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Structure-activity relationships (SARs) among mutagens and carcinogens: a review
Environmental Mutagenesis
|January 1, 1986
Summary
This review introduces structure-activity relationship (SAR) methods for evaluating mutagenicity and carcinogenicity. Modern computational approaches, particularly those using molecular connectivity, are highlighted for their effectiveness with large, diverse datasets in predicting environmental substance toxicity.
Area of Science:
- Toxicology
- Computational Chemistry
- Medicinal Chemistry
Background:
- Early attempts correlated molecular structure with biological activity.
- Structure-activity relationships (SARs) are crucial for understanding chemical toxicity.
- Evaluating mutagenicity and carcinogenicity requires robust predictive methods.
Purpose of the Study:
- To review methods for evaluating structure-activity relationships (SARs).
- To focus on SAR methods applied to mutagenicity and carcinogenicity.
- To highlight the utility of computational approaches for toxicity prediction.
Main Methods:
- Discussion of extrathermodynamic and physical property variables (e.g., Hansch method, SIMCA).
- Exploration of molecular connectivity approaches (e.g., ADAPT, CASE, Enslein methods).
- Review of computer-aided storage, retrieval, and analysis techniques.
Main Results:
- Molecular connectivity methods are effective for large, diverse mutagenicity/carcinogenicity databases.
- These methods are less sensitive to experimental variability and misclassifications.
- Specific methods (ADAPT, CASE, SIMCA, Enslein) show classification powers of 75-95% depending on the database.
- Physicochemical and extrathermodynamic methods are useful for smaller, congeneric datasets.
Conclusions:
- Computer-aided SAR methods offer a timely approach to predicting and understanding environmental substance toxicity.
- These methods are valuable tools for toxicological research.
- Further development is ongoing to explore the full predictive potential of these techniques.