QSAR-based evaluation of plant-derived larvicidal agents against Zika vector Aedes aegypti via Monte Carlo optimization and SMILES-based descriptors and molecular docking.

Abstract

Aedes aegypti is the principal vector responsible for the transmission of several arboviral diseases, including dengue, Zika, chikungunya, and yellow fever, posing a significant threat to global public health. Controlling its population is crucial to limiting the spread of these infections. Among the most effective strategies is the use of larvicides derived from plant sources, which interfere with the mosquito's development and reduce its proliferation. This study presents a QSAR analysis of 255 plant-based larvicidal compounds against Aedes aegypti (Zika vector), using pLC₅₀ values as the measure of bioactivity. QSAR models were developed using the CORAL software, which applies a Monte Carlo optimization algorithm to determine the correlation weights of molecular descriptors. The predictive power and reliability of the models were extensively validated using several statistical indicators. Results demonstrated that the models were robust, simple, and predictive, with validation metrics including r², Q², IIC, and CII ranging from 0.6877 to 0.7820, 0.6622 to 0.7643, 0.5638 to 0.8324, and 0.8248 to 0.8548, respectively. Based on these models, important molecular descriptors influencing the enhancement or reduction of larvicidal activity were determined. Furthermore, molecular docking studies were performed to investigate the binding interactions and conformational poses of the selected compounds.