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Updated: Sep 28, 2025

Assessment of Chemical Toxicity in Adult Drosophila Melanogaster

Assessment of Chemical Toxicity in Adult Drosophila Melanogaster

Published on: March 24, 2023

Structure-to-process design framework for developing safer pesticides.

Jessica M Lewer¹, Zachary R Stickelman¹, Jessica H Huang¹

¹Department of Chemistry, The George Washington University, 800 22nd St NW, Ste 4000, Washington, DC 20052-0066, USA.

Science Advances

|March 30, 2022

Summary

This summary is machine-generated.

Developing safer pesticides is crucial. This study introduces a computational framework to design pesticides with controlled degradation and low ecotoxicity, aiding green chemistry efforts.

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Area of Science:

Green Chemistry
Computational Toxicology
Environmental Science

Background:

Designing pesticides with tunable degradation and low ecotoxicity is a major challenge in green chemistry.
Current computational toxicology methods lack a multifaceted approach for system-based chemical development.
Predictive toxicology needs enhanced design-vectoring tools for novel pesticide development.

Purpose of the Study:

To develop a tiered computational framework for rational pesticide design.
To integrate photodegradation kinetics, thermodynamics, ecotoxicity, and performance predictions.
To provide a user-friendly roadmap for designing novel pesticides with desirable characteristics.

Main Methods:

A tiered computational framework integrating photodegradation (kinetics and thermodynamics) with ecotoxicity and performance predictions.
Utilizing cutoff values in mechanistically derived physicochemical and electronic parameters.
Validation against experimental data and application to 700 pesticides from the U.S. EPA registry.

Main Results:

The framework successfully integrates multiple pesticide properties, including degradation and ecotoxicity.
Screening of 700 existing pesticides identified application-ready candidates with desirable traits.
Demonstrated ability to link structural attributes to process-based outcomes and quantify trade-offs.

Conclusions:

The developed computational framework offers a powerful and user-friendly approach for rational pesticide design.
This method facilitates the identification of novel pesticides with improved safety, degradation, and performance profiles.
The study advances green chemistry by providing tools to mitigate environmental impact and enhance pesticide efficacy.