Using molecular quantum similarity measures as descriptors in quantitative structure-toxicity relationships

Area of Science:

• Computational chemistry
• Cheminformatics
• Toxicology

Background:

• Molecular quantum similarity measures (MQSM) are increasingly used in Quantitative Structure-Property Relationship (QSPR) studies.
• Existing research shows relationships between MQSM and log P values, suggesting MQSM as a theoretical alternative to empirical hydrophobic parameters.
• There is a need for novel descriptors to accurately model molecular toxicity.

Purpose of the Study:

• To utilize molecular quantum similarity measures (MQSM) for describing molecular toxicity.
• To develop Quantitative Structure-Toxicity Relationship (QSTR) models using MQSM.
• To introduce and evaluate a new type of MQSM based on electron-electron repulsion energy.

Main Methods:

• Application of molecular quantum similarity measures (MQSM).
• Development of Quantitative Structure-Toxicity Relationship (QSTR) models.
• Introduction of a novel MQSM based on the expectation value of electron-electron repulsion energy.
• Utilizing four different molecular datasets for toxicity prediction.

Main Results:

• MQSM were successfully employed to describe molecular toxicity.
• QSTR models were constructed, demonstrating the utility of MQSM in predicting toxicological endpoints.
• The new electron-electron repulsion energy-based MQSM showed promise as a descriptor.

Conclusions:

• MQSM are effective tools for describing molecular toxicity and building QSTR models.
• Theoretical MQSM can serve as a valuable alternative to empirical hydrophobic parameters in QSPR.
• The novel MQSM presented offers a new avenue for molecular property prediction and toxicity assessment.