期刊
BIOMOLECULES
卷 10, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/biom10101385
关键词
natural products; databases; cheminformatics; chemical space; visualization; molecular fingerprints; machine learning; support vector machine; origin classification
资金
- Swiss National Science Foundation [200020_178998]
- Swiss National Science Foundation (SNF) [200020_178998] Funding Source: Swiss National Science Foundation (SNF)
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint suitable for molecules across very different sizes, to analyze the Natural Products Atlas (NPAtlas), a database of 25,523 NPs of bacterial or fungal origin. To visualize NPAtlas by MAP4 similarity, we used the dimensionality reduction method tree map (TMAP). The resulting interactive map organizes molecules by physico-chemical properties and compound families such as peptides and glycosides. Remarkably, the map separates bacterial and fungal NPs from one another, revealing that these two compound families are intrinsically different despite their related biosynthetic pathways. We used these differences to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin.
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