Characterizing ecotoxicological effects of a resinoid natural complex substance using experimental and in silico approaches
Year: 2025
Type: article
Abstract: Natural complex substances (NCSs) are botanical extracts of unknown or variable composition. Such NCS contain long chain substances that are very difficult or impossible to identify, representing a challenge to characterization and toxicity assessment. This study aims to provide an innovative and relevant method to identify the constituents of galbanum resinoid, experimentally assess, and accurately predict its ecotoxicity. A fractionation technique was used to separate the NCS into three phases: "volatile," "nonvolatile but potentially bioavailable," and potentially "inert." The whole substance (WS) and each fraction were tested as water accommodated fractions (WAFs) for acute and chronic ecotoxicity to algae and daphnids. The toxicity of fractions and the WS was predicted using (a) an in silico method adapted for mixture toxicity testing and (b) the additivity Classification Labelling and Packaging/Global Harmonised System (CLP/GHS) method, based on analytically determined composition. The volatile fraction was more toxic than the nonvolatile fraction, and the inert fraction was not chronically toxic to algae or daphnids. The experimental daphnid chronic toxicity was higher than the acute for the WS because of larger molecules not toxic to their solubility limit in acute studies. The results from the experiments validated the in silico predictions, which accurately predicted toxicity of the fractions and the WS even if rather conservative for chronic daphnids. Also, the in silico method mechanistically explained the WAF test results and attributed the observed toxicity to specific constituents. However, CLP/GHS overpredicted toxicity in all cases and failed to account for observed toxicity. Experimental and in silico approaches appear to be highly complementary to deal with NCSs. Moreover, the in silico method provides a rapid and cost-effective option to obtaining data for difficult-to-test substances.
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415620455
