Genetic engineering of T cells in mouse models is essential for investigating immune mechanisms. We aimed to develop an approach to manipulate T cells…

Sana Biotechnology has shared early data for its investigational allogeneic cell therapy being studied in one patient with type 1 diabetes, sending the company’s share price up by about 200%. | Sana B...

Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer’s toolbox. Recent advances in covalent drug discovery, in particular, targeting cysteines, have led to significant breakthroughs for traditionally challenging targets such as mutant KRAS, which is implicated in diverse human cancers. However, identifying cysteines for targeted covalent inhibition is a difficult task, as experimental and in silico tools have shown limited accuracy. Using the recently released CovPDB and CovBinderInPDB databases, we have trained and tested interpretable machine learning (ML) models to identify cysteines that are liable to be covalently modified (i.e., “ligandable” cysteines). We explored myriad physicochemical features (pKa, solvent exposure, residue electrostatics, etc.) and protein–ligand pocket descriptors in our ML models. Our final logistic regression model achieved a median F1 score of 0.73 on held-out test sets. When tested on a small sample of holo proteins, our model also showed reasonable performance, accurately predicting the most ligandable cysteine in most cases. Taken together, these results indicate that we can accurately predict potential ligandable cysteines for targeted covalent drug discovery, privileging cysteines that are more likely to be selective rather than purely reactive. We release this tool to the scientific community as CovCysPredictor.

Here, Fry and colleagues examine the impact of antigen experience on subsequent CD8+ CAR T cell activity during the antileukemia response and show that RUNX2 overexpression enhances antitumor activity...

The 2025 SITC Spring Scientific, Cellular Therapy for Solid Tumors, will address the recent advances in adoptive cellular therapy for solid tumors and rate-limiting challenges that impede bringing the...

When the primary outcome of a clinical trial fails to reach its prespecified end point, can any clinically meaningful information still be derived from it? This review article addresses that question.

Biomedical research has implicated the bacterial metabolite colibactin as a causal risk factor for several cancer types, in particular, colorectal can…

The advent of droplet-based single-cell RNA-sequencing (scRNA-seq) has dramatically increased data throughput, enabling the release of a diverse array of tissue cell atlases to the public. However, we...

The crusade against bright headlights has picked up speed in recent years, in large part due to a couple of Reddit nerds. Could they know what’s best for the auto industry better than the auto industr...

In this Review, Sharma and colleagues describe the current landscape of combination therapies and discuss requirements for the development of effective combination strategies.