Toxic benthic cyanobacterial mats have been identified globally as a potential health hazard since they can produce potent cyanotoxins. Such mats have…

Peptides are highly selective organocatalysts, with intrinsic modularity allowing precise control over structure and function. Advances in peptide synthesis, biotechnology, and cheminformatics will en...

Antibiotic resistance presents a growing global health crisis, demanding new therapeutic strategies that target novel bacterial mechanisms. Recent advances in protein structure prediction and machine ...

A novel family of antibiotics, MDN-0057 to MDN-0060 (1–4), was isolated from liquid cultures of the fungus Ophiosphaerella korrae. These compounds incorporate two isocyanide groups in their complex structures that were elucidated by extensive spectroscopic analyses, including HRESIMS, and 1D and 2D NMR experiments. The relative configurations were determined by using J-based configuration analyses and the interpretation of key NOESY correlations consistent with the existence of a major conformation in solution. Mosher ester derivatization analysis allowed the establishment of their absolute configurations. All four compounds displayed in vitro antibacterial activity with a broad spectrum against Gram-negative pathogens.

Flow cytometry has great potential for screening in translational research areas due to its deep quantification of cellular features, ability to colle…

Nature - A new lasso peptide antibiotic exhibits broad-spectrum activity against Gram-negative and Gram-positive bacteria by interfering with bacterial protein synthesis, is unaffected by common...

The discovery of penicillin dates back to 1928. And since then, antibiotics have contributed to saving millions of lives all over the world, extending the average duration of human life by 23 years. I...

Scientific Reports - Dereplication of secondary metabolites from Sophora flavescens using an LC–MS/MS-based molecular networking strategy

The clustering of tandem mass spectra (MS/MS) is a crucial computational step to deduplicate repeated acquisitions in data-dependent experiments. This technique is essential in untargeted metabolomics, particularly with high-throughput mass spectrometers capable of generating hundreds of MS/MS spectra per second. Despite advancements in MS/MS clustering algorithms in proteomics, their performance in metabolomics has not been extensively evaluated due to the lack of database search tools with false discovery rate control for molecule identification. To bridge this gap, this study introduces the MS1-retention time (MS-RT) method to assess MS/MS clustering performance in metabolomics data sets. Here, we validate MS-RT by comparing MS-RT to established proteomics clustering evaluation approaches that utilize database search identifications. Additionally, we evaluate the performance of several MS/MS clustering tools on metabolomics data sets, highlighting their advantages and drawbacks. This MS-RT method and the MS/MS clustering tool benchmarking will provide valuable real world practical recommendations for tools and set the stage for future advancements in metabolomics MS/MS clustering.