Pseudomonas
CLiPs are ubiquitous specialized metabolites, impacting the producer’s lifestyle and interactions with the (a)biotic environment. Consequently, they generate interest for agricultural and clinical applications.
Cyclic lipodepsipeptides or CLiPs from Pseudomonas are secondary metabolites that mediate a wide range of biological functions for their producers, and display antimicrobial and anticancer activities. Direct interaction of CLiPs with the cellular membranes is presumed to be essential in causing these. To understand the processes involved at the molecular level, knowledge of the conformation and dynamics of CLiPs at the water-lipid interface is required to guide the interpretation of biophysical investigations in model membrane systems. We used NMR and molecular dynamics to study the conformation, location and orientation of the Pseudomonas CLiP viscosinamide in a water/dodecylphosphocholine solution. In the process, we demonstrate the strong added value of combining uniform, isotope-enriched viscosinamide and protein NMR methods. In particular, the use of techniques to determine backbone dihedral angles and detect and identify long-lived hydrogen bonds, establishes that the solution conformation previously determined in acetonitrile is maintained in water/dodecylphosphocholine solution. Paramagnetic relaxation enhancements pinpoint viscosinamide near the water-lipid interface, with its orientation dictated by the amphipathic distribution of hydrophobic and hydrophilic residues. Finally, the experimental observations are supported by molecular dynamics simulations. Thus a firm structural basis is now available for interpreting biophysical and bioactivity data relating to this class of compounds.
Long-range intramolecular vibrational energy redistribution (IVR) driven conformational changes were investigated in a matrix-isolated open-chain, asymmetrical dicarboxylic acid, E-glutaconic acid. Although the analysis was challenging due to the presence of multiple backbone conformers and short lifetimes of the prepared higher energy cis conformers, it was shown that the selective excitation of the O-H stretching overtone of one of the carboxylic groups can induce the conformational change (trans to cis) of the other carboxylic group, located at the other end of the E-glutaconic acid molecule. This is a direct proof that the IVR process can act through eight covalent bonds in a flexible molecule before the excess energy completely dissipates into the matrix. The lifetime of the prepared higher energy conformers (averaged over the different backbones) was measured to be 12 s.
Cyclic lipopeptides (CLiPs) are secondary metabolites secreted by a range of bacterial phyla. CLiPs display diverse structural variations in terms of the number of the amino acid residues, macrocycle size, amino acid identity and stereochemistry (e.g. D- vs. L-amino acids). Reports detailing the discovery of novel or already characterized CLiPs from new sources appear regularly in literature. However, in some cases, the lack of characterization detail threatens to cause considerable confusion, especially if configurational heterogeneity is present for one or more amino acids. The NMR fingerprint matching approach introduced in this work exploits the fact that the 1H and 13C NMR chemical shift fingerprint is sufficiently sensitive to differentiate the diastereomers of a particular CLiP even when they only differ in a single D/L configuration. This provides a means for a fast screening to determine whether an extracted CLiP has been reported before, by simply comparing the fingerprint of a novel CLiP with that of a reference CLiP. Even when the stereochemistry of a particular reference CLiP is unknown, the NMR fingerprint approach still allows to verify whether a CLiP from a novel source is identical to the reference. To facilitate this, we have made a publicly available knowledge base at https://www.rhizoclip.be, where we present an overview of published NMR fingerprint data of characterized CLiPs, together with literature data on the originally determined structures. The latter includes a description of the CLiPs original description, molecular mass, three dimensional structures (if available), and a summary of published antimicrobial activities. Moreover, a detailed protocol will be made available for researchers that wish to record NMR data of their newly extracted lipopeptides to compare them to the publicly available reference data.
Semiconductor manufacturing is a notoriously complex and costly multi-step process involving a long sequence of operations on expensive and quantity-limited equipment. Recent chip shortages and their impacts have highlighted the importance of semiconductors in the global supply chains and how reliant on those our daily lives are. Due to the investment cost, environmental impact, and time scale needed to build new factories, it is difficult to ramp up production when demand spikes. This work introduces a method to successfully learn to schedule a semiconductor manufacturing facility more efficiently using deep reinforcement and self-supervised learning. We propose the first adaptive scheduling approach to handle complex, continuous, stochastic, dynamic, modern semiconductor manufacturing models. Our method outperforms the traditional hierarchical dispatching strategies typically used in semiconductor manufacturing plants, substantially reducing each order's tardiness and time until completion. As a result, our method yields a better allocation of resources in the semiconductor manufacturing process.
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