Rapid Peptide Cyclization Inspired by the Modular Logic of Nonribosomal Peptide Synthetases.

Nonribosomal cyclic peptides (NRcPs) are structurally complex natural products and a vital pool of therapeutics, particularly antibiotics. Their structural diversity arises from the ability of the multidomain enzyme assembly lines, nonribosomal peptide synthetases (NRPSs), to utilize bespoke nonproteinogenic amino acids, modify the linear peptide during elongation, and catalyze an array of cyclization modes, e.g., head to tail, side chain to tail. The study and drug development of NRcPs are often limited by a lack of easy synthetic access to NRcPs and their analogues, with selective macrolactamization being a major bottleneck. Herein, we report a generally applicable chemical macrocyclization method of unprecedented speed and selectivity. Inspired by biosynthetic cyclization, it combines the deprotected linear biosynthetic precursor peptide sequence with a highly reactive C-terminus to produce NRcPs and analogues in minutes. The method was applied to several NRcPs of varying sequences, ring sizes, and cyclization modes including rufomycin, colistin, and gramicidin S with comparable success. We thus demonstrate that the linear order of modules in NRPS enzymes that determines peptide sequence encodes the key structural information to produce peptides conformationally biased toward macrocyclization. To fully exploit this conformational bias synthetically, a highly reactive C-terminal acyl azide is also required, alongside carefully balanced pH and solvent conditions. This allows for consistent, facile cyclization of exceptional speed, selectivity, and atom efficiency. This exciting macrolactamization method represents a new enabling technology for the biosynthetic study of NRcPs and their development as therapeutics.

Eddy Current Array for Defect Detection in Finely Grooved Structure Using MSTSA Network.

In this paper, we focus on eddy current array (ECA) technology for defect detection in finely grooved structures of spinning cylinders, which are significantly affected by surface texture interference, lift-off distance, and mechanical dither. Unlike a single eddy current coil, an ECA, which arranges multiple eddy current coils in a specific configuration, offers not only higher accuracy and efficiency for defect detection but also the inherent properties of space and time for signal acquisition. To efficiently detect defects in finely grooved structures, we introduce a spatiotemporal self-attention mechanism to ECA testing, enabling the detection of defects of various sizes. We propose a Multi-scale SpatioTemporal Self-Attention Network for defect detection, called MSTSA-Net. In our framework, Temporal Attention (TA) and Spatial Attention (SA) blocks are incorporated to capture the spatiotemporal features of defects. Depth-wise and point-wise convolutions are utilized to compute channel weights and spatial weights for self-attention, respectively. Multi-scale features of space and time are extracted separately in a pyramid manner and then fused to regress the bounding boxes and confidence levels of defects. Experimental results show that the proposed method significantly outperforms not only traditional image processing methods but also state-of-the-art models, such as YOLOv3-SPP and Faster R-CNN, with fewer parameters and lower FLOPs in terms of Recall and F1 score.

Production of copropophyrin III, biliverdin and bilirubin by the rufomycin producer, Streptomyces atratus.

Heme is best known for its role as a versatile prosthetic group in prokaryotic and eukaryotic proteins with diverse biological functions including gas and electron transport, as well as a wide array of redox chemistry. However, free heme and related tetrapyrroles also have important roles in the cell. In several bacterial strains, heme biosynthetic precursors and degradation products have been proposed to function as signaling molecules, ion chelators, antioxidants and photoprotectants. While the uptake and degradation of heme by bacterial pathogens is well studied, less is understood about the physiological role of these processes and their products in non-pathogenic bacteria. Streptomyces are slow growing soil bacteria known for their extraordinary capacity to produce complex secondary metabolites, particularly many clinically used antibiotics. Here we report the unambiguous identification of three tetrapyrrole metabolites from heme metabolism, coproporphyrin III, biliverdin and bilirubin, in culture extracts of the rufomycin antibiotic producing Streptomyces atratus DSM41673. We propose that biliverdin and bilirubin may combat oxidative stress induced by nitric oxide production during rufomycin biosynthesis, and indicate the genes involved in their production. This is, to our knowledge, the first report of the production of all three of these tetrapyrroles by a Streptomycete.

Redesigning Enzymes for Biocatalysis: Exploiting Structural Understanding for Improved Selectivity.

The discovery of new enzymes, alongside the push to make chemical processes more sustainable, has resulted in increased industrial interest in the use of biocatalytic processes to produce high-value and chiral precursor chemicals. Huge strides in protein engineering methodology and in silico tools have facilitated significant progress in the discovery and production of enzymes for biocatalytic processes. However, there are significant gaps in our knowledge of the relationship between enzyme structure and function. This has demonstrated the need for improved computational methods to model mechanisms and understand structure dynamics. Here, we explore efforts to rationally modify enzymes toward changing aspects of their catalyzed chemistry. We highlight examples of enzymes where links between enzyme function and structure have been made, thus enabling rational changes to the enzyme structure to give predictable chemical outcomes. We look at future directions the field could take and the technologies that will enable it.