Based on the overall annotation outcomes, a total of 291 features were successfully annotated for both T. wilfordii roots and bark extracts. To visually depict key annotations concerning the primary constituents of T. wilfordii, these annotations are summarized in Table and have been presented in Figure . Within this figure, both the MS data and the CAD trace are shown. The comparison of these two traces facilitated a manual assessment of the features corresponding to the major NPs detected in both extracts. The inclusion of the CAD trace not only enhances the dereplication analysis but also aids in the identification of the major constituents . This approach demonstrates a good fitting between the annotation results for these key constituents and existing literature data, reinforcing the notion that these compounds stand as major NPs from the plant. Most of these compounds also corresponded to the most pharmacologically significant compounds within the T. wilfordii species and Tripterygium genus. This includes compounds like celastrol , triptolide , and wilforlide A . Additionally, the targeted isolation of celastrol and pristimerin was performed on the root of T. wilfordii (data not shown). The structures were confirmed by 1D and 2D NMR analysis. The respective UHPLC-HRMS 2 analysis confirmed the retention time and the MS 2 spectral information was shared on the GNPS platform (celastrol, pristimerin). These MSI level 1 annotations and findings contribute to strengthening the confidence in the overall annotation results presented within this study. The comprehensive UHPLC-PDA-CAD-HRMS 2 metabolite profiling conducted on the set of Celastraceae plants, followed by data processing, facilitated the creation of an extensive set of annotations using state-of-the-art bioinformatic tools. The results of the annotation pipelines were then used to construct a chemical space, which was subsequently compared against the reported chemical space for the Celastraceae family. This work opens avenues for data exploration, enabling the identification of taxonomic relationships based on chemical similarities. Moreover, within the dataset, a subset of features remains unannotated, representing potential connections to novel and uncharacterized NPs. This is exemplified by the work undertaken in the development of Inventa . This dataset not only serves as a cornerstone for further investigations into chemotaxonomy but also provides a valuable resource for any research aimed at uncovering the diverse chemical space of this botanical family, known for its abundant array of specialized metabolites.