Kinase inhibition screening by label-free mass spectrometry employing the MALDI PharmaPulse HTS solution

Significance of the Topic

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is emerging as a powerful label-free readout for high-throughput screening (HTS) in drug discovery. Inhibitor profiling of protein kinases, key targets in many diseases, benefits from rapid, cost-effective and low-false-positive assays. The integration of Bruker’s rapifleX MALDI PharmaPulse HTS solution addresses the need for fast cycle times, robust data quality and seamless data management in large compound library screens.

Study Objectives and Overview

This application demonstrates the capabilities of the MALDI PharmaPulse platform for in vitro inhibition screening of human tyrosine kinase ABL. Key goals were:

• Achieve sub-second data acquisition per sample.
• Establish assay robustness via Z′ and relative standard deviation (RSD) metrics.
• Integrate automated workflows from sample handling to data export.

The study covers assay design, MS acquisition, data processing and validation against a radiolabeling reference method.

Methodology and Instrumentation

Assay Design and Sample Preparation:
Enzymatic phosphorylation of a synthetic peptide substrate (EAIYAAPFAKKK, m/z 1336 Da) by ABL(H) yields a phosphorylated product (m/z 1416 Da). Reaction conditions mirrored a 33P radiolabel reference assay, with quenching by trifluoroacetic acid (1%). Samples were diluted 1:100 in MALDI buffer (10 mM NH4H2PO4, 1% TFA) and spotted onto prestructured AnchorChip 384 BC targets using α-cyano-4-hydroxycinnamic acid matrix.

Instrument Parameters:

• Mod​ule: Bruker rapifleX MALDI PharmaPulse MALDI-TOF MS
• Laser: smartbeam 3D at 10 kHz
• Acquisition: reflector positive mode, m/z range 1300–1500
• Shots per spectrum: 2 000 (random walk raster, 100 shots/position)
• Calibration: external (Peptide Calibration Standard II) and internal using substrate peak
• Control Software: MALDI PharmaPulse 2.2, flexControl 4.0
• Data Processing: flexAnalysis 4.0 with MPP2_2_meth-dev_screen_peptides.FAMSMethod

Main Results and Discussion

Throughput and Reproducibility:
Average acquisition time per spot was below one second. Enzyme titration and time-course experiments yielded RSDs of 0.5–7%, demonstrating high precision. The assay delivered a Z′ factor of 0.7 in 96-well screening format.

Inhibitor Profiling and Dose–Response:
A panel of 40 reference inhibitors was screened at individual concentrations. Normalized conversion rates across four measurements per compound showed an average RSD of 12%. Selected compounds (PP2, staurosporine, imatinib, dasatinib) were subjected to dose–response analysis, and IC₅₀ values obtained after non-linear fitting in Genedata Screener matched literature and 33P reference data closely.

Applications and Benefits

• Rapid, label-free readout reduces assay costs and eliminates radioactive waste.
• High sample throughput (<1 s/spot) enables screening of large libraries.
• Low false discovery rates streamline hit validation.
• Fully integrated software supports campaign setup, real-time plate visualization, quality control (Z′ calculation) and data export to LIMS/analysis tools.

Future Trends and Applications

Advances in MALDI-TOF HTS will likely include broader enzyme target panels, higher degrees of automation with liquid-handling robotics, smaller sample volumes for ultra-high-density formats, and incorporation of machine learning for spectral interpretation and hit triage. Integration with cloud-based informatics and AI-driven data mining will further enhance decision-making in early drug discovery.

Conclusion

The Bruker rapifleX MALDI PharmaPulse HTS solution provides a robust, high-speed, label-free platform for kinase inhibition screens. Demonstrated assay quality (Z′ ≥0.7, RSD <12%) and consistency with established radiolabel methods underline its suitability for large-scale drug discovery campaigns.

Reference

1. Heap RE, et al. SLAS Discovery, 22(10), 1193–1202 (2017).
2. Beeman K, et al. SLAS Discovery, 22(10), 1203–1210 (2017).
3. Winter M, et al. SLAS Discovery, 23(6), 561–573 (2018).
4. Winter M, et al. SLAS Technology, 24(2), 209–221 (2018).