Density Functional Theory in the Prediction of Mutagenicity: A Perspective

被引:19
作者
Townsend, Piers A. [1 ]
Grayson, Matthew N. [2 ]
机构
[1] Univ Bath, Ctr Sustainable Chem Technol, Dept Chem, Bath BA2 7AY, Avon, England
[2] Univ Bath, Dept Chem, Bath BA2 7AY, Avon, England
基金
英国工程与自然科学研究理事会;
关键词
D O I
10.1021/acs.chemrestox.0c00113
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
As a field, computational toxicology is concerned with using in silico models to predict and understand the origins of toxicity. It is fast, relatively inexpensive, and avoids the ethical conundrum of using animals in scientific experimentation. In this perspective, we discuss the importance of computational models in toxicology, with a specific focus on the different model types that can be used in predictive toxicological approaches toward mutagenicity (SARs and QSARs). We then focus on how quantum chemical methods, such as density functional theory (DFT), have previously been used in the prediction of mutagenicity. It is then discussed how DFT allows for the development of new chemical descriptors that focus on capturing the steric and energetic effects that influence toxicological reactions. We hope to demonstrate the role that DFT plays in understanding the fundamental, intrinsic chemistry of toxicological reactions in predictive toxicology.
引用
收藏
页码:179 / 188
页数:10
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