The use of in silico models in the prediction of genotoxicity potentials of pharmaceuticals
Genotoxicity: Advances in Research and Applications, NOVA Publications , ss.31-51, 2023
- Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
- Basım Tarihi: 2023
- Yayınevi: NOVA Publications
- Sayfa Sayıları: ss.31-51
- Anahtar Kelimeler: Ames test, Genotoxicity, In silico models, QSAR, Toxicity prediction
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
Evaluation of genotoxic potential is important for the risk and safety assessment of many compounds such as cosmetics, personal care products, environmental pollutants, food, human and veterinary drugs and nanocarriers. In vitro and in vivo methods are generally used for the evaluation of the genotoxic potential of these compounds. Besides these methods, however, there has been an increasing interest in in silico methods for the genotoxic assessment of potential toxic substances. In silico models are a computational method used in toxicology to predict the potential adverse effects of compounds based on their chemical structure. Most of these models focus on bacterial reverse mutation analysis (Ames test). Compared to experimental toxicity tests such as comet and micronucleus tests, these models are cheaper and easier. In recent years, a large number of computer models have been available for the prediction of the genotoxicity of a given compound. Among these models is the quantitative structure-activity relationships (QSAR) approaches. This model is remarkable because it is more for its economic importance and not involving the use of model animals. These models assume that compounds with similar structures have similar physicochemical and toxicological properties. Thus, it provides the opportunity to analyze many substances in a short time and to prioritize compounds in this category for among these substances for experimental toxicity assessment tests. This chapter is aimed to present the genotoxic potential of various compounds with in silico models and to demonstrate the latest developments in this field.