Oak Brook, Illinois, April 29: The latest edition of SLAS Discovery (Volume 39) features four new research contributions focused on advancing drug discovery through artificial intelligence, high-throughput imaging, fragment-based screening, and large-scale ligand-binding datasets.
The issue includes three original research articles and one short communication, all aimed at improving experimental workflows and expanding data resources for AI-enabled drug discovery.
A key study introduces an AI-based analysis workflow for label-free live-cell imaging in T-cell mediated tumor killing assays. The method eliminates the need for fluorescent dyes or nuclear labels, reducing artifacts such as phototoxicity while maintaining robust and consistent hit identification in immune cell therapeutic screening.
Another study applies MALDI mass spectrometry-based screening to identify covalent fragments targeting the methyl-lysine reader protein MPP8. Researchers identified two acrylamide-containing fragments binding at cysteine 99, highlighting a promising approach for difficult cancer-related targets.
In infectious disease research, a high-throughput, high-content imaging assay has been developed to evaluate drug candidates against Trypanosoma cruzi, the parasite responsible for Chagas disease. The 384-well platform simultaneously measures anti-parasitic activity and host toxicity, supporting safer therapeutic discovery.
A fourth contribution introduces Binder2030, a curated membrane protein binding dataset comprising nearly 3,400 small-molecule ligands across approximately 400 membrane proteins, including GPCRs, ion channels, and transporters. The dataset provides standardized binding affinity measurements to support AI-driven drug discovery and address critical gaps in ligand-protein interaction data.
Access to this volume and related publications is available through SLAS Discovery’s official platform.
Society for Laboratory Automation and Screening emphasized that the journal continues to support interdisciplinary research that advances laboratory automation, screening technologies, and translational drug discovery across academia, industry, and government sectors.
