Neonicotinoid insecticide design: molecular docking, multiple chemometric approaches, and toxicity relationship with Cowpea aphids
Neonicotinoids are the fastest-growing class of insecticides successfully applied in plant protection, human and animal health care. The significant resistance increases led to the urgent need for alternative new neonicotinoids, with improved insecticidal activity. We performed molecular docking to describe a common binding mode of neonicotinoids into the nicotinic acetylcholine receptor, and to select the appropriate conformations to derive models. These were further used in a QSAR study employing both linear and nonlinear approaches to model the inhibitory activity against the Cowpea aphids. Linear modeling was performed by multiple linear regression and partial least squares and nonlinear modeling by artificial neural networks and support vector machine methods. The OECD principles were considered for QSAR models validation. Robust models with predictive power were found for neonicotinoid diverse structures. Based on our QSAR and docking outcomes, five new insecticides were predicted, according to the model applicability domain, the ligand efficiencies, and the binding mode. Therefore, the developed models can be confidently used for the prediction of the insecticidal activity of new chemicals, saving a substantial amount of time and money and, also, contributing to the chemical risk assessment.
KeywordsNeonicotinoids Cowpea aphids QSAR MLR PLS ANN SVM Docking
Quantitative structure–activity relationship
Organization for Economic Cooperation and Development
Nicotinic acetylcholine receptor
- C. Aphids
Cowpea aphids or Aphis craccivora
Multiple linear regression
Partial least squares
Artificial neural networks
Support vector machine
Principal component analysis
Lymnaea stagnalis Acetylcholine Binding Protein
Variable Importance in the Projection
Cross-validation correlation coefficient
Mean absolute error
Concordance correlation coefficient
Variance inflation factor
Multi-Criteria Decision Making
Access to the Chemaxon Ltd., OpenEye Ltd., and QSARINS (from Prof. Paola Gramatica from the University of Insubria, Varese, Italy) software is greatly acknowledged by the authors.
This work was financially supported by the Project No. 1.1/2017 of the Institute of Chemistry Timişoara of Romanian Academy.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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