Chemotaxonomic Insights into Erythrina and Sophora Alkaloids Using Self-Organizing Maps

The Fabaceae family is characterized by remarkable chemical diversity, especially alkaloids, which play a central role in taxonomic studies and drug development. Among its genera, Erythrina and Sophora stand out for the structural variety of their alkaloids and their significant pharmacological potential. This study applied self-organizing maps (SOMs) to chemotaxonomic analysis, using a database of 650 alkaloids derived from 129 species and 747 botanical occurrences. Therefore, SOMs were applied to investigate structural patterns in alkaloids from the genera Erythrina and Sophora based on molecular descriptors. A dataset composed of occurrence-based records and unique molecular structures was analyzed to evaluate the influence of structural redundancy on model performance. The SOMs showed high classification consistency, achieving overall accuracy above 90% in both approaches, with comparable precision, recall, and F1 values for the two genera. Descriptor distribution analyses suggested that Erythrina alkaloids are characterized by a higher degree of unsaturation and a greater content of sp2 carbons, whereas Sophora alkaloids tend to present a higher proportion of sp³ carbons, larger ring systems, and non-aromatic imines. The similarity between the results obtained from occurrence data and unique molecules demonstrates that SOM performance is preserved even after the removal of redundant structures. These results indicate that SOMs constitute a robust exploratory tool for the chemotaxonomic analysis of these alkaloids, although additional validation using other datasets and the integration of a larger amount of biological data are required to confirm the observed patterns.