Related Experiment Video
Updated: Jul 25, 2026

14:45
Transgenic Rodent Assay for Quantifying Male Germ Cell Mutant Frequency
Published on: August 6, 2014
Salmonella mutagenicity and rodent carcinogenicity: quantitative structure-activity relationships
B W Blake1, K Enslein, V K Gombar
1HDi, Rochester, NY 14604.
Mutation Research
|July 1, 1990
Summary
Structure-activity relationships accurately predict genotoxicity and carcinogenicity in chemicals. These models distinguish genotoxic from non-genotoxic carcinogens and carcinogenic from non-carcinogenic non-genotoxins, aiding chemical safety assessments.
Area of Science:
- Toxicology
- Computational Chemistry
- Chemical Safety
Background:
- The NCI/NTP compiled 222 rodent carcinogenicity bioassays and Salmonella mutagenicity bioassays (Ames tests).
- Ashby and Tennant (1988) categorized compounds into genotoxic (Ames-positive) and non-genotoxic (Ames-negative) groups based on structural characteristics.
- The Ames test was identified as sufficient for genotoxicity identification, outperforming other short-term bioassays or batteries.
Purpose of the Study:
- To develop structure-activity relationship (SAR) models for predicting chemical carcinogenicity and genotoxicity.
- To classify carcinogens into genotoxic and non-genotoxic groups using SAR.
- To classify non-genotoxic compounds into carcinogenic and non-carcinogenic groups using SAR.
Main Methods:
- Utilized 222 NCI/NTP carcinogenicity bioassays and Ames tests.
- Developed QSAR models using molecular descriptors (sigma charge, connectivity indices, shape descriptors, substructure descriptors).
- Validated models for discriminating between genotoxic/non-genotoxic carcinogens and carcinogenic/non-carcinogenic non-genotoxins.
Main Results:
- Achieved 94.5% accuracy in distinguishing genotoxic from non-genotoxic carcinogens using an 8-descriptor equation.
- Achieved 95.2% accuracy in distinguishing carcinogenic from non-carcinogenic non-genotoxins using a 25-descriptor equation.
- Demonstrated high classification accuracy (approx. 95%) for both categories based solely on structural information.
Conclusions:
- Developed robust SAR models capable of predicting genotoxicity and carcinogenicity.
- These models enable classification of chemicals without requiring animal bioassay data.
- The findings support the use of SAR for chemical safety assessments and regulatory purposes.
Related Concept Videos
Mutagenicity and Carcinogenicity
Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
Structure-Activity Relationships and Drug Design
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
Toxicity Testing in Animals
Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...

