Cheminformatics finds novel pesticides: Analytical targeting

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  • Published: Jan 15, 2019
  • Author: David Bradley
  • Channels: Chemometrics & Informatics
thumbnail image: Cheminformatics finds novel pesticides: Analytical targeting

Persica pest

Cheminformatics is being used by a team from Romania and Japan to help in the search for next-generation insecticides that could be used as successors to the standard neonicotinoids.

Cheminformatics is being used by a team from Romania and Japan to help in the search for next-generation insecticides that could be used as successors to the standard neonicotinoids.

Neonicotinoid pesticides are a significant alternative to the prior generation of agrochemicals with their well-publicised problems. They have high insecticidal potency, which means less is needed to kill pest species on a crop. They also have very low mammalian toxicity as well as activity even against aphids that have developed resistance to other insecticides.

Unfortunately, the use of these compounds has fallen out of environmental favour because of the emergence of evidence linking them to the idiopathic problem of bee colony collapse disorder in bees and so new even more targeted neonicotinoids that zero in on a specific pest species.

Model behaviour

Now, L. Crisan, A. Borota, and S. Funar-Timofei of the Computational Chemistry Department, at the Institute of Chemistry Timisoara of the Romanian Academy, in Timisoara, Romania and T. Suzuki of the Natural Science Laboratory, at Toyo University, in Bunkyo-ku, Tokyo, Japan, have used linear and non-linear regression techniques to carry out an in silico study of novel insecticides that might have none of the alleged problems associated with neonicotinoids and still protect a crop plant against pest species, such as the peach potato aphid Myzus persicae.

M. persicae is the most agriculturally important aphid pest of the peach tree, Prunus persica. The presence of the aphid reduces growth, shrivel leaves and kills various tissues plant. Moreover, the aphid is a vector for plant viruses, such as potato virus Y, potato leafroll virus as well as so-called mosaic viruses to other food crops, and plum pox virus.

The team has carried out Multiple Linear Regression (MLR), Partial Least Squares regression (PLS), Artificial Neural Networks (ANN), Support Vector Machine (SVM) and Pharmacophore modelling to help them identify novel insecticides against this pest. They have modelled activity that allows them to predict the correlation between the insecticidal profile based on experimental toxicity values, and molecular descriptors, calculated from the energy optimized structures.

Pesticide candidates

"Four new potential insecticides active against M. persicae and their predicted pLC50 toxicity values were reported for the first time," the team reports in the journal Molecular Informatics. "The models presented can be used as an approach in the screening and prioritization of chemicals in a scientific and regulatory frame and for toxicity prediction," the team explains.

Related Links

Mol. Inform. 2019, online: "An Approach to Identify New Insecticides Against Myzus Persicae. In Silico Study Based on Linear and Non-Linear Regression Techniques"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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