Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning

Abstract

<p>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 downloaded from <a href="https://www.npatlas.org/joomla/">https://www.npatlas.org/joomla/</a>. To visualize NPAtlas by MAP4 similarity, we used the dimensionality reduction method tree map (TMAP) (<a href="http://tmap.gdb.tools/">http://tmap.gdb.tools</a>). The resulting interactive map (<a href="https://tm.gdb.tools/map4/npatlas_map_tmap/">https://tm.gdb.tools/map4/npatlas_map_tmap/</a>) organizes molecules by physico-chemical properties and compound families such as peptides, glycosides, polyphenols or terpenoids. Remarkably, the map separates bacterial and fungal NPs from one another, revealing that these two compound families are intrinsically different despite of their related biosynthetic pathways. We used these differences to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin. </p>

Approaches for enhancing the analysis of chemical space for drug discovery

“…TMAP was used in the global analysis of the peptide chemical space, whereas MAP4 was employed as the molecular representation of peptides [47]. A similar approach was used to visualize the chemical space of NPs in the public domain [53]. To assist the processes of decision-making and selecting compound libraries for further virtual screening or compound acquisition for high-or medium-throughput screening for epigenetic drug discovery, Flores-Padilla et al reported a comprehensive analysis of 11 commercial libraries of varying sizes focused on epigenetic targets (with 53,443 compounds in total) [48].…”

A review on computational approaches that support the researches on traditional Chinese medicines (TCM) against COVID-19

“…The ISIDA descriptors have also been used to explore the chemical space of natural product. MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4) was reported as a molecular fingerprint with good performance in similarity searching and chemical space visualization for different molecular sizes, which were analyzed in Natural Products Atlas (NPAtlas) containing microbial origins ( Capecchi et al, 2020 ; Capecchi and Reymond, 2020 ). These could be great ideas for conducting experimental research using natural product databases, molecular descriptors and fingerprints, chemical space navigation of natural product against COVID-19.…”

Natural Products, the Fourth Industrial Revolution, and the Quintuple Helix

“…258 An analysis of 25,523 natural isolates from fungi and bacteria (NatProdAtlas) revealed new distinctions of evolutionary origin based on their structures and biosynthetic pathways. 259 Using a dataset of 201,791 natural products in comparison with the same number of synthetic products, a machine learning algorithm developed parameters for distinguishing the 2 sets with high accuracy and quantifying natural product-likeness. As expected, the space occupied by the natural products and the overall diversity and complexity (eg, stereocenters) was much larger for the natural products, the number of nitrogen atoms was smaller, and the number of oxygen atoms greater.…”