Environmental exposure to glyphosate does not inhibit human acetylcholinesterase and butyrylcholinesterase.

Glyphosate has remained the leading herbicide on the global market to date, despite the continuous debate between consumers, scientific community, and regulatory agencies over its carcinogenicity, genotoxicity, environmental persistence, and the role in the development of neurodegenerative disorders. Chemically, glyphosate belongs to a large family of organophosphorus pesticides, which exert a neurotoxic effect by inhibiting acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), enzymes of the cholinergic system essential for maintaining neurotransmission. Although research shows that glyphosate is a weak cholinesterase inhibitor in fish and mammals compared to other OP compounds, no conclusive data exist concerning the inhibition of human AChE and BChE. In our study we analysed its inhibitory potency on human AChE and BChE, by establishing its IC50 and reversible inhibition in terms of dissociation inhibition constants. Glyphosate concentration of 40 mmol/L caused near total inhibition of enzyme activity (approx. 10 % activity remaining). Inhibition dissociation constants (K i) of glyphosate-AChE and -BChE complexes were 28.4±2.7 mmol/L and 19.3±1.8 mmol/L, respectively. In conclusion, glyphosate shows a slight binding preference for BChE but exhibits inhibition only in a high concentration range. Our results are in line with studies reporting that its neurotoxic effect is not primarily linked to the cholinergic system.

Selected herbicides screened for toxicity and analysed as inhibitors of both cholinesterases.

Sets of 346 herbicides in use and 163 no longer in use were collected from open access online sources and compared in silico with cholinesterases inhibitors (ChI) and drugs in terms of physicochemical profile and estimated toxic effects on human health. The screening revealed at least one potential adverse consequence for each herbicide class assigned according to their mode of action on weeds. The classes with most toxic warnings were K1, K3/N, F1 and E. The selection of 11 commercial herbicides for in vitro biological tests on human acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), the enzymes involved in neurotoxicity and detoxification of various xenobiotics, respectively, was based mainly on the structural similarity with inhibitors of cholinesterases. Organophosphate anilofos and oxyacetanilide flufenacet were the most potent inhibitors of AChE (25 µM) and BChE (6.4 µM), respectively. Glyphosate, oxadiazon, tembotrione and terbuthylazine were poor inhibitors with an estimated IC50 above 100 µM, while for glyphosate the IC50 was above 1 mM. Generally, all of the selected herbicides inhibited with a slight preference towards BChE. Cytotoxicity assays showed that anilofos, bensulide, butamifos, piperophos and oxadiazon were cytotoxic for hepatocytes (HepG2) and neuroblastoma cell line (SH-SY5Y). Time-independent cytotoxicity accompanied with induction of reactive oxygen species indicated rapid cell death in few hours. Our results based on in silico and in vitro analyses give insight into the potential toxic outcome of herbicides in use and can be applied in the design of new molecules with a less impact on humans and the environment.

Comprehensive machine learning based study of the chemical space of herbicides.

Widespread use of herbicides results in the global increase in weed resistance. The rotational use of herbicides according to their modes of action (MoAs) and discovery of novel phytotoxic molecules are the two strategies used against the weed resistance. Herein, Random Forest modeling was used to build predictive models and establish comprehensive characterization of structure-activity relationships underlying herbicide classifications according to their MoAs and weed selectivity. By combining the predictive models with herbicide-likeness rules defined by selected molecular features (numbers of H-bond acceptors and donors, logP, topological and relative polar surface area, and net charge), the virtual stepwise screening platform is proposed for characterization of small weight molecules for their phytotoxic properties. The screening cascade was applied on the data set of phytotoxic natural products. The obtained results may be valuable for refinement of herbicide rotational program as well as for discovery of novel herbicides primarily among natural products as a source for molecules of novel structures and novel modes of action and translocation profiles as compared with the synthetic compounds.