Normalization techniques for high-throughput screening by infrared matrix-assisted laser desorption electrospray...

Area of Science:

• Analytical Chemistry
• Mass Spectrometry
• Drug Discovery

Background:

• Mass spectrometry (MS) is crucial for high-throughput screening (HTS) in drug discovery.
• Infrared matrix-assisted laser desorption electrospray ionization MS (IR-MALDESI-MS) offers sub-second analysis times, demanding methods to enhance data quality.
• Improving assay quality, measured by the Z-factor, requires increased analyte signal and reduced variability.

Purpose of the Study:

• To identify optimal solvent compositions for boosting analyte signal in IR-MALDESI-MS.
• To evaluate normalization strategies for decreasing signal variability in IR-MALDESI-MS analyses.
• To enhance the reliability of IR-MALDESI-MS for drug discovery HTS.

Main Methods:

• Investigated various solvent compositions for direct analysis via IR-MALDESI-MS.
• Assessed the efficacy of normalization standards (structurally similar and dissimilar) to reduce analyte abundance variability.
• Performed analyses in both positive and negative ionization modes.

Main Results:

• Determined specific solvent compositions that significantly increase measured analyte abundances.
• Demonstrated that normalization strategies can effectively reduce the variability of analyte measurements.
• Identified optimal approaches for both positive and negative ionization modes.

Conclusions:

• Optimized solvent mixtures and normalization techniques improve analyte signal and reduce variability in IR-MALDESI-MS.
• These improvements enhance data quality for high-throughput screening in drug discovery.
• The findings contribute to more reliable and efficient drug candidate identification using IR-MALDESI-MS.