A new member of the fusaricidin family - structure elucidation and synthesis of fusaricidin E.

Two hitherto unknown fusaricidins were obtained from fermentation broths of three Paenibacillus strains. After structure elucidation based on tandem mass spectrometry and NMR spectroscopy, fusaricidin E was synthesized to confirm the structure and the suggested stereochemistry. The synthesis was based on a new strategy which includes an efficient access to the 15-guanidino-3-hydroxypentadecanoyl (GHPD) side chain from erucamide.

Agrochemical Lessons for Infectious Disease Research: New Resistance Breaking Antifungal Hits against Candida auris.

Analysis of the history of the invention of the block-buster antifungal drug Fluconazole underscores the importance of agrochemical research on drug discovery and development. The multidrug resistant fungal pathogen Candida auris is now responsible for serious morbidity and mortality among immuno-compromised and long-term resident hospital patients globally. New drugs against C. auris are urgently needed. A focused screening of 1487 fungicides from the BASF agrochemical collection gave several potent inhibitors of C. auris with yet noncommercialized modes of action. The hits showed only minor activity loss against the azole-resistant C. auris strain CDC 0385 and low to moderate cytotoxicity to human HepG2 cells. Aminopyrimidine 4 showed high activity against resistant strains and selectivity in a HepG2 cells assay and is a potential hit candidate for further optimization.

A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes.

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in the development of optimized small-molecule compounds. Current approaches cannot identify the protein targets of a compound and also detect the interaction surfaces between ligands and protein targets without prior labeling or modification. To address this limitation, we here develop LiP-Quant, a drug target deconvolution pipeline based on limited proteolysis coupled with mass spectrometry that works across species, including in human cells. We use machine learning to discern features indicative of drug binding and integrate them into a single score to identify protein targets of small molecules and approximate their binding sites. We demonstrate drug target identification across compound classes, including drugs targeting kinases, phosphatases and membrane proteins. LiP-Quant estimates the half maximal effective concentration of compound binding sites in whole cell lysates, correctly discriminating drug binding to homologous proteins and identifying the so far unknown targets of a fungicide research compound.

Identification of 1,3-diiminoisoindoline carbohydrazides as potential antimalarial candidates.

A series of inhibitors of plant enzymes of the non-mevalonate pathway from herbicide research efforts at BASF were screened for antimalarial activity in a cell-based assay. A 1,3-diiminoisoindoline carbohydrazide was found to inhibit the growth of Plasmodium falciparum with an IC(50) value <100 nM. Synthesis of a variety of derivatives allowed an improvement of the initial antimalarial activity down to IC(50) =18 nM for the most potent compound, the establishment of a structure-activity relationship, and the evaluation of the cytotoxic profile of the diiminoisoindolines. Furthermore, interesting configurational and conformational aspects for this class of compounds were studied by computational and X-ray crystal structure analysis. Some of the compounds can act as tridentate ligands, forming 2:1 ligand-iron(III) complexes, which also display antimalarial activity in the nanomolar IC(50) range, paired with low cytotoxicity.