Experimental and Computational Study of Aminoacridines as MALDI(-)-MS Matrix Materials for the Analysis of Complex Samples

Monoaminoacridines (1-, 2-, 3-, 4-, and 9-aminoacridine) were studied for suitability as matrices in the negative ion mode matrix-assisted laser desorption/ionization mass spectrometry (MALDI(-)-MS) analysis of various samples. This is the first study to examine 1-, 2-, and 4-aminoacridine as potential matrix material candidates for MALDI(-)-MS. In addition, spectral (UV-Vis absorption and fluorescence), proton transfer-related (basicity and autoprotolysis), and crystallization properties of these compounds were characterized experimentally and/or computationally. For testing the capabilities of these aminoacridines as matrix materials, four samples related to cultural heritage materials-stearic acid, colophony resin, dyer's madder dye, and a resinous case-study sample from a shipwreck-were analyzed with MALDI(-)-MS. A novel algorithm (implemented as an executable Python script) for MS data analysis was developed to compare the five matrix materials and to help mass spectrometrists rapidly identify peaks originating from the sample and matrix material. It was determined that all five of the studied aminoacridines can successfully be used as matrix materials in MALDI(-)-MS analysis. As an interesting finding, in several cases, the best mass spectra were obtained by using a relatively small amount of matrix material mixed with an excess amount of sample. 3- and 4-aminoacridine outperformed the other aminoacridines in the ease of obtaining acceptable spectra, average number of ions identified in the mass spectra, and low dependence of the sample-to-matrix mass ratio on experimental results.

Automated summary

Monoaminoacridines were studied as potential matrices for MALDI(-)-MS analysis, with 3- and 4-aminoacridine showing superior performance in obtaining acceptable spectra. The compounds were characterized for their spectral, proton transfer-related, and crystallization properties, and a novel algorithm was developed for MS data analysis. All five studied aminoacridines were found to be suitable as matrix materials, with interesting results showing the benefits of using a small amount of matrix material mixed with an excess amount of sample in obtaining the best mass spectra.