Model peptide studies of Ag+ binding sites from the silver resistance protein SilE

Using model peptides, each of the nine MX2H or HXnM (n = 1, 2) motifs of the silver resistance protein SilE has been shown to coordinate to one Ag+ ion by its histidine and methionine residues with Kd in the μM range. This suggests an Ag+ buffering role for SilE in the case of high Ag+ overload

Conformational Exchange Processes in Biological Systems: Detection by Solid-State NMR

International audienceWe review recent advances in methodologies to study microseconds-to-milliseconds exchange processes in biological molecules using magic-angle spinning solid-state nuclear magnetic resonance (MAS ssNMR) spectroscopy. The particularities of MAS ssNMR, as compared to solution-state NMR, are elucidated using numerical simulations and experimental data. These simulations reveal the potential of MAS NMR to provide detailed insight into short-lived conformations of biological molecules. Recent studies of conformational exchange dynamics in microcrystalline ubiquitin are discussed

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Studying Dynamics by Magic-Angle Spinning Solid-State NMR Spectroscopy: Principles and Applications to Biomolecules

International audienceMagic-angle spinning solid-state NMR spectroscopy is an important technique to study mo- lecular structure, dynamics and interactions, and is rapidly gaining importance in biomolecu- lar sciences. Here we provide an overview of experimental approaches to study molecular dy- namics by MAS solid-state NMR, with an emphasis on the underlying theoretical concepts and differences of MAS solid-state NMR compared to solution-state NMR. The theoretical foundations of nuclear spin relaxation are revisited, focusing on the particularities of spin re- laxation in solid samples under magic-angle spinning. We discuss the range of validity of Redfield theory, as well as the inherent multi-exponential behavior of relaxation in solids. Ex- perimental challenges for measuring relaxation parameters in MAS solid-state NMR and a few recently proposed relaxation approaches are discussed, which provide information about time scales and amplitudes of motions ranging from picoseconds to milliseconds. We also discuss the theoretical basis and experimental measurements of anisotropic interactions (chemical-shift anisotropies, dipolar and quadrupolar couplings), which give direct infor- mation about the amplitude of motions. The potential of combining relaxation data with such measurements of dynamically-averaged anisotropic interactions is discussed. Although the focus of this review is on the theoretical foundations of dynamics studies rather than their ap- plication, we close by discussing a small number of recent dynamics studies, where the dy- namic properties of proteins in crystals are compared to those in solution

Divide, conquer and reconstruct: How to solve the 3D structure of recalcitrant Micro-Exon Gene (MEG) protein from Schistosoma mansoni

Micro-Exon Genes are a widespread class of genes known for their high variability, widespread in the genome of parasitic trematodes such as Schistosoma mansoni. In this study, we present a strategy that allowed us to solve the structures of three alternatively spliced isoforms from the Schistoma mansoni MEG 2.1 family for the first time. All isoforms are hydrophobic, intrinsically disordered, and recalcitrant to be expressed in high yield in heterologous hosts. We resorted to the chemical synthesis of shorter pieces, before reconstructing the entire sequence. Here, we show that isoform 1 partially folds in a-helix in the presence of trifluoroethanol while isoform 2 features two rigid elbows, that maintain the peptide as disordered, preventing any structuring. Finally, isoform 3 is dominated by the signal peptide, which folds into a-helix. We demonstrated that combining biophysical techniques, like circular dichroism and nuclear magnetic resonance at natural abundance, with in silico molecular dynamics simulation for isoform 1 only, was the key to solve the structure of MEG 2.1. Our results provide a crucial piece to the puzzle of this elusive and highly variable class of proteins

Alpha-helical folding of SilE models upon Ag(His)(Met) motif formation

The SilE protein is suspected to have a prominent role in Ag+ detoxification of silver resistant bacteria. Using model peptides, we elucidated both qualitative and quantitative aspects of the Ag+-induced α-helical structuring role of His- and Met-rich sequences of SilE, improving our understanding of its function within the Sil system

Structural constraints for the Crh protein from solid-state NMR experiments

We demonstrate that short, medium and long-range constraints can be extracted from proton mediated, rare-spin detected correlation solid-state NMR experiments for the microcrystalline 10.4 × 2 kDa dimeric model protein Crh. Magnetization build-up curves from cross signals in NHHC and CHHC spectra deliver detailed information on side chain conformers and secondary structure for interactions between spin pairs. A large number of medium and long-range correlations can be observed in the spectra, and an analysis of the resolved signals reveals that the constraints cover the entire sequence, also including inter-monomer contacts between the two molecules forming the domain-swapped Crh dimer. Dynamic behavior is shown to have an impact on cross signals intensities, as indicated for mobile residues or regions by contacts predicted from the crystal structure, but absent in the spectra. Our work validates strategies involving proton distance measurements for large and complex proteins as the Crh dimer, and confirms the magnetization transfer properties previously described for small molecules in solid protein samples

Contribution au suivi de l'état de santé de module de puissance à base de MOSFET SiC

More electrical aircraft requires power modules of higher performances, especially in terms of reliability with a control of lifetime. The replacement of hydraulic and pneumatic systems by electric actuators and their associated converters is the present trend to reduce maintenance cost and fuel consumption. Adding more electric components is also thought as a good way to increase reliability in systems. Reliability is still analysed from accelerated stress cycles. A large volume of data must be obtained in various conditions to assert a pertinent extrapolation of remaining lifetime during operation. A trend is to embed some condition monitoring functions in power modules to help predict the remaining lifetime. This approach is the field of hardware developments with respect to sensors and decorrelation methods but mainly dedicated to one particular failure. This thesis presents a learning approach of silicon carbide MOSFET based power modules condition monitoring. A large literature study has led to the elaboration of a test plan and an instrumented test bench. This test bench allows an accelerated lifespan of power module and an on-line recording of several electrical parameters. These parameters shows a drift according to the power module ageing. A neural network model based on these parameters drifts has been constructed to estimate the remaining useful lifetime of a power module in normal operationL’avion plus électrique demande des modules de puissances de plus en plus performants dans les domaines de la fiabilité et de la maîtrise de la durée de vie restante. Le remplacement des systèmes hydrauliques et pneumatiques par des actionneurs électriques et leurs convertisseurs associés est, aujourd’hui, un moyen efficace de réduire les coûts de maintenance et la consommation de carburant. L’ajout de composantes électriques est également un bon moyen d’augmenter la fiabilité des systèmes. La fiabilité est toujours étudiée à partir de contraintes cycliques accélérées. La tendance actuelle est d’embarquer des fonctions de suivi de l’état de santé dans les modules de puissance pour permettre la prédiction de la durée de vie restante. Cette approche implique des modifications du circuit afin de mettre en place des capteurs et est souvent dédiée à un mode de défaillance en particulier. Cette thèse propose une approche par apprentissage du suivi de l’état de santé de modules de puissance à base de MOSFET en carbure de silicium. Une large étude bibliographique a permis de créer et de réaliser un banc de test instrumenté permettant de mettre en œuvre des défaillances attendues dans les modules de puissance mais aussi d’enregistrer un grand nombre de paramètres électriques au cours de la vie du module. Ces paramètres montrent une évolution au cours du vieillissement du module en fonction des modes de défaillances. Un modèle de réseaux neuronaux s’appuie sur la dérive de ces paramètres pour établir le pronostic de durée de vie restante d’un module de puissance à chaque instant de son utilisation normal