Challenging diseases addressed in vol. 39 of SLAS Discovery

Oak Brook, IL – Volume 39 of SLAS Discovery includes three original research articles and one short communication that aim to accelerate drug discovery through novel imaging workflows, fragment identification for challenging targets and datasets that bridge ligand-binding data gaps to enable AI-driven drug discovery. 

Original Research

• AI-Based Analysis of Label-Free Live Cell Imaging of T-Cell Mediated Tumor Killing Assay Enables Competitive and Robust Hit Calling
  This article presents a newly developed AI-powered live brightfield microscopy analysis workflow that eliminates the need for fluorescent dyes or nuclear labels to assess functional activity of immune cell therapeutics in T-cell mediated killing assays. The hands-free approach simplifies these assays while maintaining the consistency of traditional methods and avoiding artifacts such as phototoxicity and segmentation errors.
• Application of a MALDI Mass Spectrometry Assay to Identify Covalent Fragments Targeting the Methyl-Lysine Reader Protein MPP8
  Using high-throughput MALDI-TOF mass spectrometry to screen covalent fragment libraries, the authors identify two novel acrylamide-containing fragments that target and label the methyl-lysine reader protein MPP8 at cysteine 99, a site adjacent to its functional binding pocket. The results highlight the value of efficient screening approaches for targets such as MPP8, a challenging protein target with potential implications for cancer therapeutics.
• An MRC-5 Cell Based High-Throughput, High-Content Imaging Assay to Identify Hits Against Trypanosoma cruzi Intracellular Parasites
  This study develops and validates a new high-throughput, high-content imaging assay in a 384-well format that rapidly assesses potential drug candidates against Trypanosoma cruzi, the parasite that causes Chagas disease. The multiplexed platform simultaneously measures both anti-parasitic activity and host cell toxicity, offering an efficient path to discovering safer, more effective therapies beyond the currently limited and side-effect-prone drugs benznidazole and nifurtimox.
• Binder2030: A Quantitative Membrane Proteome Binding Dataset Enabling AI-Driven Drug Discovery
  The authors present Binder2030, a curated affinity selection–mass spectrometry dataset containing nearly 3,400 small-molecule ligands measured against roughly 400 membrane proteins, including G protein-coupled receptors, solute carrier transporters and ion channels. This resource provides standardized dissociation constant measurements and chemical annotations, helping bridge a critical gap in quantitative ligand-binding data for a class of proteins that represents over half of all therapeutic targets.

Access to this volume of SLAS Discovery is available at https://www.slas-discovery.org/issue/S2472-5552(25)X0010-1

All active SLAS Discovery and SLAS Technology call for papers are available at: https://www.slas.org/publications/call-for-papers/

 

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SLAS Discovery reports how scientists develop and use novel technologies and/or approaches to provide and characterize computational, chemical and biological tools to understand and treat human disease. The journal focuses on drug discovery sciences with a strong record of scientific rigor and impact, reporting on research that:

• Enables and improves target validation
• Shares and/or compares novel methods for medium- or high-throughput screening
• Evaluates current drug discovery technologies
• Provides novel research tools
• Incorporates research approaches that enhance depth of knowledge and drug discovery success

SLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.

SLAS Discovery: Advancing the Science of Drug Discovery, 2024 Impact Factor 2.7. Editor-in-Chief Robert M. Campbell, PhD, Grove Biopharma, Inc., Chicago, IL (USA)

 

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