The electronic factor in QSAR: MO-parameters, competing interactions, reactivity and toxicity

Area of Science:

• Environmental chemistry and toxicology
• Computational chemistry
• Chemical reactivity modeling

Background:

• Reactive chemicals present unique challenges for developing Structure-Activity Relationships (SAR) and Quantitative Structure-Activity Relationships (QSAR).
• Accurate modeling of stereoelectronic interactions between toxicants and biological systems necessitates quantifiable electronic structure parameters for chemicals.
• Early methodologies for reactivity modeling often lacked the precision required for complex chemical interactions.

Purpose of the Study:

• To review historical approaches to modeling chemical reactivity.
• To emphasize the utility of generalized polyelectronic perturbation theory (GPPT) in environmental chemistry and toxicology.
• To demonstrate the application of GPPT in developing QSAR models for predicting the toxicity of reactive chemicals.

Main Methods:

• Review of early reactivity modeling approaches.
• Application of generalized polyelectronic perturbation theory (GPPT).
• Utilizing superdelocalizability and frontier orbital charges for QSAR of soft electrophiles and proelectrophiles.
• Incorporating atomic charges and bond orders for QSAR of hard electrophiles like organophosphates.

Main Results:

• GPPT provides a robust framework for quantifying electronic structure parameters relevant to chemical reactivity.
• QSAR models based on GPPT successfully predict the toxicity of soft electrophiles and proelectrophiles.
• Accurate prediction of hard electrophile toxicity requires specific parameters like atomic charges and bond orders.
• Considerations for factor orthogonality and chemical classification are crucial for effective reactivity modeling.

Conclusions:

• Generalized polyelectronic perturbation theory (GPPT) is a valuable tool for developing QSAR models for reactive toxicants.
• The choice of electronic parameters (e.g., superdelocalizability, atomic charges) is critical and depends on the electrophile's nature (soft vs. hard).
• Further research into factor orthogonality and classification schemes will enhance the predictive power of QSAR in environmental toxicology.