Introducing DoPP: A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data

The widespread abuse of legal high psychoactive plants continues to be of global concern because of their negative impacts on public health and safety. In forensic science, a major challenge in controlling these substances is the paucity of methods to rapidly identify them. We report the development of the Database of Psychoactive Plants (DoPP), a new user-friendly tool featuring an architecture for the identification of plant unknowns, and the necessary regression statistics for the development and validation of psychoactive compound quantification. The application relies on the knowledge that terrestrial plants exhibit species specific chemical signatures that can be revealed by direct analysis in real time high-resolution mass spectrometry (DART-HRMS). Subsequent automated machine learning processing of libraries of these spectra enables rapid discrimination and species identification. The chemical signature database includes 57 available plant species. The rapid acquisition of mass spectra and the ability to sample the materials in their native form enabled the generation of the vast amounts of spectral replicates required for database construction. For the identification of sample unknowns, a data analysis workflow was developed and implemented using the DoPP tool. It utilizes a hierarchical classification tree that integrates three machine learning methods, namely, random forest, k-nearest neighbors, and support vector machine, all of which were fused using posterior probabilities. The results show accuracies of 98 and 99% for 10-fold cross-validation and external validation, respectively, which make the classification model suitable for identity prediction of real samples.

Automated summary

The misuse of legal high psychoactive plants is a global concern due to the negative impacts on public health and safety. However, the development of methods to rapidly identify these substances is a major challenge. In this study, a user-friendly tool called Database of Psychoactive Plants (DoPP) was developed for the identification of unknown plants and quantification of psychoactive compounds. The tool utilizes real-time high-resolution mass spectrometry analysis to reveal species-specific chemical signatures of terrestrial plants, allowing for rapid discrimination and species identification.