Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning
The research article Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning was published in Biomolecules!
In this article we used our recently reported MAP4 and TMAP to visualize and analyze the Natural Products Atlas. The resulting interactive map organizes molecules by physico-chemical properties and compound families. Remarkably, the map also separates bacterial and fungal NPs from one another. To further investigate this aspect, we used the MAP4 fingerprint to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin.
Author(s): Alice Capecchi and Jean-Louis Reymond