Classifying Natural Products from Plants, Fungi or Bacteria using the COCONUT Database and Machine Learning

Abstract

Natural products (NPs) represent one of the most important resources for discovering new drugs. Here we asked whether NP origin can be assigned from their molecular structure in a subset of 60,171 NPs in the recently reported Collection of Open Natural Products (COCONUT) database assigned to plants, fungi, or bacteria. Visualizing this subset in an interactive tree-map (TMAP) calculated using MAP4 (MinHashed atom pair fingerprint) clustered NPs according to their assigned origin (https://tm.gdb.tools/map4/coconut_tmap/), and a support vector machine (SVM) trained with MAP4 correctly assigned the origin for 94% of plant, 89% of fungal, and 89% of bacterial NPs in this subset. An online tool based on an SVM trained with the entire subset correctly assigned the origin of further NPs with similar performance (https://np-svm-map4.gdb.tools/). Origin information might be useful when searching for biosynthetic genes of NPs isolated from plants but produced by endophytic microorganisms.

Open data and algorithms for open science in AI-driven molecular informatics

“…The PubChem database is used by millions of users every month [35]. An example for the usage of the referenced databases is the creation of a classifier that determines whether a Natural Product (NP) originates from funghi, plants, or bacteria based on its chemical structure with data obtained from the COCONUT database [36]. The ZINC database has recently been used for the in silico determination of drug candidates that inhibit the main protease of SARS-CoV-2 [37].…”

Open data and algorithms for open science in AI-driven molecular informatics

“…The PubChem database is used by millions of users every month [35]. An example for the usage of the referenced databases is the creation of a classifier that determines whether a Natural Product (NP) originates from funghi, plants, or bacteria based on its chemical structure with data obtained from the COCONUT database [36]. The ZINC database has recently been used for the in silico determination of drug candidates that inhibit the main protease of SARS-CoV-2 [37].…”

Open data and algorithms for open science in AI-driven molecular informatics

“…The PubChem database is used by millions of users every month [35]. An example for the usage of the referenced databases is the creation of a classifier that determines whether a Natural Product (NP) originates from funghi, plants, or bacteria based on its chemical structure with data obtained from the COCONUT database [36]. The ZINC database has recently been used for the in silico determination of drug candidates that inhibit the main protease of SARS-CoV-2 [37].…”

Open data and algorithms for open science in AI-driven molecular informatics

“…The PubChem database is used by millions of users every month [35]. An example for the usage of the referenced databases is the creation of a classifier that determines whether a Natural Product (NP) originates from funghi, plants, or bacteria based on its chemical structure with data obtained from the COCONUT database [36]. The ZINC database has recently been used for the in silico determination of drug candidates that inhibit the main protease of SARS-CoV-2 [37].…”