced biomass secretion, resulting in flux increases of 13 % in P-large and 40 % in B-little than P-little, respectively. Besides, MFs controlled MPs distribution on the biocake layer, resulting in forming of more rough and open structures. A relatively lower magnetic field of 20 mT facilitated biomass secretion, while a higher magnetic field of 50 mT decreased biomass. Furthermore, applying magnetic fields decreased the ratios of α-helix and ß-sheet, and increased random coil percentage. Thus, applying magnetic field mediation would contribute to the flux improvements in I-20 and I-50 by 29 % and 32 % relative to I-0. Economic analysis suggested introducing MPs and MFs to GDM was economically feasible, synergy of MPs and MFs had more economic advantages on the community scale and MPs-assisted GDM had significant economic advantages on both community and household scales. Future works should focus on developing new technologies for the recycling of MPs and membranes. This study provided new insight into the protein secondary structures associated with GDM performance and would encourage new sustainable MFs and MPs-assisted GDM technological developments.

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The establishment of stable partial nitrification (PN) is beneficial to promote the application of anaerobic ammonium oxidation, especially for low-ammonium wastewater. This study demonstrated an innovative approach for achieving PN through feeding low-level benzethonium chloride (BZC). PN was started and maintained for 125 days after the sequential feeding of 0.2 and 1 mg/L BZC for 50 days. The damaged PN recovered rapidly within eight days by feeding 2 mg/L BZC, and it thrived for more than 172 days, indicating that nitrite-oxidizing bacteria did not adapt to BZC. The removal of BZC changed from adsorption to degradation gradually. Increased extracellular polymeric substances secretion and altered protein secondary structures explained sludge granulation during BZC feeding, which may be closely related to long-term stable maintenance of PN. PICRUSt2 revealed the underlying microbial mechanisms in depth. Overall, this research proposed a novel scheme to achieve robust PN treating low-ammonium wastewater through feeding low-level BZC.

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OBJECTIVE: The use of conventional microscopy and vibrational spectroscopy in the optical region to investigate the chemical nature of hair fibres on a nanometre scale is frustrated by the diffraction limit of light, prohibiting the spectral elucidation of nanoscale sub-structures that contribute to the bulk properties of hair. The aim of this work was to overcome this limitation and gain unprecedented chemical resolution of cortical cell nano-structure of hair. METHODS: The hybrid technique of AFM-IR, combining atomic force microscopy with an IR laser, circumvents the diffraction limit of light and achieves nanoscale chemical resolution down to the AFM tip radius. In this work, AFM-IR was employed on ultra-thin microtomed cross-sections of human hair fibres to spectrally distinguish and characterize the specific protein structures and environments within the nanoscale components of cortical cells. RESULTS: At first, a topographical and chemical distinction between the macrofibrils and the surrounding intermacrofibillar matrix was achieved based on 2.5 × 2.5 µm maps of cortical cell cross-sections. It was found that the intermacrofibrillar matrix has a large protein content and specific cysteine-related residues, whereas the macrofibrils showed bigger contributions from aliphatic amino acid residues and acidic-/ester-containing species (e.g. lipids). Localized spectra recorded at a spatial resolution of the order of the AFM tip radius enabled the chemical composition of each region to be determined following deconvolution of the Amide-I and Amide-II bands. This provided specific evidence for a greater proportion of α-helices in the macrofibrils and correspondingly larger contributions of ß-sheet secondary structures in the intermacrofibrillar matrix, as inferred in earlier studies. Analysis of the parallel and antiparallel ß-sheet structures, and of selected dominant amino acid residues, yielded further novel composition and conformation results for both regions. CONCLUSION: In this work, we overcome the diffraction limit of light using atomic force microscopy integrated with IR laser spectroscopy (AFM-IR) to characterize sub-micron features of the hair cortex at ultra-high spatial resolution. The resulting spectral analysis shows clear distinctions in the Amide bands in the macrofibrils and surrounding intermacrofibrillar matrix, yielding novel insight into the molecular structure and intermolecular stabilization interactions of the constituent proteins within each cortical component.

OBJECTIF: L'utilisation de la microscopie conventionnelle et de la spectroscopie vibratoire dans la région optique pour étudier la nature chimique des fibres capillaires à l'échelle nanométrique est limitée par la limite de diffraction de la lumière, interdisant l'élucidation spectrale des sous-structures à l'échelle nanométrique qui contribuent aux propriétés des cheveux en général. L'objectif de ce travail était de surmonter cette limitation et d'obtenir une résolution chimique sans précédent de la nanostructure cellulaire corticale des cheveux. MÉTHODES: La technique hybride de l'AFM-IR, combinant la microscopie à force atomique avec un laser IR, contourne la limite de diffraction de la lumière et permet d'obtenir une résolution chimique à l'échelle nanométrique jusqu'au rayon de l'extrémité de l'AFM. Dans ce travail, l'AFM-IR a été employée sur des coupes transversales microtomes ultrafines de fibres de cheveux humains pour distinguer et caractériser sur le plan spectral les structures et environnements protéiques spécifiques au sein des composants à l'échelle nanométrique des cellules corticales. RÉSULTATS: Tout d'abord, une distinction topographique et chimique entre les macrofibrilles et la matrice intermacrofibrillaire environnante a été obtenue à partir de cartes de 2,5 × 2,5 micromètres des coupes transversales des cellules corticales. Il a été constaté que la matrice intermacrofibrillaire avait une grande teneur en protéines et des résidus spécifiques liés à la cystéine, tandis que les macrofibrilles présentaient des contributions plus importantes provenant de résidus d'acides aminés aliphatiques et d'espèces acides/contenant des esters (p. ex. lipides). Les spectres localisés enregistrés à une résolution spatiale de l'ordre du rayon de l'extrémité AFM ont permis de déterminer la composition chimique de chaque région suite à la déconvolution des bandes Amide-I et Amide-II. Cela a apporté des preuves spécifiques pour une plus grande proportion des hélices alpha des macrofibrilles, de même que des contributions plus importantes des structures secondaires à feuillet bêta dans la matrice intermacrofibrillaire, déduites dans des études antérieures. L'analyse des structures parallèles et antiparallèles des feuillets bêta, et des résidus d'acides aminés dominants sélectionnés a donné des résultats inédits de composition et de conformation pour les deux régions. CONCLUSION: Dans ce travail, nous avons surmonté la limite de diffraction de la lumière en utilisant la microscopie à force atomique intégrée à la spectroscopie laser IR (IR-AFM) pour caractériser les caractéristiques submicroniques du cortex capillaire à une résolution spatiale ultra-élevée. L'analyse spectrale qui en résulte montre des distinctions nettes dans les bandes d'amide dans les macrofibrilles et la matrice intermacrofibrillaire environnante, ce qui apporte un éclairage nouveau sur la structure moléculaire et les interactions de stabilisation intermoléculaire des protéines constitutives dans chaque composant cortical.

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Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the 1980s, various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by machine learning, have been employed in protein structure assignment. However, the assignment process becomes challenging when missing atoms are present in the protein files. Our method proposed a multi-class classifier program named DLFSA for assigning protein secondary structure elements (SSE) using convolutional neural networks (CNNs). A fast and efficient GPU-based parallel procedure extracts fragments from protein files. The model implemented in this work is trained with a subset of the protein fragments and achieves 88.1% and 82.5% train and test accuracy, respectively. The model uses only Cα coordinates for secondary structure assignments. The model has been successfully tested on a few full-length proteins also. Results from the fragment-based studies demonstrate the feasibility of applying deep learning solutions for structure assignment problems.

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Extracellular polymeric substances (EPS) influence the auto-aggregation performance of cells and play an important role in nitrogen removal during wastewater treatment. In this study, a salt-tolerant aerobic denitrifying bacterium was isolated from tannery wastewater and identified as Pseudomonas sp. DN-23. The strain exhibited significant growth and denitrifying performance, with NaCl contents ranging from 0 to 50 g/L, and high antioxidative enzyme activity, especially that of catalase (CAT), was detected under salt stress. Even greater auto-aggregation ability was observed with elevated NaCl content. Extinction-emission matrix (EEM) and Fourier-transform infrared (FTIR) spectrum analyses showed that the main components of EPS were proteins and polysaccharides. The polysaccharide content was almost unaffected by NaCl stress, while the protein content increased with NaCl stress, and the proteins may play a more important role in auto-aggregation. Analysis of the contents of each protein's secondary structure suggested that ß-Sheets increased with increasing NaCl content, which may be related to the increase of auto-aggregation ability in response to NaCl stress. Therefore, NaCl stress increased the auto-aggregation performance by altering the compositions of EPS and the distribution of protein secondary structures. This study provided further insight into the denitrifying performance, and the relationship between aggregation ability and EPS characteristics under NaCl stress.

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The challenge of deriving quantitative information from the infrared spectra of proteins arises from the large number of secondary structures and amino acid side-chain functional groups that all contribute to the spectral intensity, such as within the amide I band (1600-1700 cm-1). The band is invariably heavily convoluted from overlapping spectral features, thereby making interpretation difficult such that deconvolution is usually required. This work critically examines the methods available to deconvolute the spectra and assesses the commonly used methods and algorithms applied to vibrational spectra for smoothing and peak identification. We show that unless their spectra have very high signal-to-noise ratios, quantitative analysis to decipher protein constituents is not feasible. The advantages and disadvantages of spectral smoothing using adjacent averaging, the Savitzky-Golay filter and the fast Fourier transform filter are examined in detail. The use of derivative spectra to identify peaks is described with particular reference to the influence and reduction of interfering water bands in the amide I region. The reliability of band narrowing techniques such as second-derivative analysis or Fourier deconvolution that lead to the identification of the contributing protein peaks is investigated. Both methods are shown to be limited in their capacity to resolve features with very similar frequencies. Additionally, the presence of narrow bands arising from high-frequency noise whether from atmospheric water vapor, acoustic vibrations, or electrical interference results in both methods becoming increasingly unusable as narrow bands are preferentially enhanced at the expense of broad ones such as the amide I bands. An optimal strategy is critically developed to allow accurate determination and quantification of protein constituents and their conformations. Additionally, quantitative methods are proposed to account for baseline shifts, which would otherwise introduce significant errors in similarity indices.

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Vacuum radio frequency drying (VRFD) combining the advantages of RF heating with vacuum drying (VD) was applied to produce chicken powders. Drying time and some properties of VRFD the powders were compared with VD and microwave vacuum drying (MVD) (915 MHz and 2450 MHz). Results showed that the total drying time of VRFD chicken powders was the shortest (100 min) while that for VD powders was the longest (180 min). VRFD chicken powders exhibited the lowest hygroscopicity (2.17%), the highest water holding capacity (254.80%), and better color and taste. Besides, VRFD powders had maximum umami flavor among the obtained powders. Contrarily, the color and flavor of VD powders were the most undesirable. Additionally, VRFD had less effect on protein secondary structures compared with MVD. It was concluded that, VRFD possesses the necessary potential for use at industrial level in the production of chicken powders with high qualities.

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BACKGROUND: Protein secondary structure can be regarded as an information bridge that links the primary sequence and tertiary structure. Accurate 8-state secondary structure prediction can significantly give more precise and high resolution on structure-based properties analysis. RESULTS: We present a novel deep learning architecture which exploits an integrative synergy of prediction by a convolutional neural network, residual network, and bidirectional recurrent neural network to improve the performance of protein secondary structure prediction. A local block comprised of convolutional filters and original input is designed for capturing local sequence features. The subsequent bidirectional recurrent neural network consisting of gated recurrent units can capture global context features. Furthermore, the residual network can improve the information flow between the hidden layers and the cascaded recurrent neural network. Our proposed deep network achieved 71.4% accuracy on the benchmark CB513 dataset for the 8-state prediction; and the ensemble learning by our model achieved 74% accuracy. Our model generalization capability is also evaluated on other three independent datasets CASP10, CASP11 and CASP12 for both 8- and 3-state prediction. These prediction performances are superior to the state-of-the-art methods. CONCLUSION: Our experiment demonstrates that it is a valuable method for predicting protein secondary structure, and capturing local and global features concurrently is very useful in deep learning.

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Circular dichroism (CD) spectroscopy is a widely used technique for the evaluation of protein secondary structures that has a significant impact for the understanding of molecular biology. However, the quantitative analysis of protein secondary structures based on CD spectra is still a hard work due to the serious overlap of the spectra corresponding to different structural motifs. Here, Tchebichef image moment (TM) approach is introduced for the first time, which can effectively extract the chemical features in CD spectra for the quantitative analysis of protein secondary structures. The proposed approach was applied to analyze reference set and the obtained results were evaluated by the strict statistical parameters such as correlation coefficient, cross-validation correlation coefficient and root mean squared error. Compared with several specialized prediction methods, TM approach provided satisfactory results, especially for turns and unordered structures. Our study indicates that TM approach can be regarded as a feasible tool for the analysis of the secondary structures of proteins based on CD spectra. An available TMs package is provided and can be used directly for secondary structures prediction.

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Enterobacter sp. strain FL was newly isolated from activated sludge and exhibited significant capability of auto-aggregation as well as aerobic denitrification. The removal efficiencies of NO3--N, total nitrogen (TN), and TOC by strain FL in batch culture reached 94.6, 63.9, and 72.5% in 24 h, respectively. The production of N2O and N2 in the presence of oxygen demonstrated the occurrence of aerobic denitrification. The auto-aggregation index of strain FL reached 54.3%, suggesting a high tendency that the cells would agglomerate into aggregates. The production of extracellular polymeric substances (EPSs), which were mainly composed of proteins followed by polysaccharides, was considered to be related to the cell aggregation according to Fourier transform infrared (FT-IR) and confocal laser scanning microscopy (CLSM). The proteins in EPS were evenly and tightly combined to cells and altered the protein secondary structures of cell surface from random coils to ß-sheets and three-turn helices. The alteration of protein secondary structures of cell surface caused by the proteins in EPS might play a dominant role in the auto-aggregation of strain FL. To further assess the feasibility of strain FL for synthetic wastewater treatment, a sequencing batch reactor (SBR), solely inoculated with strain FL, was conducted. During the 16 running cycles, the removal efficiency of NO3--N was 90.2-99.7% and the auto-aggregation index was stabilized at 35.0-41.5%. The EPS promoted the biomass of strain FL to aggregate in the SBR.

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The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to classify protein secondary structures, but are faced with a significant number of misclassifications. The paper presents a technique for the classification of protein secondary structures based on protein "signal-plotting" and the use of the Fourier technique for digital signal processing. New indices are proposed to classify protein secondary structures by analyzing hydrophobicity profiles. The approach is simple and straightforward. Results show that the more types of protein secondary structures can be classified by means of these newly-proposed indices.

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The exceptional strength and extensibility of spider dragline silk have been thought to be facilitated by two spidroins, major ampullate spidroin 1 (MaSp1) and major ampullate spidroin 2 (MaSp2), under the assumption that protein secondary structures are coupled with the expressed spidroins. We tested this assumption for the dragline silk of three co-existing Australian spiders, Argiope keyserlingi, Latrodectus hasselti and Nephila plumipes. We found that silk amino acid compositions did not differ among spiders collected in May. We extended these analyses temporally and found the amino acid compositions of A. keyserlingi silks to differ when collected in May compared to November, while those of L. hasselti did not. To ascertain whether their secondary structures were decoupled from spidroin expression, we performed solid-state nuclear magnetic resonance spectroscopy (NMR) analysis on the silks of all spiders collected in May. We found the distribution of alanine toward ß-sheet and 3,10helix/random coil conformations differed between species, as did their relative crystallinities, with A. keyserlingi having the greatest 3,10helix/random coil composition and N. plumipes the greatest crystallinity. The protein secondary structures correlated with the mechanical properties for each of the silks better than the amino acid compositions. Our findings suggested that a differential distribution of alanine during spinning could decouple secondary structures from spidroin expression ensuring that silks of desirable mechanical properties are consistently produced. Alternative explanations include the possibility that other spidroins were incorporated into some silks.

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In the present study, interactions of Au(III) and Ga(III) ions on human serum albumin (HSA) were studied comparatively via spectroscopic and thermal analysis methods: UV-vis absorbance spectroscopy, fluorescence spectroscopy, Fourier transform infrared (FT-IR) spectroscopy and isothermal titration calorimetry (ITC). The potential antitumor effects of these ions were studied on MCF-7 cells via Alamar blue assay. It was found that both Au(III) and Ga(III) ions can interact with HSA, however; Au(III) ions interact with HSA more favorably and with a higher affinity. FT-IR second derivative analysis results demonstrated that, high concentrations of both metal ions led to a considerable decrease in the α-helix content of HSA; while Au(III) led to around 5% of decrease in the α-helix content at 200µM, it was around 1% for Ga(III) at the same concentration. Calorimetric analysis gave the binding kinetics of metal-HSA interactions; while the binding affinity (Ka) of Au(III)-HSA binding was around 3.87×10(5)M(-1), it was around 9.68×10(3)M(-1) for Ga(III)-HSA binding. Spectroscopy studies overall suggest that both metal ions have significant effects on the chemical structure of HSA, including the secondary structure alterations. Antitumor activity studies on MCF7 tumor cell line with both metal ions revealed that, Au(III) ions have a higher antiproliferative activity compared to Ga(III) ions.

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With climate change, pea will be more frequently subjected to heat stress in semi-arid regions like Saskatchewan during flowering. The pollen germination percentage of two pea cultivars was reduced by heat stress (36°C) with an important decrease in cultivar 'CDC Golden' compared to 'CDC Sage.' Lipids, protein and other pollen coat compositions of whole intact pollen grains of both pea cultivars were investigated using mid infrared (mid-IR) attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. Curve fitting of ATR absorbance spectra in the protein region enabled estimation and comparison of different protein secondary structures between the two cultivars. CDC Sage had relatively greater amounts of α-helical structures (48.6-43.6%; band at 1654 cm(-1)) and smaller amounts of ß-sheets (41.3-46%) than CDC Golden. The CDC Golden had higher amounts of ß-sheets (46.3-51.7%) compared to α-helical structures (35.3-36.2%). Further, heat stress resulted in prominent changes in the symmetrical and asymmetrical CH2 bands from lipid acyl chain, ester carbonyl band, and carbohydrate region. The intensity of asymmetric and symmetric CH2 vibration of heat stressed CDC Golden was reduced considerably in comparison to the control and the decrease was higher compared to CDC Sage. In addition, CDC Golden showed an increase in intensity at the oxidative band of 3015 cm(-1). These results reveal that the whole pollen grains of both pea cultivars responded differently to heat stress. The tolerance of CDC Sage to heat stress (expressed as pollen germination percentage) may be due to its protein richness with α-helical structures which would protect against the destructive effects of dehydration due to heat stress. The low pollen germination percentage of CDC Golden after heat stress may be also due to its sensitivity to lipid changes due to heat stress.

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We review the recent development of chiral sum frequency generation (SFG) spectroscopy and its applications to study chiral vibrational structures at interfaces. This review summarizes observations of chiral SFG signals from various molecular systems and describes the molecular origins of chiral SFG response. It focuses on the chiral vibrational structures of proteins and presents the chiral SFG spectra of proteins at interfaces in the C-H stretch, amide I, and N-H stretch regions. In particular, a combination of chiral amide I and N-H stretches of the peptide backbone provides highly characteristic vibrational signatures, unique to various secondary structures, which demonstrate the capacity of chiral SFG spectroscopy to distinguish protein secondary structures at interfaces. On the basis of these recent developments, we further discuss the advantages of chiral SFG spectroscopy and its potential application in various fields of science and technology. We conclude that chiral SFG spectroscopy can be a new approach to probe chiral vibrational structures of protein at interfaces, providing structural and dynamic information to study in situ and in real time protein structures and dynamics at interfaces.

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Synthetically versatile and easy to carry out, Ring-Closing Metathesis (RCM) constitutes an attractive chemical tool, easily amenable for multiple substrates in mild conditions. In medicinal chemistry, the use of RCM has been especially prolific during the last few years. An important application that has benefited from this reaction is the stabilization of spatial conformations in bioactive peptides, since their 3D arrangements play relevant roles in biomolecular recognition processes. RCM reaction is being widely used to introduce conformational constraints into small peptides, through the generation of cyclic structures from appropriate linear precursors. As an alternative to strategies like disulfide or lactam-bridged cyclizations, RCM shows the additional advantage of generating hydrocarbon bridges, less prone to metabolic degradation, and metabolically more stable, which could benefit their pharmacokinetic properties. Particularly remarkable is the application of RCM to the preparation of small peptide modulators able to mimic epitopes identified as hotspots within the surface contact areas in protein-protein interactions (PPIs). This review deals with the replacement of S-S and thioether linkages of cyclic peptides by C-C-bridges and with the stabilization of peptide secondary architectures (α-helix, ß-hairpins, ß-turns) through RCM, as a useful strategy for the modulation of therapeutically relevant signaling pathways.

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