Bioactivity-Based Molecular Networking for the Discovery of Drug Leads in Natural Product Bioassay-Guided Fractionation

Abstract

It is a common problem in natural product therapeutic lead discovery programs that despite good bioassay results in the initial extract, the active compound(s) may not be isolated during subsequent bioassay-guided purification. Herein, we present the concept of bioactive molecular networking to find candidate active molecules directly from fractionated bioactive extracts. By employing tandem mass spectrometry, it is possible to accelerate the dereplication of molecules using molecular networking prior to subsequent isolation of the compounds, and it is also possible to expose potentially bioactive molecules using bioactivity score prediction. Indeed, bioactivity score prediction can be calculated with the relative abundance of a molecule in fractions and the bioactivity level of each fraction. For that reason, we have developed a bioinformatic workflow able to map bioactivity score in molecular networks and applied it for discovery of antiviral compounds from a previously investigated extract of Euphorbia dendroides where the bioactive candidate molecules were not discovered following a classical bioassay-guided fractionation procedure. It can be expected that this approach will be implemented as a systematic strategy, not only in current and future bioactive lead discovery from natural extract collections but also for the reinvestigation of the untapped reservoir of bioactive analogues in previous bioassay-guided fractionation efforts.

Feature-based Molecular Networking in the GNPS Analysis Environment

“…The FBMN method consists of two main steps: 1) LC-MS feature detection and alignment, then 2) a dedicated molecular networking workflow on GNPS. Our first prototype for FBMN was developed with the Optimus workflow 12,18 that uses OpenMS tools 15 and the KNIME Analytics 26 platform. Following step 1 (feature detection and alignment), two files are exported: a feature quantification table (.TXT format) and a MS 2 spectral summary (.MGF format).…”

“…In both cases, FBMN resolved positional isomers in the molecular networks that have similar MS 2 spectra but distinct retention times, that would not have been resolved with classical MN. In the study of metabolites produced by Euphorbia plants, the annotation of isomers in the FBMN facilitated the subsequent isolation of antiviral compounds 12 . With samples from the American Gut Project, FBMN enabled the annotation of commendamide isomers, including a putative novel derivative 11 .…”

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

“…The inclusion of extraction blanks and technical replicates of quality controls are good examples of such practices and have been shown to be useful for the identification of features that do not originate from the samples or that exhibit low reproducibility [186]. This data cleaning process can significantly facilitate further steps of data analysis, particularly for the identification of features that are most relevant for the separation of experimental groups, for instance, in activity guided fractionation of complex extracts [187]. Another challenging and essential aspect of processing untargeted metabolomics experiments is the identification of features representing fragments, adducts, and isotopes of a same compound.…”

Response of Secondary Metabolism of Hypogean Actinobacterial Genera to Chemical and Biological Stimuli

“…Examples of this combined approach include overlaying bioactivity to molecular networking (65) and our own multiplexed activity metabolomics (MAM) approach (66). In both cases, these methods enable an estimation of the activity of unknown compounds and structure-activity relationships within compound families prior to compound isolation using activity metabolomics techniques (65,66).…”