Toxicity study of allelochemical-like pesticides by a combination of 3D-QSAR, docking, Local Binding Energy (LBE) and GRID approaches

Abstract

3D-QSAR, Docking, Local Binding Energy (LBE) and GRID methods were integrated as a tool for predicting toxicity and studying mechanisms of action. The method was tested on a set of 73 allelochemical-like pesticides, for which acute toxicity (LD₅₀) for the rat was available. 3D-QSAR gave a model with high predictive ability and the regression maps indicated the important toxic chemical substituents. Significant ligand-protein residue interactions and oxidation positions in the binding site were found by docking analysis using CYP1A2 homology modelling. The binding energies of the compounds and the important substituents (Local Binding Energy, LBE) were calculated in order to demonstrate quantitatively the substituent contributions in the metabolism and toxicity. The GRID examination identified the CYP1A2 binding pocket feature. Finally, a 3D-QSAR map was compared to the GRID map, showing good overlaps and confirming the important role of CYP1A2 in allelochemical-like compounds toxicity.

Keywords:

• 3D-QSAR
• Docking
• GRID
• LBE
• Allelochemicals
• P450

Acknowledgements

We gratefully acknowledge the financial support from the research training network entitled “Intelligent Modeling Algorithms for General Evaluations of Toxicities” (IMAGETOX) (HPRN-CT-1999-00015) and FATEALLCHEM EC Project (QLK5-CT-2001-01967). Thanks due to Dr Irini Doychinova for Chem-X software.