Quantitative Retention (Structure)-Activity Relationships in Predicting the Pharmaceutical and Toxic Properties of Potential Pesticides

Molecules. 2022 Jun 3;27(11):3599. doi: 10.3390/molecules27113599.

Abstract

The micellar liquid chromatography technique and quantitative retention (structure)-activity relationships method were used to predict properties of carbamic and phenoxyacetic acids derivatives, newly synthesized in our laboratory and considered as potential pesticides. Important properties of the test substances characterizing their potential significance as pesticides as well as threats to humans were considered: the volume of distribution, the unbonded fractions, the blood-brain distribution, the rate of skin and cell permeation, the dermal absorption, the binding to human serum albumin, partitioning between water and plants' cuticles, and the lethal dose. Pharmacokinetic and toxicity parameters were predicted as functions of the solutes' lipophilicities and the number of hydrogen bond donors, the number of hydrogen bond acceptors, and the number of rotatable bonds. The equations that were derived were evaluated statistically and cross-validated. Important features of the molecular structure influencing the properties of the tested substances were indicated. The QSAR models that were developed had high predictive ability and high reliability in modeling the properties of the molecules that were tested. The investigations highlighted the applicability of combined chromatographic technique and QS(R)ARs in modeling the important properties of potential pesticides and reducing unethical animal testing.

Keywords: QRARs; QSARs; lipophilicity; micellar chromatography; pesticides.

MeSH terms

  • Animals
  • Chromatography, Liquid / methods
  • Pesticides* / toxicity
  • Quantitative Structure-Activity Relationship
  • Reproducibility of Results
  • Solutions
  • Structure-Activity Relationship

Substances

  • Pesticides
  • Solutions

Grants and funding

This research received no external funding.