Quantitative structure-activity relationships for chemical toxicity to environmental bacteria

Area of Science:

• Environmental microbiology
• Toxicology
• Computational chemistry

Background:

• Assessing chemical toxicity is crucial for environmental engineering.
• Quantitative structure-activity relationships (QSARs) offer a predictive approach to chemical toxicity.
• Understanding bacterial toxicity is vital for environmental risk assessment.

Purpose of the Study:

• To develop QSARs for nonreactive chemical toxicity to key environmental bacteria.
• To evaluate different QSAR methodologies for accuracy and applicability.
• To identify chemical classes and specific compounds that deviate from predicted toxicity.

Main Methods:

• QSARs were developed for aerobic heterotrophs, methanogens, Nitrosomonas, and Microtox.
• Three methods were assessed: log P, linear solvation energy relationships (LSER), and molecular connectivity.
• Chemicals included environmental pollutants like substituted benzenes, phenols, and aliphatic hydrocarbons.

Main Results:

• Successful QSARs were achieved for all bacterial groups and methods, with adjusted r2 values from 0.79 to 0.95.
• LSER models demonstrated the highest accuracy and broadest chemical applicability.
• Log P and molecular connectivity QSARs offered greater ease of use due to parameter availability.

Conclusions:

• QSARs provide a reliable tool for predicting nonreactive chemical toxicity to environmental bacteria.
• LSER, log P, and molecular connectivity QSARs are effective, with varying trade-offs in accuracy and usability.
• Outliers identified potential reactive toxicity or specific bacterial sensitivities, aiding in refined risk assessments.