image: SLAS Discovery, Vol. 42
Credit: SLAS
Oak Brook, IL – Volume 42 of SLAS Discovery includes one review, eight original research articles and 1 short communication for oncology, infectious disease, immunology and computational biology research through innovative screening platforms for accelerating the discovery of targeted therapies, diagnostic biomarkers, and mechanistic insights across diverse disease areas.
Review
- ADCs for Colorectal Carcinoma: Decoding Clinical Evidence for Molecular Design Innovation
This review examines the rapidly evolving landscape of antibody-drug conjugates (ADCs) in colorectal cancer (CRC), highlighting the recent approval of T-DXd for HER2-positive disease as a milestone entry into this treatment arena. The authors explore clinical performance, design considerations and future directions, positioning ADCs as a promising targeted option for CRC patients with unmet clinical needs.
Original Research
- Identification of AMPD2 Allosteric Inhibitors with Novel Mechanism of Action by Fragment Merging Approach
Using an X-ray fragment screening approach, researchers identified a series of allosteric inhibitors that selectively target Adenosine monophosphate deaminase 2 (AMPD2) over other AMPD isozymes, overcoming the poor selectivity of traditional orthosteric inhibitors. Through iterative fragment merging and optimization, the team developed potent compounds (10g and 10h) that bind a previously uncharacterized allosteric site, offering valuable tool compounds for studying AMPD2's roles in nucleotide metabolism, energy homeostasis, and immune oncology. - Thermodynamic Profiling and Fragment Screening of GPCRS Using Grating-Coupled Interferometry
Researchers demonstrate that grating-coupled interferometry (GCI) offers a powerful biosensor platform for characterizing GPCR–ligand interactions, providing high-quality kinetic data comparable to established Biacore technology while enabling rapid affinity and thermodynamic profiling from single-concentration injections. Using the adenosine A2A receptor as a model, the team validated the approach through kinetic fragment screening of a 704-member library, identifying specific binders confirmed by nanoDSF and establishing GCI as an information-rich tool for early-stage GPCR drug discovery. - Identification of Novel Diagnostic Biomarkers and Host-Directed Drug Screening for Mycobacterium avium Infection: a Multi-Omics and Artificial Intelligence Study
By integrating single-cell RNA sequencing with machine learning, researchers mapped the immune landscape of Mycobacterium avium (MAV) infection. They uncovered a monocyte-driven MIF-APP signaling axis that recruits and "locks" macrophages into a hyper-inflammatory state, explaining the paradox of high inflammation but poor pathogen clearance. The study also developed a five-gene diagnostic signature (AUC > 0.88) and identified Wogonin as a potential host-directed therapeutic that targets STAT3 and TNF to break the immune impasse. - Development of a Rapid and Sensitive EnLIGHT OMEGA Assay for Extracellular AGR2 Detection In Biological Fluids
Researchers developed a novel homogeneous OMEGA assay to detect extracellular AGR2 (eAGR2), a protein strongly linked to tumor progression and cancer aggressiveness, with a broad dynamic range (0.02–300 ng/mL) and no washing or separation steps required. This sensitive, rapid method outperforms conventional ELISA and is applicable across diverse biological fluids, offering a valuable tool for cancer biology, drug resistance and biomarker discovery studies. - Use t Ttests to Analyze Counts of Cells in Two States
A comparative analysis of statistical tests for count data found that t tests perform as well as or better than specialized count-based methods at maintaining false-positive rates, with no disadvantage in detecting real differences. The findings reassure researchers that converting count data to percentages and analyzing with t tests is a valid and effective approach under typical wet-lab conditions. - In Silico Prioritization and Cheminformatics Identify Structurally Diverse Small-Molecule Inhibitors
Using a computational data-mining strategy applied to a previously deposited screen of nearly 300,000 small molecules, researchers identified three distinct chemical scaffolds that inhibit Lassa virus cell entry with potencies as low as 10 nM and strong selectivity over related viruses. These compounds act at the membrane fusion stage by targeting pH-sensitive regions of the viral glycoprotein, highlighting the power of combined computational and experimental approaches for antiviral drug discovery. - CellVision: A Deep Learning Based Image Analysis Platform to Accelerate Immuno-Plaque Assay Data Processing for Dengue Vaccine Development
Researchers have developed CellVision, a deep learning-based workflow that fully automates viral plaque counting in high-throughput immuno-plaque assays, accurately segmenting fused plaques and distinguishing them from other objects without any manual image review. Integrated into Merck’s (& Co., Inc.) µPlaque assay to support an investigational dengue vaccine, CellVision outperformed a commercial alternative and sets a new standard for AI-powered analysis in antiviral vaccine discovery. - Tumor-Versus-Nonmalignant Quantitative Drug Sensitivity Profiling Identifies capivasertib as a Selective Therapeutic Candidate for Nasopharyngeal Carcinoma
Using a tumor-normal-paired high-throughput drug screening approach against EBV-positive and EBV-negative nasopharyngeal carcinoma (NPC) cell lines, researchers identified the AKT inhibitor capivasertib as a highly selective anti-NPC agent that spares normal epithelial cells. Capivasertib synergized with platinum-based chemotherapy, enhanced radiosensitivity, and significantly prolonged survival in combination with cisplatin in xenograft models, providing a strong rationale for its clinical evaluation in advanced NPC.
Short Communication
- Development of a High-Throughput TR-FRET Assay for Identification of Small Molecule Inhibitors of the LILRB4 (ILT3)-SCG2 Immune Checkpoint Interaction
Researchers have developed a high-throughput TR-FRET assay to interrogate the interaction between the immune checkpoint LILRB4 (ILT3) and its ligand SCG2, a pathway driving myeloid-mediated immunosuppression in the tumor microenvironment. Pilot screening identified two compounds, BMS-813,160 and PSB-603, that dose-dependently inhibit this interaction with micromolar potency, providing the first small-molecule modulators of the LILRB4-SCG2 axis and a foundation for targeting myeloid-driven immunosuppression.
Access to this volume of SLAS Discovery is available at https://www.slas-discovery.org/issue/S2472-5552(26)X2003-2
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 compare 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, 2025 Impact Factor 3.3. Editor-in-Chief Robert M. Campbell, PhD, Grove Biopharma, Inc., Chicago, IL (USA)
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SLAS DISCOVERY