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Plant biodiversity is an important source of compounds with medicinal properties. The alkaloid galanthamine, first isolated from Galanthus woronowii (Amaryllidaceae), is approved by the FDA for the palliative treatment of mild to moderate Alzheimer’s disease due to its acetylcholinesterase (AChE) inhibitory activity. Obtaining this active pharmaceutical ingredient, still sourced on an industrial scale from the Amaryllidaceae species, is a challenge for pharmaceutical companies due to its low natural yield and the high cost of its synthesis. The aim of this work was to determine the alkaloid profile of three different Rauhia (Amaryllidaceae) species collected in Peru, and to assess the potential application of their extracts for the treatment of Alzheimer’s disease. The alkaloids were identified by gas chromatography coupled to mass spectrometry (GC-MS), and the AChE inhibitory activity of the extracts was analyzed. Thirty compounds were quantified from the Rauhia species, the R. multiflora extract being the most interesting due to its high diversity of galanthamine-type structures. The R. multiflora extract was also the most active against AChE, with the half maximal inhibitory concentration (IC₅₀) values of 0.17 ± 0.02 μg·mL⁻¹ in comparison with the IC₅₀ values of 0.53 ± 0.12 μg·mL⁻¹ for galanthamine, used as a reference. Computational experiments were carried out on the activity of the galanthamine-type alkaloids identified in R. multiflora toward five different human AChE structures. The simulation of the molecules 3-O-acetylgalanthamine, 3-O-acetylsanguinine, narwedine, and lycoraminone on the 4EY6 crystal structure theoretically showed a higher inhibition of hAChE and different interactions with the active site compared to galanthamine. In conclusion, the results of this first alkaloid profiling of the Rauhia species indicate that R. multiflora is an important natural source of galanthamine-type structures and could be used as a model for the development of biotechnological tools necessary to advance the sustainable production of galanthamine. Full article

Species distribution models (SDMs) are popular tools for predicting the geographic ranges of species. It is common practice to use georeferenced records obtained from online databases to generate these models. Using three species of Phaedranassa (Amaryllidaceae) from the Northern Andes, we compare the geographic ranges as predicted by SDMs based on online records (after standard data cleaning) with SDMs of these records confirmed through extensive field searches. We also review the identification of herbarium collections. The species’ ranges generated with corroborated field records did not agree with the species’ ranges based on the online data. Specifically, geographic ranges based on online data were significantly inflated and had significantly different and wider elevational extents compared to the ranges based on verified field records. Our results suggest that to generate accurate predictions of species’ ranges, occurrence records need to be carefully evaluated with (1) appropriate filters (e.g., altitude range, ecosystem); (2) taxonomic monographs and/or specialist corroboration; and (3) validation through field searches. This study points out the implications of generating SDMs produced with unverified online records to guide species-specific conservation strategies since inaccurate range predictions can have important consequences when estimating species’ extinction risks. Full article