Development of a thin-layer chromatography-angiotensin-converting enzyme bioassay coupled with digital image analysis for effect-directed screening of enzyme inhibitors.

A novel thin-layer chromatography (TLC)-based bioassay coupled with digital image analysis (DIA) was developed for rapid and non-targeted screening of angiotensin-converting enzyme (ACE) inhibitors in complex natural matrices. Conventional ACE inhibitory assays lack spatial resolution and rely on indirect measurements, limiting their applicability for effect-directed analysis (EDA). In this study, an on-surface enzymatic assay was implemented using hippuryl-histidyl-leucine (HHL) as substrate, followed by in situ derivatization of the generated hippuric acid with p-dimethylaminobenzaldehyde (DMAB) in an acetone:acetic anhydride system, producing an orange chromophore directly on the TLC plate. To overcome the inherent subjectivity of visual evaluation, a MATLAB-based DIA workflow was introduced to quantify the colorimetric response as pseudo-absorbance, enabling objective optimization of assay parameters. The blue channel provided the highest analytical sensitivity (R2 = 0.9984), and no significant matrix effects were observed (p = 0.09), confirming the robustness of the approach. Optimal conditions were established at 180 mU mL-1 ACE, 3 mM HHL, 30 min incubation, and 10% (w/v) DMAB. The method was applied to P. boldus alkaloidal extracts, enabling clear detection and localization of inhibitory zones poorly resolved by visual inspection. Subsequent isolation by micro-preparative TLC followed by UHPLC-DAD-MS/MS analysis enabled tentative identification of three aporphine alkaloids: norboldine (m/z 314.20 [M+H]+), boldine (m/z 328.10 [M+H]+), and laurotetanine (m/z 328.10 ([M+H]+). This integrated TLC-ACE-DIA platform, complemented by GNPS-assisted MS/MS annotation, provides a rapid, cost-effective, high-throughput strategy for discovery and prioritization of ACE inhibitors in natural products, significantly enhancing analytical capabilities of effect-directed analysis workflows.