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Related Experiment Videos

Three-dimensional quantitative structure-activity relationship study for phenylsulfonyl carboxylates using CoMFA and

Xinhui Liu1, Zhifeng Yang, Liansheng Wang

  • 1State Key Laboratory of Environmental Simulation and Pollution Control, Institute of Environmental Sciences, Beijing Normal University, 19 Xinjiekouwai Street, Beijing 100875, PR China. 1xh065@yahoo.com

Chemosphere
|September 25, 2003
PubMed
Summary

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This study developed two quantitative structure-activity relationship (3D-QSAR) models to predict the toxicity of phenylsulfonyl carboxylates. The comparative molecular field analysis (CoMFA) model showed superior predictive power for compound toxicity.

Area of Science:

  • Computational chemistry
  • Toxicology
  • Medicinal chemistry

Background:

  • Phenylsulfonyl carboxylates are a class of compounds with potential toxicological relevance.
  • Understanding the structure-activity relationships of these compounds is crucial for predicting and mitigating their toxicity.
  • Photobacterium phosphoreum is a commonly used marine bacterium for acute toxicity testing.

Purpose of the Study:

  • To develop and compare two 3D-QSAR models, CoMFA and CoMSIA, for predicting the acute toxicity of phenylsulfonyl carboxylates.
  • To identify key structural features influencing the toxicity of these compounds.
  • To gain insights into the toxic mechanisms of phenylsulfonyl carboxylates.

Main Methods:

  • Comparative molecular field analysis (CoMFA) was employed to build a 3D-QSAR model.

Related Experiment Videos

  • Comparative molecular similarity indices analysis (CoMSIA) was used to develop a second 3D-QSAR model.
  • The models were validated using leave-one-out cross-validation and conventional correlation coefficients.

    • Main Results:

    • The CoMFA model achieved a cross-validated correlation coefficient (q2) of 0.823 and a conventional correlation coefficient (r2) of 0.958.
    • The CoMSIA model yielded a q2 of 0.713 and an r2 of 0.933.
    • The CoMFA model's higher q2 and r2 values indicate a significant correlation between steric/electrostatic fields and biological activity.

    Conclusions:

    • The developed CoMFA model demonstrates significant predictive capability for the acute toxicity of phenylsulfonyl carboxylates.
    • Analysis of CoMFA contour maps provides insights into critical structural properties and potential toxic mechanisms.
    • While CoMSIA is faster, CoMFA offers superior accuracy for this dataset, highlighting the importance of steric and electrostatic factors.