Classical and 3D QSAR studies of larvicidal monoterpenes against Aedes aegypti: new molecular insights for the rational design of more active compounds

Abstract

Listen

Translate article

Monoterpenes are compounds found on essential oils of diverse plants, with biological activities such as repellent, insecticidal and larvicidal against some organism and microorganism species. Dengue, Chikungunya, and Zika are important public health problems caused by viruses, which are transmitted by the bite of Aedes aegypti mosquitoes. One of the most common strategies to combat these diseases is the control of the vector proliferation, by physical and chemical methods. Thus, the design, synthesis, and test of the compounds with larvicidal profile have emerged as an important research line. In this paper, we present the use of computational approaches to provide robust, predictive, and conveniently interpretable quantitative structure-activity relationships models, involving a series of 55 monoterpenes and structurally related compounds, which presented larvicidal activity against females of Aedes aegypti, expressed by IC50. Through the proposition and analysis of 2D and 3D molecular descriptors, consistent and easily understood molecular bases about larvicidal activity are provided, for the proposition of new molecules with more active profile. Theoretical geometry optimization of the 55 compounds was performed using the PM6 semiempirical Hamiltonian, followed by B3LYP/6-31+G(d) level of theory, using Gaussian 09W® package. A set of classical descriptors was obtained from Dragon® software for each compound and submitted to a variable selection procedure, using the Ordered Predictors Selector (OPS) algorithm, considering larvicidal (pIC50) activities previously reported. Then, a 3D quantitative structure-activity relationship (QSAR) investigation was performed by Open3DQSAR program, using the same values of activity, for the investigation of sterical and electrostatic molecular fields. For classical QSAR, five descriptors were selected as the most important, providing a robust and predictive QSAR model via multiple linear regression (MLR). In addition, a good 3D-QSAR model was found, with a clear interpretation of the physical sense of the fields, according to the classical model. Molecules with more elongated structures contain a six-membered ring with 1,4 substitution pattern, highest lipophilicity, less volume on a central moiety, and lateral hydrophobic chain at six-membered ring, tend to be more actives.