Quantitative structure-activity relationship study of amide mosquito repellents

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Toxicology

Background:

• Mosquito-borne diseases pose significant public health challenges.
• Effective insect repellents are crucial for disease prevention.
• Understanding structure-activity relationships can guide the development of novel repellents.

Purpose of the Study:

• To establish a quantitative structure-activity relationship (QSAR) model for amide repellents.
• To identify key molecular descriptors influencing repellency against Aedes aegypti.
• To validate the predictive power and stability of the developed QSAR model.

Main Methods:

• Utilized a heuristic method for QSAR analysis of 43 amide repellents.
• Employed Gaussian software for molecular structure sketching and optimization.
• Generated and screened molecular parameters using CODESSA 2.7.10 software.
• Applied the leave-one-out method for robust model validation.

Main Results:

• Developed a four-descriptor QSAR model with a high coefficient of determination (r² = 0.897).
• Achieved excellent average r² values for both the training set (0.901) and test set (0.863).
• Confirmed the model's stability and predictability through rigorous validation.

Conclusions:

• The QSAR model effectively predicts the repellency of amides against Aedes aegypti.
• Key molecular descriptors are linked to charge distribution and dipole moment, influencing repellent activity.
• Findings support the rational design of more potent and effective amide-based insect repellents.