Binding organophosphate pesticides to acetylcholinesterase: risk assessment using the Monte Carlo method

Abstract

Binding to acetylcholinesterase (AChE k1) may cause toxic effects in humans. Organophosphates simultaneously are both dangerous and useful substances. Dangerous since they are employed in chemical warfare and useful when they are applied as pesticides. Here, we suggest the models for organophosphates binding to AChE k1 developed via representing the molecular structure by a simplified molecular input-line entry system using so-called optimal descriptors calculated with the Monte Carlo technique using the Correlation and Logic (CORAL) free software available on the Internet (http://www.insilico.eu/coral). Quantitative structure-activity relationships (QSARs) serve to develop predictive models for organophosphates. The predictive potential of these models is quite good: the determination coefficient for the validation set ranged from 0.87 to 0.90. These models were built up according to the principle ‘QSARs is a random event’, that is, predictive potential of an approach should be checked up with several splits of available data into the training and test sets. The special scheme of mechanistic interpretation definition is represented. The mechanistic interpretation is based on probabilities of molecular features to be in the sub-group of promoters of increase for endpoint or in sub-group of promoters of it is decrease.

Keywords:

• Organophosphate
• pesticide toxicity
• QSAR
• risk assessment
• SMILES
• Monte Carlo method

Acknowledgments

The authors are grateful for the contribution of the project LIFE-CONCERT contract (LIFE17 GIE/IT/000461) and Optitox (OC/EFSA/SCER/2018/01) for support.

Ethical approval

The manuscript is not submitted to any other journal.

Consent to participate

The article did not involve any human participants.

Consent to publish

The submitted work is original.

Author contributions

APT was involved in formal analysis, data collection, and curation, investigation, methodology incl. statistics, software, visualization, writing of original draft, and revision. AAT was involved in conceptualization, data curation, formal analysis, investigation, methodology incl. statistics, software, visualization, writing of original draft, review, and editing. AR was involved in conceptualization, formal analysis, visualization, writing of original draft, review, and editing. EB was involved in conceptualization, formal analysis, visualization, review, and editing.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.

Data availability statement

All data generated or analyzed during this study are included in this article (and its supplementary information files).

Additional information

Funding

Not applicable.