Using molecular docking-based binding energy to predict toxicity of binary mixture with different binding sites

Area of Science:

• Environmental Chemistry
• Toxicology
• Computational Chemistry

Background:

• Environmental chemical pollution presents complex mixtures.
• Individual chemicals can bind to various sites on target proteins, complicating toxicity prediction.
• Understanding these interactions is crucial for environmental risk assessment.

Purpose of the Study:

• To develop a general approach for predicting the toxicity of chemical mixtures.
• To utilize molecular docking-based binding energy (Ebinding) for toxicity prediction.
• To establish a relationship between mixture toxicity and individual chemical properties.

Main Methods:

• Selected examples of chemical mixtures with same and different binding sites/target proteins (aldehydes, cyanogenic toxicants, triazines, urea herbicides, sulfonamides, trimethoprim).
• Employed molecular docking to determine binding energy (Ebinding) for individual chemicals.
• Correlated Ebinding and logKow(mix) with binary mixture toxicity (EC50M).

Main Results:

• A general relationship was found between binary mixture toxicity (EC50M) and the binding energy (Ebinding) and logKow(mix) of individual chemicals.
• Ebinding effectively describes how individual chemicals interact at different binding sites.
• The proposed approach shows promise for predicting mixture toxicity.

Conclusions:

• A general and simplified model for predicting chemical mixture toxicity to microorganisms was developed.
• Molecular docking-based binding energy (Ebinding) is a valuable parameter for assessing mixture toxicity.
• This approach can help understand and predict the environmental impact of complex chemical mixtures.