Development of benzimidazole derivatives as efficient matrices for the analysis of acidic small‐molecule compounds using matrix‐assisted laser desorption/ionisation time‐of‐flight mass spectrometry in negative ion mode

Abstract

RationaleWith the development of matrix‐assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) in spatial localisation omics research on small molecules, the detection sensitivity of the matrix must increase. However, the types of matrices suitable for detecting acidic small molecules in (−) MALDI‐MS mode are very limited and are either not sensitive enough or difficult to obtain.MethodsMore than 10 commercially available benzimidazole and benzothiazole derivatives were selected as MALDI matrices in negative ion mode. MALDI‐MS analysis was performed on 38 acidic small molecules and mouse serum, and the matrix effects were compared with those of the common commercial matrices 9‐aminoacridine (9AA), 1,5‐naphthalenediamine (DAN) and 3‐aminoquinoline (3AQ). Moreover, the proton affinity (PA) of the selected potential matrix was calculated, and the relationships among the compound structure, PA value and matrix effect were discussed.ResultsIn (−) MALDI‐MS mode, a higher PA value generally indicates a better matrix effect. Amino‐substituted 2‐phenyl‐1H‐benzo[d]imidazole derivatives had well‐defined matrix effects on all analytes and were generally superior to the commonly used matrices 9AA, DAN and 3AQ. Among them, 2‐(4‐(dimethylamino‐phenyl)‐1H‐benzo[d]imidazole‐5‐amine (E‐4) has the best sensitivity and versatility for detecting different analytes and has the best ability to detect fatty acids in mouse serum; moreover, the limit of detection (LOD) of some analytes can reach as low as ng/L.ConclusionsCompared to 9AA, DAN and 3AQ, matrix E‐4 is more effective at detecting low‐molecular‐weight acidic compounds in (−) MALDI‐MS mode, with higher sensitivity and better versatility. In addition, there is a clear correlation between compound structure, PA and matrix effects, which provides a basis for designing more efficient matrices.