SLAS Discovery: Advancing Tools for Cancer Fibrosis and Drug Discovery

SLAS Discovery: Advancing Tools for Cancer Fibrosis and Drug Discovery

Highlights include novel FAK-paxillin inhibitors, a venom toxin screening platform, and AI-driven solubility prediction

Oak Brook, IL – Volume 34 of SLAS Discovery includes two original research articles, one short communication and one entry in the upcoming Special Issue on EUOS/SLAS Joint Challenge: Compound Solubility.

Original Research

• Development of a high-throughput TR-FRET assay to identify inhibitors of the FAK-paxillin protein-protein interaction
  This study presents a high-throughput TR-FRET assay targeting the FAK FAT domain's interaction with paxillin, identifying four novel small-molecule inhibitors with potential applications in cancer and fibrosis therapy. The screening strategy combined TR-FRET primary/counterscreen assays and SPR validation to ensure specificity, establishing a robust framework for future FAK PPI drug discovery.
• Parallel in vitro ion channel and in vivo zebrafish assaying of elapid snake venoms following chromatographic separation of toxin components
  This article introduces an integrated high-throughput platform combining nanofractionation analytics, calcium flux assays, zebrafish paralysis tests and proteomics to rapidly identify and characterize snake venom toxins targeting ion channels, demonstrating its utility with elapid venoms.

Short Communication

• Optimization and development of a high-throughput TR-FRET screening assay for SLIT2/ROBO1 interaction
  The authors demonstrate a high-throughput TR-FRET assay for screening inhibitors of the oncogenic SLIT2/ROBO1 interaction, identifying SMIFH2 as a dose-dependent disruptor. This discovery provides the first pharmacological tool to target this pathway in cancer, fibrosis and vascular diseases.

Special Issue

The upcoming special issue, EUOS/SLAS Joint Challenge: Compound Solubility, highlights a scientific challenge in which computational experts developed machine learning models to predict solubility for ~100,000 compounds from the EU-OPENSCREEN collection. The challenge prioritized interpretable AI workflows, combining robust data curation with meaningful chemical descriptors to create a benchmark for future solubility prediction in drug discovery.

Access to this issue of SLAS Discovery is available at https://www.slas-discovery.org/issue/S2472-5552(25)X0005-8

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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, Ph.D., Grove Biopharma, Inc., Chicago, IL (USA)

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