Structure-based drug design articles from across Nature Portfolio

Fragment-based molecular design uses chemical motifs and combines them into bio-active compounds. While this approach has grown in capability, molecular linker methods are restricted to linking fragments one by one, which makes the search for effective combinations harder. Igashov and colleagues use a conditional diffusion model to link multiple fragments in a one-shot generative process.

Deep learning generative approaches have been used in recent years to discover new molecules with drug-like properties. To improve the performance of such approaches, Yang et al. add chemical binding knowledge to a deep generative framework and demonstrate, including by wet-lab verification, that the method can find valid molecules that successfully bind to target proteins.

Antimicrobial resistance is a global health threat and the development of alternative strategies to overcome it is of high interest. Here, the authors report proteolysis targeting chimeras active in bacteria (BacPROTACs) that bind to ClpC1, a component of the mycobacterial protein degradation machinery, and apply them for targeting a range of mycobacterial strains, including antibiotic-resistant ones.

Bivalent molecules comprising dual functional motifs often exhibit strong target binding, however arriving at the optimal structure is challenging. Here, the authors employ EGFR as a model system for understanding a subtle difference in the linker structure of bivalent inhibitors to enhance binding against drug-resistant EGFR mutants.

Pro-survival B-cell lymphoma-2 (BCL-2) family proteins BCL-2 and BCL-X_L are the targets of anti-tumour drugs, but resistance is emerging. The authors present cyclic peptides against BCL-2 and BCL-X_L, with a distinct mechanism of targeting characterised.

The paper presents the universal QM-based scoring function that accurately and rapidly predicts protein-ligand binding affinities, outperforming current computational tools. This is demonstrated on the PL-REX experimental benchmark dataset.

Developing inhibitors for SH2 domains is challenging due to their shallow pockets and highly charged ligands. Structure-guided drug design has enabled the discovery of a cell-permeable covalent inhibitor of the SOCS2 SH2 domain, a key regulator of cytokine signaling pathways.

By investigating the structure–activity relationship of molecular glue degraders that target cyclin K, we discovered that a wide range of compounds, including known kinase inhibitors, possess this gain-of-function activity. These findings provide insights that might enable more rational design and optimization of molecular glue compounds.

By breaking a clinical candidate into its substructures, fragments with poor bioavailability profiles can be identified, removed and replaced in a compound before entering the laboratory.

Though HER2 (ERBB2) exon 20 insertion mutations occur in ~2% of non-small-cell lung cancers, molecular targeted therapies for such cancers have been lacking. A study now identifies selective HER2 inhibitors that have marked efficacy against tumors driven by HER2 exon 20 insertions, without inhibiting wild-type EGFR activity.

It is extremely difficult to design a broad-spectrum inhibitor for metallo-β-lactamases (MBLs) due to the diversity in the active site. Now, indole-2-carboxylates have been developed as broad-spectrum inhibitors for MBLs. These inhibitors take advantage of key elements of both MBL substrates and products and work by locking a hydroxide.

Smith et al. report the design of ripretinib, an investigational tyrosine kinase inhibitor that forces the activation loop of KIT and PDGFRα into an inactive conformation and targets a broad spectrum of KIT and PDGFRα mutants in GIST.