Drug screening articles from across Nature Portfolio

A new engineering strategy for improving the biosynthesis of secondary metabolites in Streptomyces has been developed through the analysis of genes co-evolved with biosynthetic gene clusters. This strategy has been verified in 11 Streptomyces strains to enhance production of 16,385 metabolites, showing potential applications in drug discovery and industrial production.

NanoLuciferase- and HaloTag-based screening technologies are versatile tools suitable for the live-cell analysis of the entire small-molecule-induced degradation cascade to uncover the mode of action of proximity-inducing compounds such as PROTACs.

Biological assays are essential to pharmaceutical, agrochemical and cosmetics research. However, false readouts pose substantial challenges in screening small molecules. This Review explores the current methods for tackling assay interference, focusing on computational approaches and their integration with experimental methods.

A new engineering strategy for improving the biosynthesis of secondary metabolites in Streptomyces has been developed through the analysis of genes co-evolved with biosynthetic gene clusters. This strategy has been verified in 11 Streptomyces strains to enhance production of 16,385 metabolites, showing potential applications in drug discovery and industrial production.

A protein-templated selection approach has been developed for the discovery of full ligands from dual-pharmacophore DNA-encoded libraries by incorporating fragment linking into the selection process. The performance of this method was demonstrated with selections against protein–protein interaction and protein–DNA interaction targets, through which potent and selective inhibitors were identified.

Cyclic peptides can bind challenging disease targets, but their oral application is hindered by digestion and absorption issues. We developed a versatile method for the synthesis and functional screening of vast numbers of synthetic cyclic peptides and identified peptides with high inhibitory activity, stability and oral bioavailability in rats.

Computational approaches are emerging as powerful tools for the discovery of antibiotics. A study now uses machine learning to discover abaucin, a potent antibiotic that targets the bacterial pathogen Acinetobacter baumannii.

Deep learning approaches have potential to substantially reduce the astronomical costs and long timescales involved in drug discovery. KarmaDock proposes a deep learning workflow for ligand docking that shows improved performance against both benchmark cases and in a real-world virtual screening experiment.

The plasma of individuals with atherosclerosis contains cytokines that induce a pathogenic signaling cascade in immune cells. Saracatinib, a dual kinase inhibitor that targets the tyrosine kinases SRC and BCR-ABL, can prevent activation of this phospho-signaling pathway implicated in the pathogenesis of cardiovascular disease.